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  1. .ipynb_checkpoints/job_A100-checkpoint.sh +17 -0
  2. .ipynb_checkpoints/job_A100_phi-checkpoint.sh +23 -0
  3. .ipynb_checkpoints/retrieval_head_detection-checkpoint.py +640 -0
  4. PaulGrahamEssays/addiction.txt +116 -0
  5. PaulGrahamEssays/aord.txt +126 -0
  6. PaulGrahamEssays/apple.txt +201 -0
  7. PaulGrahamEssays/avg.txt +375 -0
  8. PaulGrahamEssays/before.txt +387 -0
  9. PaulGrahamEssays/bias.txt +54 -0
  10. PaulGrahamEssays/boss.txt +218 -0
  11. PaulGrahamEssays/copy.txt +81 -0
  12. PaulGrahamEssays/corpdev.txt +107 -0
  13. PaulGrahamEssays/desres.txt +234 -0
  14. PaulGrahamEssays/diff.txt +73 -0
  15. PaulGrahamEssays/ecw.txt +98 -0
  16. PaulGrahamEssays/founders.txt +83 -0
  17. PaulGrahamEssays/foundervisa.txt +5 -0
  18. PaulGrahamEssays/gap.txt +485 -0
  19. PaulGrahamEssays/gba.txt +198 -0
  20. PaulGrahamEssays/gh.txt +434 -0
  21. PaulGrahamEssays/goodtaste.txt +86 -0
  22. PaulGrahamEssays/hubs.txt +156 -0
  23. PaulGrahamEssays/iflisp.txt +46 -0
  24. PaulGrahamEssays/island.txt +55 -0
  25. PaulGrahamEssays/know.txt +53 -0
  26. PaulGrahamEssays/langdes.txt +242 -0
  27. PaulGrahamEssays/laundry.txt +487 -0
  28. PaulGrahamEssays/love.txt +376 -0
  29. PaulGrahamEssays/mod.txt +54 -0
  30. PaulGrahamEssays/newideas.txt +114 -0
  31. PaulGrahamEssays/nft.txt +26 -0
  32. PaulGrahamEssays/philosophy.txt +429 -0
  33. PaulGrahamEssays/popular.txt +602 -0
  34. PaulGrahamEssays/pow.txt +10 -0
  35. PaulGrahamEssays/rootsoflisp.txt +41 -0
  36. PaulGrahamEssays/rss.txt +3 -0
  37. PaulGrahamEssays/siliconvalley.txt +292 -0
  38. PaulGrahamEssays/startuplessons.txt +395 -0
  39. PaulGrahamEssays/submarine.txt +217 -0
  40. PaulGrahamEssays/sun.txt +43 -0
  41. PaulGrahamEssays/superangels.txt +302 -0
  42. PaulGrahamEssays/todo.txt +22 -0
  43. PaulGrahamEssays/unions.txt +42 -0
  44. PaulGrahamEssays/useful.txt +225 -0
  45. PaulGrahamEssays/vb.txt +129 -0
  46. PaulGrahamEssays/vcsqueeze.txt +124 -0
  47. PaulGrahamEssays/vw.txt +75 -0
  48. PaulGrahamEssays/want.txt +43 -0
  49. PaulGrahamEssays/web20.txt +299 -0
  50. PaulGrahamEssays/weird.txt +30 -0
.ipynb_checkpoints/job_A100-checkpoint.sh ADDED
@@ -0,0 +1,17 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+
3
+ #SBATCH --job-name=rh_q7b
4
+ #SBATCH --nodes=1 # Request 1 compute node per job instance
5
+ #SBATCH --cpus-per-task=4
6
+ #SBATCH --gres=gpu:a100:1
7
+ #SBATCH --mem=36GB # Request 2GB of RAM per job instance
8
+ #SBATCH --time=02:30:00 # Request 10 mins per job instance
9
+ #SBATCH --output=/scratch/spp9399/output_logs/rh_outputs/qwen25_7b_og_%A.out # The output will be saved here. %A will be replaced by the slurm job ID, and %a will be replaced by the SLURM_ARRAY_TASK_ID
10
+ #SBATCH [email protected] # Email address
11
+ #SBATCH --mail-type=BEGIN,END # Send an email when all the instances of this job are completed
12
+
13
+ module purge # unload all currently loaded modules in the environment
14
+
15
+
16
+ MODEL_PATH="/scratch/spp9399/LLMS/Qwen2.5-7B-Instruct"
17
+ PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True /scratch/spp9399/env/retrieval_heads/run_env.sh python3 retrieval_head_detection.py --model_path $MODEL_PATH --s 0 --e 50000
.ipynb_checkpoints/job_A100_phi-checkpoint.sh ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ #!/bin/bash
2
+
3
+ #SBATCH --job-name=phi
4
+ #SBATCH --nodes=1 # Request 1 compute node per job instance
5
+ #SBATCH --cpus-per-task=4
6
+ #SBATCH --gres=gpu:a100:2
7
+ #SBATCH --mem=64GB # Request 2GB of RAM per job instance
8
+ #SBATCH --time=02:00:00 # Request 10 mins per job instance
9
+ #SBATCH --output=/scratch/spp9399/output_logs/rh_outputs/phi_%A.out # The output will be saved here. %A will be replaced by the slurm job ID, and %a will be replaced by the SLURM_ARRAY_TASK_ID
10
+ #SBATCH [email protected] # Email address
11
+ #SBATCH --mail-type=BEGIN,END # Send an email when all the instances of this job are completed
12
+
13
+ module purge # unload all currently loaded modules in the environment
14
+
15
+ export WANDB_ENTITY=ETNLP_Project
16
+ export WANDB_PROJECT=retrieval-head-detection
17
+
18
+ MODEL_PATH="/scratch/spp9399/LLMS/Phi-3.5-mini-instruct"
19
+ # PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True /scratch/spp9399/env/retrieval_heads/run_env.sh python3 retrieval_head_detection.py --model_path $MODEL_PATH -s 0 -e 50000 --haystack_dir /scratch/spp9399/ETNLP/original/Retrieval_Head/haystack_for_detect/en --needle_lg en --exp_name phi_35_mini_inst_en
20
+
21
+ PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True /scratch/spp9399/env/retrieval_heads/run_env.sh python3 retrieval_head_detection.py --model_path $MODEL_PATH -s 0 -e 50000 --haystack_dir /scratch/spp9399/ETNLP/original/Retrieval_Head/haystack_for_detect/zh --needle_lg zh --exp_name phi_35_mini_inst_zh
22
+
23
+ # PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True /scratch/spp9399/env/retrieval_heads/run_env.sh python3 retrieval_head_detection.py --model_path $MODEL_PATH -s 0 -e 50000 --haystack_dir /scratch/spp9399/ETNLP/original/Retrieval_Head/haystack_for_detect/de --needle_lg de --exp_name phi_35_mini_inst_de
.ipynb_checkpoints/retrieval_head_detection-checkpoint.py ADDED
@@ -0,0 +1,640 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ """
2
+ This script is adapted from
3
+ https://github.com/gkamradt/LLMTest_NeedleInAHaystack
4
+
5
+ # GPT-4
6
+ (
7
+ python -u needle_in_haystack.py --s_len 0 --e_len 128000\
8
+ --model_provider OpenAI\
9
+ --model_name gpt-4-1106-preview
10
+ --api_key $OPENAI_API_KEY
11
+ ) 2>&1 | tee logs/eval_gpt_4_128k.log
12
+
13
+ # LLaMA 2 32K. Remember to download the model first
14
+ (
15
+ python -u needle_in_haystack.py --s_len 0 --e_len 128000\
16
+ --model_provider LLaMA\
17
+ --model_path ../../../Llama-2-7B-32K-Instruct
18
+ ) 2>&1 | tee logs/eval_llama2_32k_instruct.log
19
+
20
+ # LongChat. Remember to download the model first
21
+ (
22
+ python -u needle_in_haystack.py --s_len 0 --e_len 128000\
23
+ --model_provider LLaMA\
24
+ --model_path /ML-A800/models/longchat-7b-v1.5-32k
25
+ ) 2>&1 | tee logs/eval_longchat.log
26
+
27
+ # Our llama-2-7b-80k, requires 4*80G A100
28
+ # require you to download the model first
29
+ (
30
+ python -u needle_in_haystack.py --s_len 0 --e_len 128000\
31
+ --model_provider LLaMA\
32
+ --model_path ../../../llama-2-7b-80k
33
+ ) 2>&1 | tee logs/eval_llama-2-7b-80k.log
34
+ """
35
+
36
+ #import tiktoken
37
+ import os
38
+ import glob
39
+ import json
40
+ from transformers import AutoTokenizer, AutoModel, AutoModelForCausalLM, AutoConfig
41
+ import sys
42
+ sys.path.append("./faiss_attn/")
43
+ from source.modeling_llama import LlamaForCausalLM
44
+ from source.modeling_qwen2 import Qwen2ForCausalLM
45
+ from source.modeling_mixtral import MixtralForCausalLM
46
+ from source.modeling_mistral import MistralForCausalLM
47
+ from source.modeling_phi3 import Phi3ForCausalLM
48
+ import numpy as np
49
+ import argparse
50
+ from rouge_score import rouge_scorer
51
+ from datetime import datetime, timezone
52
+ from collections import defaultdict
53
+ import time
54
+ import torch
55
+
56
+ import wandb
57
+ from rouge_chinese import Rouge
58
+ import jieba
59
+ from matplotlib import pyplot as plt
60
+ import matplotlib.patches as mpatches
61
+
62
+
63
+ def reset_rope(model, model_max_train_len, scaling_factor):
64
+ for l in model.model.layers:
65
+ l.self_attn.rotary_emb.scaling_factor = scaling_factor
66
+ l.self_attn.rotary_emb._set_cos_sin_cache(seq_len=model_max_train_len, device=l.self_attn.rotary_emb.inv_freq.device, dtype=torch.float32)
67
+ return
68
+ scorer = rouge_scorer.RougeScorer(['rouge1', 'rougeL'], use_stemmer=True)
69
+ scorer_zh = Rouge()
70
+
71
+ class LLMNeedleHaystackTester:
72
+ """
73
+ This class is used to test the LLM Needle Haystack.
74
+ """
75
+ def __init__(self,
76
+ needle="\nThe best thing to do in San Francisco is eat a sandwich and sit in Dolores Park on a sunny day.\n",
77
+ haystack_dir="./haystack_for_detect/wiki_en/",
78
+ retrieval_question="What is the best thing to do in San Francisco?",
79
+ results_version = 1,
80
+ context_lengths_min = 1000,
81
+ context_lengths_max = 50000,
82
+ context_lengths_num_intervals = 20,
83
+ context_lengths = None,
84
+ document_depth_percent_min = 0,
85
+ document_depth_percent_max = 100,
86
+ document_depth_percent_intervals = 10,
87
+ document_depth_percents = None,
88
+ document_depth_percent_interval_type = "linear",
89
+ model_provider = "OpenAI",
90
+ model_name='',
91
+ model_name_suffix=None,
92
+ num_concurrent_requests = 1,
93
+ save_results = True,
94
+ save_contexts = True,
95
+ final_context_length_buffer = 200,
96
+ seconds_to_sleep_between_completions = None,
97
+ print_ongoing_status = True,
98
+ exp_name=None,
99
+ needle_lg=None):
100
+ """
101
+ :param needle: The needle to be found in the haystack. Default is None.
102
+ :param haystack_dir: The directory of text files to use as background context (or a haystack) in which the needle is to be found. Default is Paul Graham Essays.
103
+ :param retrieval_question: The question which with to prompt the model to do the retrieval.
104
+ :param results_version: In case you would like to try the same combination of model, context length, and depth % multiple times, change the results version other than 1
105
+ :param num_concurrent_requests: Due to volume, this object is set up to run concurrent requests, default = 1. Be careful of rate limits.
106
+ :param save_results: Whether or not you would like to save your contexts to file. Warning: These will get long! Default = True
107
+ :param save_contexts: Whether or not you would like to save your contexts to file. Warning: These will get long! Default is True.
108
+ :param final_context_length_buffer: The amount of cushion you'd like to leave off the input context to allow for the output context. Default 200 tokens
109
+ :param context_lengths_min: The minimum length of the context. Default is 1000.
110
+ :param context_lengths_max: The maximum length of the context. Default is 200000.
111
+ :param context_lengths_num_intervals: The number of intervals for the context length. Default is 35.
112
+ :param context_lengths: The lengths of the context. Default is None.
113
+ :param document_depth_percent_min: The minimum depth percent of the document. Default is 0.
114
+ :param document_depth_percent_max: The maximum depth percent of the document. Default is 100.
115
+ :param document_depth_percent_intervals: The number of intervals for the document depth percent. Default is 35.
116
+ :param document_depth_percents: The depth percentages of the document. Default is None.
117
+ :param document_depth_percent_interval_type: The type of interval for the document depth percent. Must be either 'linear' or 'sigmoid'. Default is 'linear'.
118
+ :param model_provider: The provider of the model. Must be either 'OpenAI' or 'Anthropic'. Default is 'OpenAI'.
119
+ :param openai_api_key: The API key for OpenAI. Default is None.
120
+ :param anthropic_api_key: The API key for Anthropic. Default is None.
121
+ :param model_name: The name of the model. Default is 'gpt-4-1106-preview'.
122
+ :param seconds_to_sleep_between_completions: The number of seconds to sleep between completions. Default is None.
123
+ :param print_ongoing_status: Whether or not to print the ongoing status. Default is True.
124
+ :param exp_name: Name of the exp. This will be used to save files. Default is True.
125
+ :param needle_lg: Needle language. This will be used to determine the rouge_scorer
126
+ """
127
+
128
+ if not needle or not haystack_dir or not retrieval_question:
129
+ raise ValueError("Needle, haystack, and retrieval_question must be provided.")
130
+ if not exp_name or not needle_lg:
131
+ raise ValueError("exp_name and needle_lg must be provided")
132
+
133
+ self.wandb_run = wandb.init(name=exp_name)
134
+
135
+ needles_and_stacks = [json.loads(l) for l in open(f"{haystack_dir}/needles.jsonl")]
136
+ self.needle_list = [l["needle"] for l in needles_and_stacks]
137
+ self.haystack_dir_list = [f"{haystack_dir}/part{i}" for i in range(1, 4)]
138
+ self.retrieval_question_list = [l["question"] for l in needles_and_stacks]
139
+ self.real_ansers_list = [l["real_needle"] for l in needles_and_stacks]
140
+ self.results_version = results_version
141
+ self.num_concurrent_requests = num_concurrent_requests
142
+ self.save_results = save_results
143
+ self.final_context_length_buffer = final_context_length_buffer
144
+ self.save_contexts = save_contexts
145
+ self.seconds_to_sleep_between_completions = seconds_to_sleep_between_completions
146
+ self.print_ongoing_status = print_ongoing_status
147
+ self.model_provider = model_provider
148
+ self.testing_results = []
149
+ self.head_counter = defaultdict(list)
150
+ self.exp_name = exp_name
151
+ self.needle_lg = needle_lg
152
+ if("/" in model_name):
153
+ self.model_version = model_name.split("/")[-1]
154
+ else: self.model_version = model_name
155
+ if(model_name_suffix is not None): self.model_version += "_" + model_name_suffix
156
+
157
+ if context_lengths is None:
158
+ if context_lengths_min is None or context_lengths_max is None or context_lengths_num_intervals is None:
159
+ raise ValueError("Either context_lengths_min, context_lengths_max, context_lengths_intervals need to be filled out OR the context_lengths_list needs to be supplied.")
160
+ else:
161
+ self.context_lengths = np.round(np.linspace(context_lengths_min, context_lengths_max, num=context_lengths_num_intervals, endpoint=True)).astype(int)
162
+ else:
163
+ self.context_lengths = context_lengths
164
+
165
+ if document_depth_percents is None:
166
+ if document_depth_percent_min is None or document_depth_percent_max is None or document_depth_percent_intervals is None:
167
+ raise ValueError("Either document_depth_percent_min, document_depth_percent_max, document_depth_percent_intervals need to be filled out OR the document_depth_percents needs to be supplied.")
168
+ else:
169
+ if document_depth_percent_interval_type == 'linear':
170
+ self.document_depth_percents = np.round(np.linspace(document_depth_percent_min, document_depth_percent_max, num=document_depth_percent_intervals, endpoint=True)).astype(int)
171
+ elif document_depth_percent_interval_type == 'sigmoid':
172
+ self.document_depth_percents = [self.logistic(x) for x in np.linspace(document_depth_percent_min, document_depth_percent_max, document_depth_percent_intervals)]
173
+ else:
174
+ self.document_depth_percents = document_depth_percents
175
+
176
+ if document_depth_percent_interval_type not in [None, "linear", "sigmoid"]:
177
+ raise ValueError("document_depth_percent_interval_type must be either None, 'linear' or 'sigmoid'. If you'd like your own distribution give a list of ints in via document_depth_percent_intervals")
178
+
179
+ self.model_name = model_name
180
+
181
+ self.enc = AutoTokenizer.from_pretrained(model_name, use_fast=False)
182
+ print("loading from %s" % model_name)
183
+ config = AutoConfig.from_pretrained(model_name)
184
+ self.layer_num, self.head_num = config.num_hidden_layers, config.num_attention_heads
185
+ print(f"layer number: {self.layer_num}, head number {self.head_num}")
186
+ if "Qwen" in self.model_version:
187
+ self.model_to_test = Qwen2ForCausalLM.from_pretrained(
188
+ model_name,torch_dtype="auto",device_map='balanced',use_flash_attention_2="flash_attention_2"
189
+ ).eval()
190
+ elif "Mixtral" in self.model_version:
191
+ self.model_to_test = MixtralForCausalLM.from_pretrained(
192
+ model_name,torch_dtype="auto",device_map='balanced',use_flash_attention_2="flash_attention_2",trust_remote_code=True,
193
+ ).eval()
194
+ elif "Mistral" in self.model_version:
195
+ self.model_to_test = MistralForCausalLM.from_pretrained(
196
+ model_name,torch_dtype="auto",device_map='balanced',use_flash_attention_2="flash_attention_2",trust_remote_code=True,
197
+ ).eval()
198
+ elif "Phi" in self.model_version:
199
+ self.model_to_test = Phi3ForCausalLM.from_pretrained(
200
+ model_name,torch_dtype="auto",device_map='balanced',use_flash_attention_2="flash_attention_2",trust_remote_code=True,
201
+ ).eval()
202
+ else:
203
+ self.model_to_test = LlamaForCausalLM.from_pretrained(model_name,
204
+ use_flash_attention_2="flash_attention_2", torch_dtype=torch.bfloat16,device_map='balanced').eval()
205
+
206
+ if 'llama-2-7b-80k' in self.model_version:
207
+ scaling_factor = 10
208
+ reset_rope(self.model_to_test, model_max_train_len=81920, scaling_factor=scaling_factor)
209
+
210
+ if "CUDA_VISIBLE_DEVICES" in os.environ:
211
+ self.multi_gpus = len(os.environ["CUDA_VISIBLE_DEVICES"])>1
212
+ else:
213
+ self.multi_gpus = True
214
+
215
+ self.model_to_test_description = model_name
216
+ self.evaluation_model = None
217
+ self.debug='debug'
218
+ model_name = model_name.split('/')[-1]
219
+
220
+ def logistic(self, x, L=100, x0=50, k=.1):
221
+ if x == 0:
222
+ return 0
223
+ if x == 100:
224
+ return 100
225
+ return np.round(L / (1 + np.exp(-k * (x - x0))), 3)
226
+
227
+ def bound_evaluate_and_log(self, *args):
228
+ self.evaluate_and_log(*args)
229
+
230
+ def run_test(self, args):
231
+ # Run through each iteration of context_lengths and depths
232
+ tasks = []
233
+
234
+ for context_length in self.context_lengths:
235
+ if context_length < args.s_len or context_length > args.e_len: continue
236
+ for depth_percent in self.document_depth_percents:
237
+ task = self.bound_evaluate_and_log(context_length, depth_percent)
238
+
239
+ def retrieval_calculate(self, attention_maxtrix,retrieval_score, inp, step_token,topk=1):
240
+ for layer_idx in range(self.layer_num):
241
+ for head_idx in range(self.head_num):
242
+ values, idx = attention_maxtrix[layer_idx][0][head_idx][-1].topk(topk)
243
+ for v, i in zip(values, idx):
244
+ if self.needle_start <= i < self.needle_end and inp.item()==self.prompt_ids[i].item():
245
+ retrieval_score[layer_idx][head_idx][0] += 1/(self.needle_end - self.needle_start)
246
+ retrieval_score[layer_idx][head_idx][1] += step_token
247
+ break
248
+ def retrieval_head_accumulate(self, retrieval_score):
249
+ for layer_idx in range(self.layer_num):
250
+ for head_idx in range(self.head_num):
251
+ self.head_counter[f"{layer_idx}-{head_idx}"].append(retrieval_score[layer_idx][head_idx][0])
252
+
253
+ def decode(self, q_outputs, inp, decode_len, block_list=None):
254
+ output, retrieval_score = [], [[[0, ''] for _ in range(self.head_num)] for _ in range(self.layer_num)]
255
+ past_kv = q_outputs.past_key_values
256
+ for step_i in range(decode_len):
257
+ inp = inp.view(1, 1)
258
+ outputs = self.model_to_test(input_ids=inp, past_key_values=past_kv, use_cache=True, output_attentions=True, attn_mode="torch" )
259
+ past_kv = outputs.past_key_values
260
+ inp = outputs.logits[0, -1].argmax()
261
+ step_token = self.enc.convert_ids_to_tokens(inp.item())
262
+ output.append(inp.item())
263
+ self.retrieval_calculate(outputs.attentions, retrieval_score, inp, step_token)
264
+ if step_token=='<0x0A>' or inp.item()==144: break
265
+ return output, retrieval_score
266
+
267
+ def find_needle_idx(self, needle):
268
+ needle_ids = self.enc(needle, add_special_tokens=False)["input_ids"]
269
+ print( self.enc.decode(needle_ids, skip_special_tokens=False))
270
+ span_len = len(needle_ids)
271
+ for i in range(len(self.prompt_ids)):
272
+ token_span = self.prompt_ids[i : i + span_len]
273
+ span_ids = set(token_span.tolist())
274
+ overlap = float(len(span_ids.intersection(set(needle_ids)))) / len(set(needle_ids))
275
+ if(overlap > 0.9):
276
+ return i, i + span_len
277
+ return -1, -1
278
+
279
+ def evaluate_and_log(self, context_length, depth_percent):
280
+ # Checks to see if you've already checked a length/percent/version.
281
+ # This helps if the program stop running and you want to restart later
282
+ # Go generate the required length context and place your needle statement in
283
+ context = self.generate_context(context_length, depth_percent)
284
+ question = f"Based on the content of the book, Question: {self.retrieval_question}\nAnswer:"
285
+ '''
286
+ if self.model_version=="Qwen1.5-14B-Chat":
287
+ context = "<|im_start|>system\nYou are a helpful assistant<|im_end|>\n<|im_start|>user\n" + context input_context = "f{context}\nquestion<|im_end|>\n<|im_start|>assistant\n
288
+ question += '<|im_end|>\n<|im_start|>assistant\n'
289
+ input_ids = self.enc(input_context , return_tensors="pt")['input_ids']
290
+ '''
291
+ if self.model_version in ["Mistral-7B-Instruct-v0.2", "Qwen1.5-14B-Chat"]:
292
+ prompt = [
293
+ {"role": "user", "content": f"<book>{context}</book>\nBased on the content of the book, Question: {self.retrieval_question}\nAnswer:"},
294
+ ]
295
+ input_ids = self.enc.apply_chat_template(conversation=prompt, tokenize=True, add_generation_prompt=True, return_tensors='pt')
296
+ else:
297
+ input_context = context + question
298
+ input_ids = self.enc(input_context , return_tensors="pt")['input_ids']
299
+
300
+ # Prepare your message to send to the model you're going to evaluate
301
+ test_start_time = time.time()
302
+ self.prompt_ids = input_ids[0, :]
303
+ if not self.multi_gpus:
304
+ input_ids = input_ids.to(self.model_to_test.device)
305
+ self.needle_start, self.needle_end = self.find_needle_idx(self.real_needle)
306
+ print("Needle start and end", self.needle_start, self.needle_end )
307
+ with torch.no_grad():
308
+ q_outputs = self.model_to_test(input_ids=input_ids[:,:-1], use_cache=True, return_dict=True)
309
+ output, retrieval_score = self.decode(q_outputs, input_ids[:,-1], 75) # 75 -- german requires more than 50
310
+ response = self.enc.decode(output,skip_special_tokens=True).strip()
311
+
312
+ test_end_time = time.time()
313
+ test_elapsed_time = test_end_time - test_start_time
314
+
315
+ try:
316
+ if self.needle_lg == 'zh':
317
+ score = scorer_zh.get_scores(' '.join(jieba.cut(response)), ' '.join(jieba.cut(self.real_needle)))[0]["rouge-1"]["r"]*100
318
+ else:
319
+ score = scorer.score(self.real_needle, response)['rouge1'].recall*100
320
+ except Exception as e:
321
+ print("[ERROR]", e, "response:", response)
322
+ score = 0
323
+
324
+ ## if recall > 50, we determine this retrieval succeed and update the retrieval score
325
+ if score > 50:
326
+ self.retrieval_head_accumulate(retrieval_score)
327
+ head_score = [(i[0], np.mean(i[1])) for i in self.head_counter.items()]
328
+ head_score = sorted(head_score, key=lambda x:x[1], reverse=True)
329
+ print([[i[0]] for i in head_score][:20])
330
+
331
+ results = {
332
+ 'model' : self.model_to_test_description,
333
+ 'context_length' : int(context_length),
334
+ 'depth_percent' : float(depth_percent),
335
+ 'version' : self.results_version,
336
+ 'needle' : self.needle,
337
+ 'model_response' : response,
338
+ 'score' : score,
339
+ 'test_duration_seconds' : test_elapsed_time,
340
+ 'test_timestamp_utc' : datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M:%S%z'),
341
+ 'ni': int(self.ni)
342
+ }
343
+
344
+ self.wandb_run.log(results)
345
+
346
+ self.testing_results.append(results)
347
+
348
+ if self.print_ongoing_status:
349
+ print (f"-- Test Summary -- ")
350
+ print (f"Duration: {test_elapsed_time:.1f} seconds")
351
+ print (f"Context: {context_length} tokens")
352
+ print (f"Depth: {depth_percent}%")
353
+ print (f"Score: {score}")
354
+ print (f"Response: {response}\n")
355
+
356
+ context_file_location = f'{self.model_version.replace(".", "_")}_len_{context_length}_depth_{int(depth_percent*100)}_{self.ni}'
357
+
358
+ if self.save_contexts:
359
+ results['file_name'] : context_file_location
360
+
361
+ # Save the context to file for retesting
362
+ if not os.path.exists('contexts'):
363
+ os.makedirs('contexts')
364
+
365
+ if not os.path.exists(f'contexts/{self.exp_name}'):
366
+ os.makedirs(f'contexts/{self.exp_name}')
367
+
368
+ with open(f'contexts/{self.exp_name}/{context_file_location}_context.txt', 'w') as f:
369
+ f.write(context)
370
+
371
+ if self.save_results:
372
+ # Save the context to file for retesting
373
+ if not os.path.exists(f'results/graph/{self.exp_name}'):
374
+ os.makedirs(f'results/graph/{self.exp_name}')
375
+
376
+ # Save the result to file for retesting
377
+ p = f'results/graph/{self.exp_name}/{context_file_location}_results.json'
378
+ print("Writing at %s" % p)
379
+ with open(p, 'w') as f:
380
+ json.dump(results, f)
381
+
382
+ def result_exists(self, context_length, depth_percent):
383
+ """
384
+ Checks to see if a result has already been evaluated or not
385
+ """
386
+
387
+ results_dir = 'results/' + self.model_version
388
+ print("Searching existing results at %s" % results_dir)
389
+ if not os.path.exists(results_dir):
390
+ return False
391
+ for filename in os.listdir(results_dir):
392
+ if filename.endswith('.json'):
393
+ with open(os.path.join(results_dir, filename), 'r') as f:
394
+ result = json.load(f)
395
+ context_length_met = result['context_length'] == context_length
396
+ depth_percent_met = result['depth_percent'] == depth_percent
397
+ version_met = result.get('version', 1) == self.results_version
398
+ model_met = result['model'] == self.model_name
399
+ # import ipdb; ipdb.set_trace()
400
+ if context_length_met and depth_percent_met and version_met and model_met:
401
+ return True
402
+ return False
403
+
404
+ def generate_context(self, context_length, depth_percent):
405
+ # Load up tiktoken so we navigate tokens more easily
406
+
407
+ # Get your Paul Graham files loaded into a string
408
+ context = self.read_context_files()
409
+
410
+ # Truncate the Paul Graham essays to the context length you desire
411
+ context = self.encode_and_trim(context, context_length)
412
+
413
+ # Insert your random statement according to your depth percent
414
+ context = self.insert_needle(context, depth_percent, context_length)
415
+
416
+ return context
417
+
418
+ def encode_text_to_tokens(self, text):
419
+ if self.model_provider in ["OpenAI", "LLaMA", "Mistral", "GLM"]:
420
+ return self.enc.encode(text)
421
+ elif self.model_provider == "Anthropic":
422
+ # Assuming you have a different encoder for Anthropic
423
+ return self.enc.encode(text).ids
424
+ else:
425
+ raise ValueError("model_provider must be either 'OpenAI' or 'Anthropic'")
426
+
427
+ def insert_needle(self, context, depth_percent, context_length):
428
+ tokens_needle = self.encode_text_to_tokens(self.needle)
429
+ tokens_context = self.encode_text_to_tokens(context)
430
+
431
+ # Reducing the context length by 150 buffer. This is to account for system message, the user question, and response.
432
+ context_length -= self.final_context_length_buffer
433
+
434
+ # If your context + needle are longer than the context length (which it will be), then reduce tokens from the context by the needle length
435
+ if len(tokens_context) + len(tokens_needle) > context_length:
436
+ tokens_context = tokens_context[:context_length - len(tokens_needle)]
437
+
438
+ if depth_percent == 100:
439
+ # If your depth percent is 100 (which means your needle is the last thing in the doc), throw it at the end
440
+ tokens_new_context = tokens_context + tokens_needle
441
+ else:
442
+ # Go get the position (in terms of tokens) to insert your needle
443
+ insertion_point = int(len(tokens_context) * (depth_percent / 100))
444
+ # import ipdb; ipdb.set_trace()
445
+
446
+ # tokens_new_context represents the tokens before the needle
447
+ tokens_new_context = tokens_context[:insertion_point]
448
+
449
+ # We want to make sure that we place our needle at a sentence break so we first see what token a '.' is
450
+ if(self.model_provider in ["LLaMA", "LongLLaMA"]): period_tokens = [29889, 869]
451
+ elif(self.model_provider == "Mistral"): period_tokens = [842, 28723]
452
+ elif(self.model_provider == "GLM"): period_tokens = [918, 30930]
453
+ else: period_tokens = self.encode_text_to_tokens('.')
454
+
455
+ # Then we iteration backwards until we find the first period
456
+ while tokens_new_context and tokens_new_context[-1] not in period_tokens:
457
+ insertion_point -= 1
458
+ tokens_new_context = tokens_context[:insertion_point]
459
+
460
+ print("insertion at %d" % insertion_point)
461
+ # Once we get there, then add in your needle, and stick the rest of your context in on the other end.
462
+ # Now we have a needle in a haystack
463
+ tokens_new_context += tokens_needle + tokens_context[insertion_point:]
464
+
465
+ # Convert back to a string and return it
466
+ new_context = self.decode_tokens(tokens_new_context)
467
+ return new_context
468
+
469
+ def get_context_length_in_tokens(self, context):
470
+ print( self.model_provider )
471
+ if self.model_provider in ["OpenAI", "LLaMA", "Mistral", "GLM"]:
472
+ return len(self.enc.encode(context))
473
+ elif self.model_provider == "Anthropic":
474
+ # Assuming you have a different encoder for Anthropic
475
+ encoded = self.enc.encode(context)
476
+ return len(self.enc.encode(context).ids)
477
+ else:
478
+
479
+ raise ValueError("model_provider must be either 'OpenAI' or 'Anthropic'")
480
+
481
+ def read_context_files(self):
482
+ context = ""
483
+ max_context_length = max(self.context_lengths)
484
+
485
+ # For zh use encoder to get token length
486
+ if self.needle_lg == 'zh':
487
+ while self.get_context_length_in_tokens(context) < max_context_length:
488
+ for file in glob.glob(f"{self.haystack_dir}/*.txt"):
489
+ print(file)
490
+ with open(file, 'r') as f:
491
+ context += f.read()
492
+ else:
493
+ while len(context.split()) < max_context_length:
494
+ for file in glob.glob(f"{self.haystack_dir}/*.txt"):
495
+ with open(file, 'r') as f:
496
+ context += f.read()
497
+ return context
498
+
499
+ def get_tokens_from_context(self, context):
500
+ if self.model_provider in ["OpenAI", "LLaMA", "Mistral", "GLM"]:
501
+ return self.enc.encode(context)
502
+ elif self.model_provider == "Anthropic":
503
+ # Assuming you have a different encoder for Anthropic
504
+ return self.enc.encode(context).ids
505
+ else:
506
+ raise ValueError("model_provider must be either 'OpenAI' or 'Anthropic'")
507
+
508
+ def decode_tokens(self, tokens, context_length=None):
509
+ if self.model_provider in ["OpenAI", "LLaMA", "Mistral", "GLM"]:
510
+ return self.enc.decode(tokens[:context_length])
511
+ elif self.model_provider == "Anthropic":
512
+ # Assuming you have a different decoder for Anthropic
513
+ return self.enc.decode(tokens[:context_length])
514
+ else:
515
+ raise ValueError("model_provider must be either 'OpenAI' or 'Anthropic'")
516
+
517
+ def encode_and_trim(self, context, context_length):
518
+ tokens = self.get_tokens_from_context(context)
519
+ if len(tokens) > context_length:
520
+ context = self.decode_tokens(tokens, context_length)
521
+ return context
522
+
523
+ def get_results(self):
524
+ return self.testing_results
525
+
526
+ def print_start_test_summary(self):
527
+ print ("\n")
528
+ print ("Starting Needle In A Haystack Testing...")
529
+ print (f"- Model: {self.model_name}")
530
+ print (f"- Context Lengths: {len(self.context_lengths)}, Min: {min(self.context_lengths)}, Max: {max(self.context_lengths)}")
531
+ print (f"- Document Depths: {len(self.document_depth_percents)}, Min: {min(self.document_depth_percents)}%, Max: {max(self.document_depth_percents)}%")
532
+ print (f"- Needle: {self.needle.strip()}")
533
+ print ("\n\n")
534
+
535
+ def wandb_plot(self):
536
+ with open(f"head_score/{self.exp_name}.json", 'r') as f:
537
+ head_list = json.load( f )
538
+ head_score_list = [([int(ll) for ll in l[0].split("-")],np.mean(l[1])) for l in head_list.items()]
539
+ head_score_list = sorted(head_score_list, key=lambda x: x[1], reverse=True)
540
+ top_retrieval_heads = [[l[0], round(np.mean(l[1]), 2)] for l in head_score_list]
541
+
542
+ scores = [ i[1] for i in top_retrieval_heads ]
543
+
544
+ def get_color(score):
545
+ if score >= 0.5:
546
+ return '#FF4C4C' # red
547
+ elif score >= 0.1:
548
+ return '#FFA07A' # light coral / salmon
549
+ elif score > 0.0:
550
+ return '#4682B4' # steel blue
551
+ else:
552
+ return '#ADD8E6' # light blue
553
+
554
+ color_grouped_scores = defaultdict(float)
555
+ for score in scores:
556
+ color_grouped_scores[get_color(score)] += 1
557
+
558
+ sorted_groups = sorted(color_grouped_scores.items(), key=lambda x: x[1], reverse=True)
559
+
560
+ grouped_scores = [v for _, v in sorted_groups]
561
+ grouped_colors = [c for c, _ in sorted_groups]
562
+
563
+ color_meanings = {
564
+ '#FF4C4C': '≥ 0.5',
565
+ '#FFA07A': '0.1 – 0.5',
566
+ '#4682B4': '0.0 – 0.1',
567
+ '#ADD8E6': '0'
568
+ }
569
+
570
+ legend_handles = [mpatches.Patch(color=color, label=color_meanings[color]) for color in grouped_colors]
571
+
572
+ fig, ax = plt.subplots(figsize=(16, 16))
573
+ wedges, texts, autotexts = ax.pie(
574
+ grouped_scores,
575
+ labels=None, # No labels
576
+ autopct='%1.1f%%',
577
+ startangle=90,
578
+ colors=grouped_colors,
579
+ wedgeprops=dict(width=0.4)
580
+ )
581
+
582
+ centre_circle = plt.Circle((0, 0), 0.70, fc='white')
583
+ fig.gca().add_artist(centre_circle)
584
+ ax.axis('equal')
585
+ plt.title(f"Top Retrieval Head Colors {self.exp_name} {self.model_version}")
586
+ plt.legend(handles=legend_handles, title="Score Range", loc="upper right")
587
+ self.wandb_run.log({f"retrieval_head_{self.model_version}_{self.exp_name}": wandb.Image(fig)})
588
+ plt.close(fig)
589
+
590
+ def start_test(self, args):
591
+ for ni in range(len(self.needle_list)):
592
+ self.ni = ni # Used for storing results
593
+ self.needle = self.needle_list[ni]
594
+ self.haystack_dir = self.haystack_dir_list[ni]
595
+ self.real_needle = self.real_ansers_list[ni]
596
+ self.retrieval_question = self.retrieval_question_list[ni]
597
+ if self.print_ongoing_status:
598
+ self.print_start_test_summary()
599
+ self.run_test(args)
600
+ if os.path.exists(f"head_score/{self.exp_name}.json"):
601
+ with open(f"./head_score/{self.exp_name}.json", "r") as file:
602
+ head_counter = json.loads(file.readline())
603
+ for k,v in head_counter.items():
604
+ self.head_counter[k] += v
605
+ with open(f"head_score/{self.exp_name}.json", 'w') as f:
606
+ json.dump(self.head_counter, f)
607
+
608
+ self.wandb_plot()
609
+
610
+
611
+ if __name__ == "__main__":
612
+ # Tons of defaults set, check out the LLMNeedleHaystackTester's init for more info
613
+ parser = argparse.ArgumentParser()
614
+ parser.add_argument('-s', '--s_len', metavar='N', type=int, help='a number')
615
+ parser.add_argument('-e', '--e_len', metavar='N', type=int, help='a number')
616
+ parser.add_argument('--model_path', type=str, default=None, help='path to model')
617
+ parser.add_argument('--model_name', type=str, default=None, help='name of model')
618
+ parser.add_argument('--model_name_suffix', type=str, default=None, help='name of model')
619
+ parser.add_argument('--model_provider', type=str, default="LLaMA", help='which model to use')
620
+ parser.add_argument("--haystack_dir", type=str, default="en", help="haystack dir")
621
+ parser.add_argument("--exp_name", type=str, default=None, help="name of the exp, this will be used to save the files")
622
+ parser.add_argument("--needle_lg", type=str, default=None, help="needle lang, this will be used to determine the rouge scorer")
623
+ args = parser.parse_args()
624
+
625
+ model_name = args.model_path
626
+
627
+
628
+ ht = LLMNeedleHaystackTester(model_name=model_name,
629
+ model_name_suffix=args.model_name_suffix,
630
+ model_provider=args.model_provider,
631
+ save_contexts=True,
632
+ save_results=True,
633
+ context_lengths_min=args.s_len,
634
+ context_lengths_max=args.e_len,
635
+ exp_name=args.exp_name,
636
+ needle_lg=args.needle_lg,
637
+ haystack_dir=args.haystack_dir
638
+ )
639
+
640
+ ht.start_test(args)
PaulGrahamEssays/addiction.txt ADDED
@@ -0,0 +1,116 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ July 2010What hard liquor, cigarettes, heroin, and crack have in common is
2
+ that they're all more concentrated forms of less addictive predecessors.
3
+ Most if not all the things we describe as addictive are. And the
4
+ scary thing is, the process that created them is accelerating.We wouldn't want to stop it. It's the same process that cures
5
+ diseases: technological progress. Technological progress means
6
+ making things do more of what we want. When the thing we want is
7
+ something we want to want, we consider technological progress good.
8
+ If some new technique makes solar cells x% more efficient, that
9
+ seems strictly better. When progress concentrates something we
10
+ don't want to want—when it transforms opium into heroin—it seems
11
+ bad. But it's the same process at work.
12
+ [1]No one doubts this process is accelerating, which means increasing
13
+ numbers of things we like will be transformed into things we like
14
+ too much.
15
+ [2]As far as I know there's no word for something we like too much.
16
+ The closest is the colloquial sense of "addictive." That usage has
17
+ become increasingly common during my lifetime. And it's clear why:
18
+ there are an increasing number of things we need it for. At the
19
+ extreme end of the spectrum are crack and meth. Food has been
20
+ transformed by a combination of factory farming and innovations in
21
+ food processing into something with way more immediate bang for the
22
+ buck, and you can see the results in any town in America. Checkers
23
+ and solitaire have been replaced by World of Warcraft and FarmVille.
24
+ TV has become much more engaging, and even so it can't compete with Facebook.The world is more addictive than it was 40 years ago. And unless
25
+ the forms of technological progress that produced these things are
26
+ subject to different laws than technological progress in general,
27
+ the world will get more addictive in the next 40 years than it did
28
+ in the last 40.The next 40 years will bring us some wonderful things. I don't
29
+ mean to imply they're all to be avoided. Alcohol is a dangerous
30
+ drug, but I'd rather live in a world with wine than one without.
31
+ Most people can coexist with alcohol; but you have to be careful.
32
+ More things we like will mean more things we have to be careful
33
+ about.Most people won't, unfortunately. Which means that as the world
34
+ becomes more addictive, the two senses in which one can live a
35
+ normal life will be driven ever further apart. One sense of "normal"
36
+ is statistically normal: what everyone else does. The other is the
37
+ sense we mean when we talk about the normal operating range of a
38
+ piece of machinery: what works best.These two senses are already quite far apart. Already someone
39
+ trying to live well would seem eccentrically abstemious in most of
40
+ the US. That phenomenon is only going to become more pronounced.
41
+ You can probably take it as a rule of thumb from now on that if
42
+ people don't think you're weird, you're living badly.Societies eventually develop antibodies to addictive new things.
43
+ I've seen that happen with cigarettes. When cigarettes first
44
+ appeared, they spread the way an infectious disease spreads through
45
+ a previously isolated population. Smoking rapidly became a
46
+ (statistically) normal thing. There were ashtrays everywhere. We
47
+ had ashtrays in our house when I was a kid, even though neither of
48
+ my parents smoked. You had to for guests.As knowledge spread about the dangers of smoking, customs changed.
49
+ In the last 20 years, smoking has been transformed from something
50
+ that seemed totally normal into a rather seedy habit: from something
51
+ movie stars did in publicity shots to something small huddles of
52
+ addicts do outside the doors of office buildings. A lot of the
53
+ change was due to legislation, of course, but the legislation
54
+ couldn't have happened if customs hadn't already changed.It took a while though—on the order of 100 years. And unless the
55
+ rate at which social antibodies evolve can increase to match the
56
+ accelerating rate at which technological progress throws off new
57
+ addictions, we'll be increasingly unable to rely on customs to
58
+ protect us.
59
+ [3]
60
+ Unless we want to be canaries in the coal mine
61
+ of each new addiction—the people whose sad example becomes a
62
+ lesson to future generations—we'll have to figure out for ourselves
63
+ what to avoid and how. It will actually become a reasonable strategy
64
+ (or a more reasonable strategy) to suspect
65
+ everything new.In fact, even that won't be enough. We'll have to worry not just
66
+ about new things, but also about existing things becoming more
67
+ addictive. That's what bit me. I've avoided most addictions, but
68
+ the Internet got me because it became addictive while I was using
69
+ it.
70
+ [4]Most people I know have problems with Internet addiction. We're
71
+ all trying to figure out our own customs for getting free of it.
72
+ That's why I don't have an iPhone, for example; the last thing I
73
+ want is for the Internet to follow me out into the world.
74
+ [5]
75
+ My latest trick is taking long hikes. I used to think running was a
76
+ better form of exercise than hiking because it took less time. Now
77
+ the slowness of hiking seems an advantage, because the longer I
78
+ spend on the trail, the longer I have to think without interruption.Sounds pretty eccentric, doesn't it? It always will when you're
79
+ trying to solve problems where there are no customs yet to guide
80
+ you. Maybe I can't plead Occam's razor; maybe I'm simply eccentric.
81
+ But if I'm right about the acceleration of addictiveness, then this
82
+ kind of lonely squirming to avoid it will increasingly be the fate
83
+ of anyone who wants to get things done. We'll increasingly be
84
+ defined by what we say no to.
85
+ Notes[1]
86
+ Could you restrict technological progress to areas where you
87
+ wanted it? Only in a limited way, without becoming a police state.
88
+ And even then your restrictions would have undesirable side effects.
89
+ "Good" and "bad" technological progress aren't sharply differentiated,
90
+ so you'd find you couldn't slow the latter without also slowing the
91
+ former. And in any case, as Prohibition and the "war on drugs"
92
+ show, bans often do more harm than good.[2]
93
+ Technology has always been accelerating. By Paleolithic
94
+ standards, technology evolved at a blistering pace in the Neolithic
95
+ period.[3]
96
+ Unless we mass produce social customs. I suspect the recent
97
+ resurgence of evangelical Christianity in the US is partly a reaction
98
+ to drugs. In desperation people reach for the sledgehammer; if
99
+ their kids won't listen to them, maybe they'll listen to God. But
100
+ that solution has broader consequences than just getting kids to
101
+ say no to drugs. You end up saying no to
102
+ science as well.
103
+ I worry we may be heading for a future in which only a few people
104
+ plot their own itinerary through no-land, while everyone else books
105
+ a package tour. Or worse still, has one booked for them by the
106
+ government.[4]
107
+ People commonly use the word "procrastination" to describe
108
+ what they do on the Internet. It seems to me too mild to describe
109
+ what's happening as merely not-doing-work. We don't call it
110
+ procrastination when someone gets drunk instead of working.[5]
111
+ Several people have told me they like the iPad because it
112
+ lets them bring the Internet into situations where a laptop would
113
+ be too conspicuous. In other words, it's a hip flask. (This is
114
+ true of the iPhone too, of course, but this advantage isn't as
115
+ obvious because it reads as a phone, and everyone's used to those.)Thanks to Sam Altman, Patrick Collison, Jessica Livingston, and
116
+ Robert Morris for reading drafts of this.
PaulGrahamEssays/aord.txt ADDED
@@ -0,0 +1,126 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ October 2015When I talk to a startup that's been operating for more than 8 or
2
+ 9 months, the first thing I want to know is almost always the same.
3
+ Assuming their expenses remain constant and their revenue growth
4
+ is what it has been over the last several months, do they make it to
5
+ profitability on the money they have left? Or to put it more
6
+ dramatically, by default do they live or die?The startling thing is how often the founders themselves don't know.
7
+ Half the founders I talk to don't know whether they're default alive
8
+ or default dead.If you're among that number, Trevor Blackwell has made a handy
9
+ calculator you can use to find out.The reason I want to know first whether a startup is default alive
10
+ or default dead is that the rest of the conversation depends on the
11
+ answer. If the company is default alive, we can talk about ambitious
12
+ new things they could do. If it's default dead, we probably need
13
+ to talk about how to save it. We know the current trajectory ends
14
+ badly. How can they get off that trajectory?Why do so few founders know whether they're default alive or default
15
+ dead? Mainly, I think, because they're not used to asking that.
16
+ It's not a question that makes sense to ask early on, any more than
17
+ it makes sense to ask a 3 year old how he plans to support
18
+ himself. But as the company grows older, the question switches from
19
+ meaningless to critical. That kind of switch often takes people
20
+ by surprise.I propose the following solution: instead of starting to ask too
21
+ late whether you're default alive or default dead, start asking too
22
+ early. It's hard to say precisely when the question switches
23
+ polarity. But it's probably not that dangerous to start worrying
24
+ too early that you're default dead, whereas it's very dangerous to
25
+ start worrying too late.The reason is a phenomenon I wrote about earlier: the
26
+ fatal pinch.
27
+ The fatal pinch is default dead + slow growth + not enough
28
+ time to fix it. And the way founders end up in it is by not realizing
29
+ that's where they're headed.There is another reason founders don't ask themselves whether they're
30
+ default alive or default dead: they assume it will be easy to raise
31
+ more money. But that assumption is often false, and worse still, the
32
+ more you depend on it, the falser it becomes.Maybe it will help to separate facts from hopes. Instead of thinking
33
+ of the future with vague optimism, explicitly separate the components.
34
+ Say "We're default dead, but we're counting on investors to save
35
+ us." Maybe as you say that, it will set off the same alarms in your
36
+ head that it does in mine. And if you set off the alarms sufficiently
37
+ early, you may be able to avoid the fatal pinch.It would be safe to be default dead if you could count on investors
38
+ saving you. As a rule their interest is a function of
39
+ growth. If you have steep revenue growth, say over 5x a year, you
40
+ can start to count on investors being interested even if you're not
41
+ profitable.
42
+ [1]
43
+ But investors are so fickle that you can never
44
+ do more than start to count on them. Sometimes something about your
45
+ business will spook investors even if your growth is great. So no
46
+ matter how good your growth is, you can never safely treat fundraising
47
+ as more than a plan A. You should always have a plan B as well: you
48
+ should know (as in write down) precisely what you'll need to do to
49
+ survive if you can't raise more money, and precisely when you'll
50
+ have to switch to plan B if plan A isn't working.In any case, growing fast versus operating cheaply is far from the
51
+ sharp dichotomy many founders assume it to be. In practice there
52
+ is surprisingly little connection between how much a startup spends
53
+ and how fast it grows. When a startup grows fast, it's usually
54
+ because the product hits a nerve, in the sense of hitting some big
55
+ need straight on. When a startup spends a lot, it's usually because
56
+ the product is expensive to develop or sell, or simply because
57
+ they're wasteful.If you're paying attention, you'll be asking at this point not just
58
+ how to avoid the fatal pinch, but how to avoid being default dead.
59
+ That one is easy: don't hire too fast. Hiring too fast is by far
60
+ the biggest killer of startups that raise money.
61
+ [2]Founders tell themselves they need to hire in order to grow. But
62
+ most err on the side of overestimating this need rather than
63
+ underestimating it. Why? Partly because there's so much work to
64
+ do. Naive founders think that if they can just hire enough
65
+ people, it will all get done. Partly because successful startups have
66
+ lots of employees, so it seems like that's what one does in order
67
+ to be successful. In fact the large staffs of successful startups
68
+ are probably more the effect of growth than the cause. And
69
+ partly because when founders have slow growth they don't want to
70
+ face what is usually the real reason: the product is not appealing
71
+ enough.Plus founders who've just raised money are often encouraged to
72
+ overhire by the VCs who funded them. Kill-or-cure strategies are
73
+ optimal for VCs because they're protected by the portfolio effect.
74
+ VCs want to blow you up, in one sense of the phrase or the other.
75
+ But as a founder your incentives are different. You want above all
76
+ to survive.
77
+ [3]Here's a common way startups die. They make something moderately
78
+ appealing and have decent initial growth. They raise their first
79
+ round fairly easily, because the founders seem smart and the idea
80
+ sounds plausible. But because the product is only moderately
81
+ appealing, growth is ok but not great. The founders convince
82
+ themselves that hiring a bunch of people is the way to boost growth.
83
+ Their investors agree. But (because the product is only moderately
84
+ appealing) the growth never comes. Now they're rapidly running out
85
+ of runway. They hope further investment will save them. But because
86
+ they have high expenses and slow growth, they're now unappealing
87
+ to investors. They're unable to raise more, and the company dies.What the company should have done is address the fundamental problem:
88
+ that the product is only moderately appealing. Hiring people is
89
+ rarely the way to fix that. More often than not it makes it harder.
90
+ At this early stage, the product needs to evolve more than to be
91
+ "built out," and that's usually easier with fewer people.
92
+ [4]Asking whether you're default alive or default dead may save you
93
+ from this. Maybe the alarm bells it sets off will counteract the
94
+ forces that push you to overhire. Instead you'll be compelled to
95
+ seek growth in other ways. For example, by doing
96
+ things that don't scale, or by redesigning the product in the
97
+ way only founders can.
98
+ And for many if not most startups, these paths to growth will be
99
+ the ones that actually work.Airbnb waited 4 months after raising money at the end of Y Combinator
100
+ before they hired their first employee. In the meantime the founders
101
+ were terribly overworked. But they were overworked evolving Airbnb
102
+ into the astonishingly successful organism it is now.Notes[1]
103
+ Steep usage growth will also interest investors. Revenue
104
+ will ultimately be a constant multiple of usage, so x% usage growth
105
+ predicts x% revenue growth. But in practice investors discount
106
+ merely predicted revenue, so if you're measuring usage you need a
107
+ higher growth rate to impress investors.[2]
108
+ Startups that don't raise money are saved from hiring too
109
+ fast because they can't afford to. But that doesn't mean you should
110
+ avoid raising money in order to avoid this problem, any more than
111
+ that total abstinence is the only way to avoid becoming an alcoholic.[3]
112
+ I would not be surprised if VCs' tendency to push founders
113
+ to overhire is not even in their own interest. They don't know how
114
+ many of the companies that get killed by overspending might have
115
+ done well if they'd survived. My guess is a significant number.[4]
116
+ After reading a draft, Sam Altman wrote:"I think you should make the hiring point more strongly. I think
117
+ it's roughly correct to say that YC's most successful companies
118
+ have never been the fastest to hire, and one of the marks of a great
119
+ founder is being able to resist this urge."Paul Buchheit adds:"A related problem that I see a lot is premature scaling—founders
120
+ take a small business that isn't really working (bad unit economics,
121
+ typically) and then scale it up because they want impressive growth
122
+ numbers. This is similar to over-hiring in that it makes the business
123
+ much harder to fix once it's big, plus they are bleeding cash really
124
+ fast."
125
+ Thanks to Sam Altman, Paul Buchheit, Joe Gebbia, Jessica Livingston,
126
+ and Geoff Ralston for reading drafts of this.
PaulGrahamEssays/apple.txt ADDED
@@ -0,0 +1,201 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ November 2009I don't think Apple realizes how badly the App Store approval process
10
+ is broken. Or rather, I don't think they realize how much it matters
11
+ that it's broken.The way Apple runs the App Store has harmed their reputation with
12
+ programmers more than anything else they've ever done.
13
+ Their reputation with programmers used to be great.
14
+ It used to be the most common complaint you heard
15
+ about Apple was that their fans admired them too uncritically.
16
+ The App Store has changed that. Now a lot of programmers
17
+ have started to see Apple as evil.How much of the goodwill Apple once had with programmers have they
18
+ lost over the App Store? A third? Half? And that's just so far.
19
+ The App Store is an ongoing karma leak.* * *How did Apple get into this mess? Their fundamental problem is
20
+ that they don't understand software.They treat iPhone apps the way they treat the music they sell through
21
+ iTunes. Apple is the channel; they own the user; if you want to
22
+ reach users, you do it on their terms. The record labels agreed,
23
+ reluctantly. But this model doesn't work for software. It doesn't
24
+ work for an intermediary to own the user. The software business
25
+ learned that in the early 1980s, when companies like VisiCorp showed
26
+ that although the words "software" and "publisher" fit together,
27
+ the underlying concepts don't. Software isn't like music or books.
28
+ It's too complicated for a third party to act as an intermediary
29
+ between developer and user. And yet that's what Apple is trying
30
+ to be with the App Store: a software publisher. And a particularly
31
+ overreaching one at that, with fussy tastes and a rigidly enforced
32
+ house style.If software publishing didn't work in 1980, it works even less now
33
+ that software development has evolved from a small number of big
34
+ releases to a constant stream of small ones. But Apple doesn't
35
+ understand that either. Their model of product development derives
36
+ from hardware. They work on something till they think it's finished,
37
+ then they release it. You have to do that with hardware, but because
38
+ software is so easy to change, its design can benefit from evolution.
39
+ The standard way to develop applications now is to launch fast and
40
+ iterate. Which means it's a disaster to have long, random delays
41
+ each time you release a new version.Apparently Apple's attitude is that developers should be more careful
42
+ when they submit a new version to the App Store. They would say
43
+ that. But powerful as they are, they're not powerful enough to
44
+ turn back the evolution of technology. Programmers don't use
45
+ launch-fast-and-iterate out of laziness. They use it because it
46
+ yields the best results. By obstructing that process, Apple is
47
+ making them do bad work, and programmers hate that as much as Apple
48
+ would.How would Apple like it if when they discovered a serious bug in
49
+ OS X, instead of releasing a software update immediately, they had
50
+ to submit their code to an intermediary who sat on it for a month
51
+ and then rejected it because it contained an icon they didn't like?By breaking software development, Apple gets the opposite of what
52
+ they intended: the version of an app currently available in the App
53
+ Store tends to be an old and buggy one. One developer told me:
54
+
55
+ As a result of their process, the App Store is full of half-baked
56
+ applications. I make a new version almost every day that I release
57
+ to beta users. The version on the App Store feels old and crappy.
58
+ I'm sure that a lot of developers feel this way: One emotion is
59
+ "I'm not really proud about what's in the App Store", and it's
60
+ combined with the emotion "Really, it's Apple's fault."
61
+
62
+ Another wrote:
63
+
64
+ I believe that they think their approval process helps users by
65
+ ensuring quality. In reality, bugs like ours get through all the
66
+ time and then it can take 4-8 weeks to get that bug fix approved,
67
+ leaving users to think that iPhone apps sometimes just don't work.
68
+ Worse for Apple, these apps work just fine on other platforms
69
+ that have immediate approval processes.
70
+
71
+ Actually I suppose Apple has a third misconception: that all the
72
+ complaints about App Store approvals are not a serious problem.
73
+ They must hear developers complaining. But partners and suppliers
74
+ are always complaining. It would be a bad sign if they weren't;
75
+ it would mean you were being too easy on them. Meanwhile the iPhone
76
+ is selling better than ever. So why do they need to fix anything?They get away with maltreating developers, in the short term, because
77
+ they make such great hardware. I just bought a new 27" iMac a
78
+ couple days ago. It's fabulous. The screen's too shiny, and the
79
+ disk is surprisingly loud, but it's so beautiful that you can't
80
+ make yourself care.So I bought it, but I bought it, for the first time, with misgivings.
81
+ I felt the way I'd feel buying something made in a country with a
82
+ bad human rights record. That was new. In the past when I bought
83
+ things from Apple it was an unalloyed pleasure. Oh boy! They make
84
+ such great stuff. This time it felt like a Faustian bargain. They
85
+ make such great stuff, but they're such assholes. Do I really want
86
+ to support this company?* * *Should Apple care what people like me think? What difference does
87
+ it make if they alienate a small minority of their users?There are a couple reasons they should care. One is that these
88
+ users are the people they want as employees. If your company seems
89
+ evil, the best programmers won't work for you. That hurt Microsoft
90
+ a lot starting in the 90s. Programmers started to feel sheepish
91
+ about working there. It seemed like selling out. When people from
92
+ Microsoft were talking to other programmers and they mentioned where
93
+ they worked, there were a lot of self-deprecating jokes about having
94
+ gone over to the dark side. But the real problem for Microsoft
95
+ wasn't the embarrassment of the people they hired. It was the
96
+ people they never got. And you know who got them? Google and
97
+ Apple. If Microsoft was the Empire, they were the Rebel Alliance.
98
+ And it's largely because they got more of the best people that
99
+ Google and Apple are doing so much better than Microsoft today.Why are programmers so fussy about their employers' morals? Partly
100
+ because they can afford to be. The best programmers can work
101
+ wherever they want. They don't have to work for a company they
102
+ have qualms about.But the other reason programmers are fussy, I think, is that evil
103
+ begets stupidity. An organization that wins by exercising power
104
+ starts to lose the ability to win by doing better work. And it's
105
+ not fun for a smart person to work in a place where the best ideas
106
+ aren't the ones that win. I think the reason Google embraced "Don't
107
+ be evil" so eagerly was not so much to impress the outside world
108
+ as to inoculate themselves against arrogance.
109
+ [1]That has worked for Google so far. They've become more
110
+ bureaucratic, but otherwise they seem to have held true to their
111
+ original principles. With Apple that seems less the case. When you
112
+ look at the famous
113
+ 1984 ad
114
+ now, it's easier to imagine Apple as the
115
+ dictator on the screen than the woman with the hammer.
116
+ [2]
117
+ In fact, if you read the dictator's speech it sounds uncannily like a
118
+ prophecy of the App Store.
119
+
120
+ We have triumphed over the unprincipled dissemination of facts.We have created, for the first time in all history, a garden of
121
+ pure ideology, where each worker may bloom secure from the pests
122
+ of contradictory and confusing truths.
123
+
124
+ The other reason Apple should care what programmers think of them
125
+ is that when you sell a platform, developers make or break you. If
126
+ anyone should know this, Apple should. VisiCalc made the Apple II.And programmers build applications for the platforms they use. Most
127
+ applications—most startups, probably—grow out of personal projects.
128
+ Apple itself did. Apple made microcomputers because that's what
129
+ Steve Wozniak wanted for himself. He couldn't have afforded a
130
+ minicomputer.
131
+ [3]
132
+ Microsoft likewise started out making interpreters
133
+ for little microcomputers because
134
+ Bill Gates and Paul Allen were interested in using them. It's a
135
+ rare startup that doesn't build something the founders use.The main reason there are so many iPhone apps is that so many programmers
136
+ have iPhones. They may know, because they read it in an article,
137
+ that Blackberry has such and such market share. But in practice
138
+ it's as if RIM didn't exist. If they're going to build something,
139
+ they want to be able to use it themselves, and that means building
140
+ an iPhone app.So programmers continue to develop iPhone apps, even though Apple
141
+ continues to maltreat them. They're like someone stuck in an abusive
142
+ relationship. They're so attracted to the iPhone that they can't
143
+ leave. But they're looking for a way out. One wrote:
144
+
145
+ While I did enjoy developing for the iPhone, the control they
146
+ place on the App Store does not give me the drive to develop
147
+ applications as I would like. In fact I don't intend to make any
148
+ more iPhone applications unless absolutely necessary.
149
+ [4]
150
+
151
+ Can anything break this cycle? No device I've seen so far could.
152
+ Palm and RIM haven't a hope. The only credible contender is Android.
153
+ But Android is an orphan; Google doesn't really care about it, not
154
+ the way Apple cares about the iPhone. Apple cares about the iPhone
155
+ the way Google cares about search.* * *Is the future of handheld devices one locked down by Apple? It's
156
+ a worrying prospect. It would be a bummer to have another grim
157
+ monoculture like we had in the 1990s. In 1995, writing software
158
+ for end users was effectively identical with writing Windows
159
+ applications. Our horror at that prospect was the single biggest
160
+ thing that drove us to start building web apps.At least we know now what it would take to break Apple's lock.
161
+ You'd have to get iPhones out of programmers' hands. If programmers
162
+ used some other device for mobile web access, they'd start to develop
163
+ apps for that instead.How could you make a device programmers liked better than the iPhone?
164
+ It's unlikely you could make something better designed. Apple
165
+ leaves no room there. So this alternative device probably couldn't
166
+ win on general appeal. It would have to win by virtue of some
167
+ appeal it had to programmers specifically.One way to appeal to programmers is with software. If you
168
+ could think of an application programmers had to have, but that
169
+ would be impossible in the circumscribed world of the iPhone,
170
+ you could presumably get them to switch.That would definitely happen if programmers started to use handhelds
171
+ as development machines—if handhelds displaced laptops the
172
+ way laptops displaced desktops. You need more control of a development
173
+ machine than Apple will let you have over an iPhone.Could anyone make a device that you'd carry around in your pocket
174
+ like a phone, and yet would also work as a development machine?
175
+ It's hard to imagine what it would look like. But I've learned
176
+ never to say never about technology. A phone-sized device that
177
+ would work as a development machine is no more miraculous by present
178
+ standards than the iPhone itself would have seemed by the standards
179
+ of 1995.My current development machine is a MacBook Air, which I use with
180
+ an external monitor and keyboard in my office, and by itself when
181
+ traveling. If there was a version half the size I'd prefer it.
182
+ That still wouldn't be small enough to carry around everywhere like
183
+ a phone, but we're within a factor of 4 or so. Surely that gap is
184
+ bridgeable. In fact, let's make it an
185
+ RFS. Wanted:
186
+ Woman with hammer.Notes[1]
187
+ When Google adopted "Don't be evil," they were still so small
188
+ that no one would have expected them to be, yet.
189
+ [2]
190
+ The dictator in the 1984 ad isn't Microsoft, incidentally;
191
+ it's IBM. IBM seemed a lot more frightening in those days, but
192
+ they were friendlier to developers than Apple is now.[3]
193
+ He couldn't even afford a monitor. That's why the Apple
194
+ I used a TV as a monitor.[4]
195
+ Several people I talked to mentioned how much they liked the
196
+ iPhone SDK. The problem is not Apple's products but their policies.
197
+ Fortunately policies are software; Apple can change them instantly
198
+ if they want to. Handy that, isn't it?Thanks to Sam Altman, Trevor Blackwell, Ross Boucher,
199
+ James Bracy, Gabor Cselle,
200
+ Patrick Collison, Jason Freedman, John Gruber, Joe Hewitt, Jessica Livingston,
201
+ Robert Morris, Teng Siong Ong, Nikhil Pandit, Savraj Singh, and Jared Tame for reading drafts of this.
PaulGrahamEssays/avg.txt ADDED
@@ -0,0 +1,375 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ April 2001, rev. April 2003(This article is derived from a talk given at the 2001 Franz
10
+ Developer Symposium.)
11
+ In the summer of 1995, my friend Robert Morris and I
12
+ started a startup called
13
+ Viaweb.
14
+ Our plan was to write
15
+ software that would let end users build online stores.
16
+ What was novel about this software, at the time, was
17
+ that it ran on our server, using ordinary Web pages
18
+ as the interface.A lot of people could have been having this idea at the
19
+ same time, of course, but as far as I know, Viaweb was
20
+ the first Web-based application. It seemed such
21
+ a novel idea to us that we named the company after it:
22
+ Viaweb, because our software worked via the Web,
23
+ instead of running on your desktop computer.Another unusual thing about this software was that it
24
+ was written primarily in a programming language called
25
+ Lisp. It was one of the first big end-user
26
+ applications to be written in Lisp, which up till then
27
+ had been used mostly in universities and research labs. [1]The Secret WeaponEric Raymond has written an essay called "How to Become a Hacker,"
28
+ and in it, among other things, he tells would-be hackers what
29
+ languages they should learn. He suggests starting with Python and
30
+ Java, because they are easy to learn. The serious hacker will also
31
+ want to learn C, in order to hack Unix, and Perl for system
32
+ administration and cgi scripts. Finally, the truly serious hacker
33
+ should consider learning Lisp:
34
+
35
+ Lisp is worth learning for the profound enlightenment experience
36
+ you will have when you finally get it; that experience will make
37
+ you a better programmer for the rest of your days, even if you
38
+ never actually use Lisp itself a lot.
39
+
40
+ This is the same argument you tend to hear for learning Latin. It
41
+ won't get you a job, except perhaps as a classics professor, but
42
+ it will improve your mind, and make you a better writer in languages
43
+ you do want to use, like English.But wait a minute. This metaphor doesn't stretch that far. The
44
+ reason Latin won't get you a job is that no one speaks it. If you
45
+ write in Latin, no one can understand you. But Lisp is a computer
46
+ language, and computers speak whatever language you, the programmer,
47
+ tell them to.So if Lisp makes you a better programmer, like he says, why wouldn't
48
+ you want to use it? If a painter were offered a brush that would
49
+ make him a better painter, it seems to me that he would want to
50
+ use it in all his paintings, wouldn't he? I'm not trying to make
51
+ fun of Eric Raymond here. On the whole, his advice is good. What
52
+ he says about Lisp is pretty much the conventional wisdom. But
53
+ there is a contradiction in the conventional wisdom: Lisp will
54
+ make you a better programmer, and yet you won't use it.Why not? Programming languages are just tools, after all. If Lisp
55
+ really does yield better programs, you should use it. And if it
56
+ doesn't, then who needs it?This is not just a theoretical question. Software is a very
57
+ competitive business, prone to natural monopolies. A company that
58
+ gets software written faster and better will, all other things
59
+ being equal, put its competitors out of business. And when you're
60
+ starting a startup, you feel this very keenly. Startups tend to
61
+ be an all or nothing proposition. You either get rich, or you get
62
+ nothing. In a startup, if you bet on the wrong technology, your
63
+ competitors will crush you.Robert and I both knew Lisp well, and we couldn't see any reason
64
+ not to trust our instincts and go with Lisp. We knew that everyone
65
+ else was writing their software in C++ or Perl. But we also knew
66
+ that that didn't mean anything. If you chose technology that way,
67
+ you'd be running Windows. When you choose technology, you have to
68
+ ignore what other people are doing, and consider only what will
69
+ work the best.This is especially true in a startup. In a big company, you can
70
+ do what all the other big companies are doing. But a startup can't
71
+ do what all the other startups do. I don't think a lot of people
72
+ realize this, even in startups.The average big company grows at about ten percent a year. So if
73
+ you're running a big company and you do everything the way the
74
+ average big company does it, you can expect to do as well as the
75
+ average big company-- that is, to grow about ten percent a year.The same thing will happen if you're running a startup, of course.
76
+ If you do everything the way the average startup does it, you should
77
+ expect average performance. The problem here is, average performance
78
+ means that you'll go out of business. The survival rate for startups
79
+ is way less than fifty percent. So if you're running a startup,
80
+ you had better be doing something odd. If not, you're in trouble.Back in 1995, we knew something that I don't think our competitors
81
+ understood, and few understand even now: when you're writing
82
+ software that only has to run on your own servers, you can use
83
+ any language you want. When you're writing desktop software,
84
+ there's a strong bias toward writing applications in the same
85
+ language as the operating system. Ten years ago, writing applications
86
+ meant writing applications in C. But with Web-based software,
87
+ especially when you have the source code of both the language and
88
+ the operating system, you can use whatever language you want.This new freedom is a double-edged sword, however. Now that you
89
+ can use any language, you have to think about which one to use.
90
+ Companies that try to pretend nothing has changed risk finding that
91
+ their competitors do not.If you can use any language, which do you use? We chose Lisp.
92
+ For one thing, it was obvious that rapid development would be
93
+ important in this market. We were all starting from scratch, so
94
+ a company that could get new features done before its competitors
95
+ would have a big advantage. We knew Lisp was a really good language
96
+ for writing software quickly, and server-based applications magnify
97
+ the effect of rapid development, because you can release software
98
+ the minute it's done.If other companies didn't want to use Lisp, so much the better.
99
+ It might give us a technological edge, and we needed all the help
100
+ we could get. When we started Viaweb, we had no experience in
101
+ business. We didn't know anything about marketing, or hiring
102
+ people, or raising money, or getting customers. Neither of us had
103
+ ever even had what you would call a real job. The only thing we
104
+ were good at was writing software. We hoped that would save us.
105
+ Any advantage we could get in the software department, we would
106
+ take.So you could say that using Lisp was an experiment. Our hypothesis
107
+ was that if we wrote our software in Lisp, we'd be able to get
108
+ features done faster than our competitors, and also to do things
109
+ in our software that they couldn't do. And because Lisp was so
110
+ high-level, we wouldn't need a big development team, so our costs
111
+ would be lower. If this were so, we could offer a better product
112
+ for less money, and still make a profit. We would end up getting
113
+ all the users, and our competitors would get none, and eventually
114
+ go out of business. That was what we hoped would happen, anyway.What were the results of this experiment? Somewhat surprisingly,
115
+ it worked. We eventually had many competitors, on the order of
116
+ twenty to thirty of them, but none of their software could compete
117
+ with ours. We had a wysiwyg online store builder that ran on the
118
+ server and yet felt like a desktop application. Our competitors
119
+ had cgi scripts. And we were always far ahead of them in features.
120
+ Sometimes, in desperation, competitors would try to introduce
121
+ features that we didn't have. But with Lisp our development cycle
122
+ was so fast that we could sometimes duplicate a new feature within
123
+ a day or two of a competitor announcing it in a press release. By
124
+ the time journalists covering the press release got round to calling
125
+ us, we would have the new feature too.It must have seemed to our competitors that we had some kind of
126
+ secret weapon-- that we were decoding their Enigma traffic or
127
+ something. In fact we did have a secret weapon, but it was simpler
128
+ than they realized. No one was leaking news of their features to
129
+ us. We were just able to develop software faster than anyone
130
+ thought possible.When I was about nine I happened to get hold of a copy of The Day
131
+ of the Jackal, by Frederick Forsyth. The main character is an
132
+ assassin who is hired to kill the president of France. The assassin
133
+ has to get past the police to get up to an apartment that overlooks
134
+ the president's route. He walks right by them, dressed up as an
135
+ old man on crutches, and they never suspect him.Our secret weapon was similar. We wrote our software in a weird
136
+ AI language, with a bizarre syntax full of parentheses. For years
137
+ it had annoyed me to hear Lisp described that way. But now it
138
+ worked to our advantage. In business, there is nothing more valuable
139
+ than a technical advantage your competitors don't understand. In
140
+ business, as in war, surprise is worth as much as force.And so, I'm a little embarrassed to say, I never said anything
141
+ publicly about Lisp while we were working on Viaweb. We never
142
+ mentioned it to the press, and if you searched for Lisp on our Web
143
+ site, all you'd find were the titles of two books in my bio. This
144
+ was no accident. A startup should give its competitors as little
145
+ information as possible. If they didn't know what language our
146
+ software was written in, or didn't care, I wanted to keep it that
147
+ way.[2]The people who understood our technology best were the customers.
148
+ They didn't care what language Viaweb was written in either, but
149
+ they noticed that it worked really well. It let them build great
150
+ looking online stores literally in minutes. And so, by word of
151
+ mouth mostly, we got more and more users. By the end of 1996 we
152
+ had about 70 stores online. At the end of 1997 we had 500. Six
153
+ months later, when Yahoo bought us, we had 1070 users. Today, as
154
+ Yahoo Store, this software continues to dominate its market. It's
155
+ one of the more profitable pieces of Yahoo, and the stores built
156
+ with it are the foundation of Yahoo Shopping. I left Yahoo in
157
+ 1999, so I don't know exactly how many users they have now, but
158
+ the last I heard there were about 20,000.
159
+ The Blub ParadoxWhat's so great about Lisp? And if Lisp is so great, why doesn't
160
+ everyone use it? These sound like rhetorical questions, but actually
161
+ they have straightforward answers. Lisp is so great not because
162
+ of some magic quality visible only to devotees, but because it is
163
+ simply the most powerful language available. And the reason everyone
164
+ doesn't use it is that programming languages are not merely
165
+ technologies, but habits of mind as well, and nothing changes
166
+ slower. Of course, both these answers need explaining.I'll begin with a shockingly controversial statement: programming
167
+ languages vary in power.Few would dispute, at least, that high level languages are more
168
+ powerful than machine language. Most programmers today would agree
169
+ that you do not, ordinarily, want to program in machine language.
170
+ Instead, you should program in a high-level language, and have a
171
+ compiler translate it into machine language for you. This idea is
172
+ even built into the hardware now: since the 1980s, instruction sets
173
+ have been designed for compilers rather than human programmers.Everyone knows it's a mistake to write your whole program by hand
174
+ in machine language. What's less often understood is that there
175
+ is a more general principle here: that if you have a choice of
176
+ several languages, it is, all other things being equal, a mistake
177
+ to program in anything but the most powerful one. [3]There are many exceptions to this rule. If you're writing a program
178
+ that has to work very closely with a program written in a certain
179
+ language, it might be a good idea to write the new program in the
180
+ same language. If you're writing a program that only has to do
181
+ something very simple, like number crunching or bit manipulation,
182
+ you may as well use a less abstract language, especially since it
183
+ may be slightly faster. And if you're writing a short, throwaway
184
+ program, you may be better off just using whatever language has
185
+ the best library functions for the task. But in general, for
186
+ application software, you want to be using the most powerful
187
+ (reasonably efficient) language you can get, and using anything
188
+ else is a mistake, of exactly the same kind, though possibly in a
189
+ lesser degree, as programming in machine language.You can see that machine language is very low level. But, at least
190
+ as a kind of social convention, high-level languages are often all
191
+ treated as equivalent. They're not. Technically the term "high-level
192
+ language" doesn't mean anything very definite. There's no dividing
193
+ line with machine languages on one side and all the high-level
194
+ languages on the other. Languages fall along a continuum [4] of
195
+ abstractness, from the most powerful all the way down to machine
196
+ languages, which themselves vary in power.Consider Cobol. Cobol is a high-level language, in the sense that
197
+ it gets compiled into machine language. Would anyone seriously
198
+ argue that Cobol is equivalent in power to, say, Python? It's
199
+ probably closer to machine language than Python.Or how about Perl 4? Between Perl 4 and Perl 5, lexical closures
200
+ got added to the language. Most Perl hackers would agree that Perl
201
+ 5 is more powerful than Perl 4. But once you've admitted that,
202
+ you've admitted that one high level language can be more powerful
203
+ than another. And it follows inexorably that, except in special
204
+ cases, you ought to use the most powerful you can get.This idea is rarely followed to its conclusion, though. After a
205
+ certain age, programmers rarely switch languages voluntarily.
206
+ Whatever language people happen to be used to, they tend to consider
207
+ just good enough.Programmers get very attached to their favorite languages, and I
208
+ don't want to hurt anyone's feelings, so to explain this point I'm
209
+ going to use a hypothetical language called Blub. Blub falls right
210
+ in the middle of the abstractness continuum. It is not the most
211
+ powerful language, but it is more powerful than Cobol or machine
212
+ language.And in fact, our hypothetical Blub programmer wouldn't use either
213
+ of them. Of course he wouldn't program in machine language. That's
214
+ what compilers are for. And as for Cobol, he doesn't know how
215
+ anyone can get anything done with it. It doesn't even have x (Blub
216
+ feature of your choice).As long as our hypothetical Blub programmer is looking down the
217
+ power continuum, he knows he's looking down. Languages less powerful
218
+ than Blub are obviously less powerful, because they're missing some
219
+ feature he's used to. But when our hypothetical Blub programmer
220
+ looks in the other direction, up the power continuum, he doesn't
221
+ realize he's looking up. What he sees are merely weird languages.
222
+ He probably considers them about equivalent in power to Blub, but
223
+ with all this other hairy stuff thrown in as well. Blub is good
224
+ enough for him, because he thinks in Blub.When we switch to the point of view of a programmer using any of
225
+ the languages higher up the power continuum, however, we find that
226
+ he in turn looks down upon Blub. How can you get anything done in
227
+ Blub? It doesn't even have y.By induction, the only programmers in a position to see all the
228
+ differences in power between the various languages are those who
229
+ understand the most powerful one. (This is probably what Eric
230
+ Raymond meant about Lisp making you a better programmer.) You can't
231
+ trust the opinions of the others, because of the Blub paradox:
232
+ they're satisfied with whatever language they happen to use, because
233
+ it dictates the way they think about programs.I know this from my own experience, as a high school kid writing
234
+ programs in Basic. That language didn't even support recursion.
235
+ It's hard to imagine writing programs without using recursion, but
236
+ I didn't miss it at the time. I thought in Basic. And I was a
237
+ whiz at it. Master of all I surveyed.The five languages that Eric Raymond recommends to hackers fall at
238
+ various points on the power continuum. Where they fall relative
239
+ to one another is a sensitive topic. What I will say is that I
240
+ think Lisp is at the top. And to support this claim I'll tell you
241
+ about one of the things I find missing when I look at the other
242
+ four languages. How can you get anything done in them, I think,
243
+ without macros? [5]Many languages have something called a macro. But Lisp macros are
244
+ unique. And believe it or not, what they do is related to the
245
+ parentheses. The designers of Lisp didn't put all those parentheses
246
+ in the language just to be different. To the Blub programmer, Lisp
247
+ code looks weird. But those parentheses are there for a reason.
248
+ They are the outward evidence of a fundamental difference between
249
+ Lisp and other languages.Lisp code is made out of Lisp data objects. And not in the trivial
250
+ sense that the source files contain characters, and strings are
251
+ one of the data types supported by the language. Lisp code, after
252
+ it's read by the parser, is made of data structures that you can
253
+ traverse.If you understand how compilers work, what's really going on is
254
+ not so much that Lisp has a strange syntax as that Lisp has no
255
+ syntax. You write programs in the parse trees that get generated
256
+ within the compiler when other languages are parsed. But these
257
+ parse trees are fully accessible to your programs. You can write
258
+ programs that manipulate them. In Lisp, these programs are called
259
+ macros. They are programs that write programs.Programs that write programs? When would you ever want to do that?
260
+ Not very often, if you think in Cobol. All the time, if you think
261
+ in Lisp. It would be convenient here if I could give an example
262
+ of a powerful macro, and say there! how about that? But if I did,
263
+ it would just look like gibberish to someone who didn't know Lisp;
264
+ there isn't room here to explain everything you'd need to know to
265
+ understand what it meant. In
266
+ Ansi Common Lisp I tried to move
267
+ things along as fast as I could, and even so I didn't get to macros
268
+ until page 160.But I think I can give a kind of argument that might be convincing.
269
+ The source code of the Viaweb editor was probably about 20-25%
270
+ macros. Macros are harder to write than ordinary Lisp functions,
271
+ and it's considered to be bad style to use them when they're not
272
+ necessary. So every macro in that code is there because it has to
273
+ be. What that means is that at least 20-25% of the code in this
274
+ program is doing things that you can't easily do in any other
275
+ language. However skeptical the Blub programmer might be about my
276
+ claims for the mysterious powers of Lisp, this ought to make him
277
+ curious. We weren't writing this code for our own amusement. We
278
+ were a tiny startup, programming as hard as we could in order to
279
+ put technical barriers between us and our competitors.A suspicious person might begin to wonder if there was some
280
+ correlation here. A big chunk of our code was doing things that
281
+ are very hard to do in other languages. The resulting software
282
+ did things our competitors' software couldn't do. Maybe there was
283
+ some kind of connection. I encourage you to follow that thread.
284
+ There may be more to that old man hobbling along on his crutches
285
+ than meets the eye.Aikido for StartupsBut I don't expect to convince anyone
286
+ (over 25)
287
+ to go out and learn
288
+ Lisp. The purpose of this article is not to change anyone's mind,
289
+ but to reassure people already interested in using Lisp-- people
290
+ who know that Lisp is a powerful language, but worry because it
291
+ isn't widely used. In a competitive situation, that's an advantage.
292
+ Lisp's power is multiplied by the fact that your competitors don't
293
+ get it.If you think of using Lisp in a startup, you shouldn't worry that
294
+ it isn't widely understood. You should hope that it stays that
295
+ way. And it's likely to. It's the nature of programming languages
296
+ to make most people satisfied with whatever they currently use.
297
+ Computer hardware changes so much faster than personal habits that
298
+ programming practice is usually ten to twenty years behind the
299
+ processor. At places like MIT they were writing programs in
300
+ high-level languages in the early 1960s, but many companies continued
301
+ to write code in machine language well into the 1980s. I bet a
302
+ lot of people continued to write machine language until the processor,
303
+ like a bartender eager to close up and go home, finally kicked them
304
+ out by switching to a risc instruction set.Ordinarily technology changes fast. But programming languages are
305
+ different: programming languages are not just technology, but what
306
+ programmers think in. They're half technology and half religion.[6]
307
+ And so the median language, meaning whatever language the median
308
+ programmer uses, moves as slow as an iceberg. Garbage collection,
309
+ introduced by Lisp in about 1960, is now widely considered to be
310
+ a good thing. Runtime typing, ditto, is growing in popularity.
311
+ Lexical closures, introduced by Lisp in the early 1970s, are now,
312
+ just barely, on the radar screen. Macros, introduced by Lisp in the
313
+ mid 1960s, are still terra incognita.Obviously, the median language has enormous momentum. I'm not
314
+ proposing that you can fight this powerful force. What I'm proposing
315
+ is exactly the opposite: that, like a practitioner of Aikido, you
316
+ can use it against your opponents.If you work for a big company, this may not be easy. You will have
317
+ a hard time convincing the pointy-haired boss to let you build
318
+ things in Lisp, when he has just read in the paper that some other
319
+ language is poised, like Ada was twenty years ago, to take over
320
+ the world. But if you work for a startup that doesn't have
321
+ pointy-haired bosses yet, you can, like we did, turn the Blub
322
+ paradox to your advantage: you can use technology that your
323
+ competitors, glued immovably to the median language, will never be
324
+ able to match.If you ever do find yourself working for a startup, here's a handy
325
+ tip for evaluating competitors. Read their job listings. Everything
326
+ else on their site may be stock photos or the prose equivalent,
327
+ but the job listings have to be specific about what they want, or
328
+ they'll get the wrong candidates.During the years we worked on Viaweb I read a lot of job descriptions.
329
+ A new competitor seemed to emerge out of the woodwork every month
330
+ or so. The first thing I would do, after checking to see if they
331
+ had a live online demo, was look at their job listings. After a
332
+ couple years of this I could tell which companies to worry about
333
+ and which not to. The more of an IT flavor the job descriptions
334
+ had, the less dangerous the company was. The safest kind were the
335
+ ones that wanted Oracle experience. You never had to worry about
336
+ those. You were also safe if they said they wanted C++ or Java
337
+ developers. If they wanted Perl or Python programmers, that would
338
+ be a bit frightening-- that's starting to sound like a company
339
+ where the technical side, at least, is run by real hackers. If I
340
+ had ever seen a job posting looking for Lisp hackers, I would have
341
+ been really worried.
342
+ Notes[1] Viaweb at first had two parts: the editor, written in Lisp,
343
+ which people used to build their sites, and the ordering system,
344
+ written in C, which handled orders. The first version was mostly
345
+ Lisp, because the ordering system was small. Later we added two
346
+ more modules, an image generator written in C, and a back-office
347
+ manager written mostly in Perl.In January 2003, Yahoo released a new version of the editor
348
+ written in C++ and Perl. It's hard to say whether the program is no
349
+ longer written in Lisp, though, because to translate this program
350
+ into C++ they literally had to write a Lisp interpreter: the source
351
+ files of all the page-generating templates are still, as far as I
352
+ know, Lisp code. (See Greenspun's Tenth Rule.)[2] Robert Morris says that I didn't need to be secretive, because
353
+ even if our competitors had known we were using Lisp, they wouldn't
354
+ have understood why: "If they were that smart they'd already be
355
+ programming in Lisp."[3] All languages are equally powerful in the sense of being Turing
356
+ equivalent, but that's not the sense of the word programmers care
357
+ about. (No one wants to program a Turing machine.) The kind of
358
+ power programmers care about may not be formally definable, but
359
+ one way to explain it would be to say that it refers to features
360
+ you could only get in the less powerful language by writing an
361
+ interpreter for the more powerful language in it. If language A
362
+ has an operator for removing spaces from strings and language B
363
+ doesn't, that probably doesn't make A more powerful, because you
364
+ can probably write a subroutine to do it in B. But if A supports,
365
+ say, recursion, and B doesn't, that's not likely to be something
366
+ you can fix by writing library functions.[4] Note to nerds: or possibly a lattice, narrowing toward the top;
367
+ it's not the shape that matters here but the idea that there is at
368
+ least a partial order.[5] It is a bit misleading to treat macros as a separate feature.
369
+ In practice their usefulness is greatly enhanced by other Lisp
370
+ features like lexical closures and rest parameters.[6] As a result, comparisons of programming languages either take
371
+ the form of religious wars or undergraduate textbooks so determinedly
372
+ neutral that they're really works of anthropology. People who
373
+ value their peace, or want tenure, avoid the topic. But the question
374
+ is only half a religious one; there is something there worth
375
+ studying, especially if you want to design new languages.
PaulGrahamEssays/before.txt ADDED
@@ -0,0 +1,387 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ October 2014(This essay is derived from a guest lecture in Sam Altman's startup class at
10
+ Stanford. It's intended for college students, but much of it is
11
+ applicable to potential founders at other ages.)One of the advantages of having kids is that when you have to give
12
+ advice, you can ask yourself "what would I tell my own kids?" My
13
+ kids are little, but I can imagine what I'd tell them about startups
14
+ if they were in college, and that's what I'm going to tell you.Startups are very counterintuitive. I'm not sure why. Maybe it's
15
+ just because knowledge about them hasn't permeated our culture yet.
16
+ But whatever the reason, starting a startup is a task where you
17
+ can't always trust your instincts.It's like skiing in that way. When you first try skiing and you
18
+ want to slow down, your instinct is to lean back. But if you lean
19
+ back on skis you fly down the hill out of control. So part of
20
+ learning to ski is learning to suppress that impulse. Eventually
21
+ you get new habits, but at first it takes a conscious effort. At
22
+ first there's a list of things you're trying to remember as you
23
+ start down the hill.Startups are as unnatural as skiing, so there's a similar list for
24
+ startups. Here I'm going to give you the first part of it — the things
25
+ to remember if you want to prepare yourself to start a startup.
26
+ CounterintuitiveThe first item on it is the fact I already mentioned: that startups
27
+ are so weird that if you trust your instincts, you'll make a lot
28
+ of mistakes. If you know nothing more than this, you may at least
29
+ pause before making them.When I was running Y Combinator I used to joke that our function
30
+ was to tell founders things they would ignore. It's really true.
31
+ Batch after batch, the YC partners warn founders about mistakes
32
+ they're about to make, and the founders ignore them, and then come
33
+ back a year later and say "I wish we'd listened."Why do the founders ignore the partners' advice? Well, that's the
34
+ thing about counterintuitive ideas: they contradict your intuitions.
35
+ They seem wrong. So of course your first impulse is to disregard
36
+ them. And in fact my joking description is not merely the curse
37
+ of Y Combinator but part of its raison d'etre. If founders' instincts
38
+ already gave them the right answers, they wouldn't need us. You
39
+ only need other people to give you advice that surprises you. That's
40
+ why there are a lot of ski instructors and not many running
41
+ instructors.
42
+ [1]You can, however, trust your instincts about people. And in fact
43
+ one of the most common mistakes young founders make is not to
44
+ do that enough. They get involved with people who seem impressive,
45
+ but about whom they feel some misgivings personally. Later when
46
+ things blow up they say "I knew there was something off about him,
47
+ but I ignored it because he seemed so impressive."If you're thinking about getting involved with someone — as a
48
+ cofounder, an employee, an investor, or an acquirer — and you
49
+ have misgivings about them, trust your gut. If someone seems
50
+ slippery, or bogus, or a jerk, don't ignore it.This is one case where it pays to be self-indulgent. Work with
51
+ people you genuinely like, and you've known long enough to be sure.
52
+ ExpertiseThe second counterintuitive point is that it's not that important
53
+ to know a lot about startups. The way to succeed in a startup is
54
+ not to be an expert on startups, but to be an expert on your users
55
+ and the problem you're solving for them.
56
+ Mark Zuckerberg didn't succeed because he was an expert on startups.
57
+ He succeeded despite being a complete noob at startups, because he
58
+ understood his users really well.If you don't know anything about, say, how to raise an angel round,
59
+ don't feel bad on that account. That sort of thing you can learn
60
+ when you need to, and forget after you've done it.In fact, I worry it's not merely unnecessary to learn in great
61
+ detail about the mechanics of startups, but possibly somewhat
62
+ dangerous. If I met an undergrad who knew all about convertible
63
+ notes and employee agreements and (God forbid) class FF stock, I
64
+ wouldn't think "here is someone who is way ahead of their peers."
65
+ It would set off alarms. Because another of the characteristic
66
+ mistakes of young founders is to go through the motions of starting
67
+ a startup. They make up some plausible-sounding idea, raise money
68
+ at a good valuation, rent a cool office, hire a bunch of people.
69
+ From the outside that seems like what startups do. But the next
70
+ step after rent a cool office and hire a bunch of people is: gradually
71
+ realize how completely fucked they are, because while imitating all
72
+ the outward forms of a startup they have neglected the one thing
73
+ that's actually essential: making something people want.
74
+ GameWe saw this happen so often that we made up a name for it: playing
75
+ house. Eventually I realized why it was happening. The reason
76
+ young founders go through the motions of starting a startup is
77
+ because that's what they've been trained to do for their whole lives
78
+ up to that point. Think about what you have to do to get into
79
+ college, for example. Extracurricular activities, check. Even in
80
+ college classes most of the work is as artificial as running laps.I'm not attacking the educational system for being this way. There
81
+ will always be a certain amount of fakeness in the work you do when
82
+ you're being taught something, and if you measure their performance
83
+ it's inevitable that people will exploit the difference to the point
84
+ where much of what you're measuring is artifacts of the fakeness.I confess I did it myself in college. I found that in a lot of
85
+ classes there might only be 20 or 30 ideas that were the right shape
86
+ to make good exam questions. The way I studied for exams in these
87
+ classes was not (except incidentally) to master the material taught
88
+ in the class, but to make a list of potential exam questions and
89
+ work out the answers in advance. When I walked into the final, the
90
+ main thing I'd be feeling was curiosity about which of my questions
91
+ would turn up on the exam. It was like a game.It's not surprising that after being trained for their whole lives
92
+ to play such games, young founders' first impulse on starting a
93
+ startup is to try to figure out the tricks for winning at this new
94
+ game. Since fundraising appears to be the measure of success for
95
+ startups (another classic noob mistake), they always want to know what the
96
+ tricks are for convincing investors. We tell them the best way to
97
+ convince investors is to make a startup
98
+ that's actually doing well, meaning growing fast, and then simply
99
+ tell investors so. Then they want to know what the tricks are for
100
+ growing fast. And we have to tell them the best way to do that is
101
+ simply to make something people want.So many of the conversations YC partners have with young founders
102
+ begin with the founder asking "How do we..." and the partner replying
103
+ "Just..."Why do the founders always make things so complicated? The reason,
104
+ I realized, is that they're looking for the trick.So this is the third counterintuitive thing to remember about
105
+ startups: starting a startup is where gaming the system stops
106
+ working. Gaming the system may continue to work if you go to work
107
+ for a big company. Depending on how broken the company is, you can
108
+ succeed by sucking up to the right people, giving the impression
109
+ of productivity, and so on.
110
+ [2]
111
+ But that doesn't work with startups.
112
+ There is no boss to trick, only users, and all users care about is
113
+ whether your product does what they want. Startups are as impersonal
114
+ as physics. You have to make something people want, and you prosper
115
+ only to the extent you do.The dangerous thing is, faking does work to some degree on investors.
116
+ If you're super good at sounding like you know what you're talking
117
+ about, you can fool investors for at least one and perhaps even two
118
+ rounds of funding. But it's not in your interest to. The company
119
+ is ultimately doomed. All you're doing is wasting your own time
120
+ riding it down.So stop looking for the trick. There are tricks in startups, as
121
+ there are in any domain, but they are an order of magnitude less
122
+ important than solving the real problem. A founder who knows nothing
123
+ about fundraising but has made something users love will have an
124
+ easier time raising money than one who knows every trick in the
125
+ book but has a flat usage graph. And more importantly, the founder
126
+ who has made something users love is the one who will go on to
127
+ succeed after raising the money.Though in a sense it's bad news in that you're deprived of one of
128
+ your most powerful weapons, I think it's exciting that gaming the
129
+ system stops working when you start a startup. It's exciting that
130
+ there even exist parts of the world where you win by doing good
131
+ work. Imagine how depressing the world would be if it were all
132
+ like school and big companies, where you either have to spend a lot
133
+ of time on bullshit things or lose to people who do.
134
+ [3]
135
+ I would
136
+ have been delighted if I'd realized in college that there were parts
137
+ of the real world where gaming the system mattered less than others,
138
+ and a few where it hardly mattered at all. But there are, and this
139
+ variation is one of the most important things to consider when
140
+ you're thinking about your future. How do you win in each type of
141
+ work, and what would you like to win by doing?
142
+ [4]
143
+ All-ConsumingThat brings us to our fourth counterintuitive point: startups are
144
+ all-consuming. If you start a startup, it will take over your life
145
+ to a degree you cannot imagine. And if your startup succeeds, it
146
+ will take over your life for a long time: for several years at the
147
+ very least, maybe for a decade, maybe for the rest of your working
148
+ life. So there is a real opportunity cost here.Larry Page may seem to have an enviable life, but there are aspects
149
+ of it that are unenviable. Basically at 25 he started running as
150
+ fast as he could and it must seem to him that he hasn't stopped to
151
+ catch his breath since. Every day new shit happens in the Google
152
+ empire that only the CEO can deal with, and he, as CEO, has to deal
153
+ with it. If he goes on vacation for even a week, a whole week's
154
+ backlog of shit accumulates. And he has to bear this uncomplainingly,
155
+ partly because as the company's daddy he can never show fear or
156
+ weakness, and partly because billionaires get less than zero sympathy
157
+ if they talk about having difficult lives. Which has the strange
158
+ side effect that the difficulty of being a successful startup founder
159
+ is concealed from almost everyone except those who've done it.Y Combinator has now funded several companies that can be called
160
+ big successes, and in every single case the founders say the same
161
+ thing. It never gets any easier. The nature of the problems change.
162
+ You're worrying about construction delays at your London office
163
+ instead of the broken air conditioner in your studio apartment.
164
+ But the total volume of worry never decreases; if anything it
165
+ increases.Starting a successful startup is similar to having kids in that
166
+ it's like a button you push that changes your life irrevocably.
167
+ And while it's truly wonderful having kids, there are a lot of
168
+ things that are easier to do before you have them than after. Many
169
+ of which will make you a better parent when you do have kids. And
170
+ since you can delay pushing the button for a while, most people in
171
+ rich countries do.Yet when it comes to startups, a lot of people seem to think they're
172
+ supposed to start them while they're still in college. Are you
173
+ crazy? And what are the universities thinking? They go out of
174
+ their way to ensure their students are well supplied with contraceptives,
175
+ and yet they're setting up entrepreneurship programs and startup
176
+ incubators left and right.To be fair, the universities have their hand forced here. A lot
177
+ of incoming students are interested in startups. Universities are,
178
+ at least de facto, expected to prepare them for their careers. So
179
+ students who want to start startups hope universities can teach
180
+ them about startups. And whether universities can do this or not,
181
+ there's some pressure to claim they can, lest they lose applicants
182
+ to other universities that do.Can universities teach students about startups? Yes and no. They
183
+ can teach students about startups, but as I explained before, this
184
+ is not what you need to know. What you need to learn about are the
185
+ needs of your own users, and you can't do that until you actually
186
+ start the company.
187
+ [5]
188
+ So starting a startup is intrinsically
189
+ something you can only really learn by doing it. And it's impossible
190
+ to do that in college, for the reason I just explained: startups
191
+ take over your life. You can't start a startup for real as a
192
+ student, because if you start a startup for real you're not a student
193
+ anymore. You may be nominally a student for a bit, but you won't even
194
+ be that for long.
195
+ [6]Given this dichotomy, which of the two paths should you take? Be
196
+ a real student and not start a startup, or start a real startup and
197
+ not be a student? I can answer that one for you. Do not start a
198
+ startup in college. How to start a startup is just a subset of a
199
+ bigger problem you're trying to solve: how to have a good life.
200
+ And though starting a startup can be part of a good life for a lot
201
+ of ambitious people, age 20 is not the optimal time to do it.
202
+ Starting a startup is like a brutally fast depth-first search. Most
203
+ people should still be searching breadth-first at 20.You can do things in your early 20s that you can't do as well before
204
+ or after, like plunge deeply into projects on a whim and travel
205
+ super cheaply with no sense of a deadline. For unambitious people,
206
+ this sort of thing is the dreaded "failure to launch," but for the
207
+ ambitious ones it can be an incomparably valuable sort of exploration.
208
+ If you start a startup at 20 and you're sufficiently successful,
209
+ you'll never get to do it.
210
+ [7]Mark Zuckerberg will never get to bum around a foreign country. He
211
+ can do other things most people can't, like charter jets to fly him
212
+ to foreign countries. But success has taken a lot of the serendipity
213
+ out of his life. Facebook is running him as much as he's running
214
+ Facebook. And while it can be very cool to be in the grip of a
215
+ project you consider your life's work, there are advantages to
216
+ serendipity too, especially early in life. Among other things it
217
+ gives you more options to choose your life's work from.There's not even a tradeoff here. You're not sacrificing anything
218
+ if you forgo starting a startup at 20, because you're more likely
219
+ to succeed if you wait. In the unlikely case that you're 20 and
220
+ one of your side projects takes off like Facebook did, you'll face
221
+ a choice of running with it or not, and it may be reasonable to run
222
+ with it. But the usual way startups take off is for the founders
223
+ to make them take off, and it's gratuitously
224
+ stupid to do that at 20.
225
+ TryShould you do it at any age? I realize I've made startups sound
226
+ pretty hard. If I haven't, let me try again: starting a startup
227
+ is really hard. What if it's too hard? How can you tell if you're
228
+ up to this challenge?The answer is the fifth counterintuitive point: you can't tell. Your
229
+ life so far may have given you some idea what your prospects might
230
+ be if you tried to become a mathematician, or a professional football
231
+ player. But unless you've had a very strange life you haven't done
232
+ much that was like being a startup founder.
233
+ Starting a startup will change you a lot. So what you're trying
234
+ to estimate is not just what you are, but what you could grow into,
235
+ and who can do that?For the past 9 years it was my job to predict whether people would
236
+ have what it took to start successful startups. It was easy to
237
+ tell how smart they were, and most people reading this will be over
238
+ that threshold. The hard part was predicting how tough and ambitious they would become. There
239
+ may be no one who has more experience at trying to predict that,
240
+ so I can tell you how much an expert can know about it, and the
241
+ answer is: not much. I learned to keep a completely open mind about
242
+ which of the startups in each batch would turn out to be the stars.The founders sometimes think they know. Some arrive feeling sure
243
+ they will ace Y Combinator just as they've aced every one of the (few,
244
+ artificial, easy) tests they've faced in life so far. Others arrive
245
+ wondering how they got in, and hoping YC doesn't discover whatever
246
+ mistake caused it to accept them. But there is little correlation
247
+ between founders' initial attitudes and how well their companies
248
+ do.I've read that the same is true in the military — that the
249
+ swaggering recruits are no more likely to turn out to be really
250
+ tough than the quiet ones. And probably for the same reason: that
251
+ the tests involved are so different from the ones in their previous
252
+ lives.If you're absolutely terrified of starting a startup, you probably
253
+ shouldn't do it. But if you're merely unsure whether you're up to
254
+ it, the only way to find out is to try. Just not now.
255
+ IdeasSo if you want to start a startup one day, what should you do in
256
+ college? There are only two things you need initially: an idea and
257
+ cofounders. And the m.o. for getting both is the same. Which leads
258
+ to our sixth and last counterintuitive point: that the way to get
259
+ startup ideas is not to try to think of startup ideas.I've written a whole essay on this,
260
+ so I won't repeat it all here. But the short version is that if
261
+ you make a conscious effort to think of startup ideas, the ideas
262
+ you come up with will not merely be bad, but bad and plausible-sounding,
263
+ meaning you'll waste a lot of time on them before realizing they're
264
+ bad.The way to come up with good startup ideas is to take a step back.
265
+ Instead of making a conscious effort to think of startup ideas,
266
+ turn your mind into the type that startup ideas form in without any
267
+ conscious effort. In fact, so unconsciously that you don't even
268
+ realize at first that they're startup ideas.This is not only possible, it's how Apple, Yahoo, Google, and
269
+ Facebook all got started. None of these companies were even meant
270
+ to be companies at first. They were all just side projects. The
271
+ best startups almost have to start as side projects, because great
272
+ ideas tend to be such outliers that your conscious mind would reject
273
+ them as ideas for companies.Ok, so how do you turn your mind into the type that startup ideas
274
+ form in unconsciously? (1) Learn a lot about things that matter,
275
+ then (2) work on problems that interest you (3) with people you
276
+ like and respect. The third part, incidentally, is how you get
277
+ cofounders at the same time as the idea.The first time I wrote that paragraph, instead of "learn a lot about
278
+ things that matter," I wrote "become good at some technology." But
279
+ that prescription, though sufficient, is too narrow. What was
280
+ special about Brian Chesky and Joe Gebbia was not that they were
281
+ experts in technology. They were good at design, and perhaps even
282
+ more importantly, they were good at organizing groups and making
283
+ projects happen. So you don't have to work on technology per se,
284
+ so long as you work on problems demanding enough to stretch you.What kind of problems are those? That is very hard to answer in
285
+ the general case. History is full of examples of young people who
286
+ were working on important problems that no
287
+ one else at the time thought were important, and in particular
288
+ that their parents didn't think were important. On the other hand,
289
+ history is even fuller of examples of parents who thought their
290
+ kids were wasting their time and who were right. So how do you
291
+ know when you're working on real stuff?
292
+ [8]I know how I know. Real problems are interesting, and I am
293
+ self-indulgent in the sense that I always want to work on interesting
294
+ things, even if no one else cares about them (in fact, especially
295
+ if no one else cares about them), and find it very hard to make
296
+ myself work on boring things, even if they're supposed to be
297
+ important.My life is full of case after case where I worked on something just
298
+ because it seemed interesting, and it turned out later to be useful
299
+ in some worldly way. Y
300
+ Combinator itself was something I only did because it seemed
301
+ interesting. So I seem to have some sort of internal compass that
302
+ helps me out. But I don't know what other people have in their
303
+ heads. Maybe if I think more about this I can come up with heuristics
304
+ for recognizing genuinely interesting problems, but for the moment
305
+ the best I can offer is the hopelessly question-begging advice that
306
+ if you have a taste for genuinely interesting problems, indulging
307
+ it energetically is the best way to prepare yourself for a startup.
308
+ And indeed, probably also the best way to live.
309
+ [9]But although I can't explain in the general case what counts as an
310
+ interesting problem, I can tell you about a large subset of them.
311
+ If you think of technology as something that's spreading like a
312
+ sort of fractal stain, every moving point on the edge represents
313
+ an interesting problem. So one guaranteed way to turn your mind
314
+ into the type that has good startup ideas is to get yourself to the
315
+ leading edge of some technology — to cause yourself, as Paul
316
+ Buchheit put it, to "live in the future." When you reach that point,
317
+ ideas that will seem to other people uncannily prescient will seem
318
+ obvious to you. You may not realize they're startup ideas, but
319
+ you'll know they're something that ought to exist.For example, back at Harvard in the mid 90s a fellow grad student
320
+ of my friends Robert and Trevor wrote his own voice over IP software.
321
+ He didn't mean it to be a startup, and he never tried to turn it
322
+ into one. He just wanted to talk to his girlfriend in Taiwan without
323
+ paying for long distance calls, and since he was an expert on
324
+ networks it seemed obvious to him that the way to do it was turn
325
+ the sound into packets and ship it over the Internet. He never did
326
+ any more with his software than talk to his girlfriend, but this
327
+ is exactly the way the best startups get started.So strangely enough the optimal thing to do in college if you want
328
+ to be a successful startup founder is not some sort of new, vocational
329
+ version of college focused on "entrepreneurship." It's the classic
330
+ version of college as education for its own sake. If you want to
331
+ start a startup after college, what you should do in college is
332
+ learn powerful things. And if you have genuine intellectual
333
+ curiosity, that's what you'll naturally tend to do if you just
334
+ follow your own inclinations.
335
+ [10]The component of entrepreneurship that really matters is domain
336
+ expertise. The way to become Larry Page was to become an expert
337
+ on search. And the way to become an expert on search was to be
338
+ driven by genuine curiosity, not some ulterior motive.At its best, starting a startup is merely an ulterior motive for
339
+ curiosity. And you'll do it best if you introduce the ulterior
340
+ motive toward the end of the process.So here is the ultimate advice for young would-be startup founders,
341
+ boiled down to two words: just learn.
342
+ Notes[1]
343
+ Some founders listen more than others, and this tends to be a
344
+ predictor of success. One of the things I
345
+ remember about the Airbnbs during YC is how intently they listened.[2]
346
+ In fact, this is one of the reasons startups are possible. If
347
+ big companies weren't plagued by internal inefficiencies, they'd
348
+ be proportionately more effective, leaving less room for startups.[3]
349
+ In a startup you have to spend a lot of time on schleps, but this sort of work is merely
350
+ unglamorous, not bogus.[4]
351
+ What should you do if your true calling is gaming the system?
352
+ Management consulting.[5]
353
+ The company may not be incorporated, but if you start to get
354
+ significant numbers of users, you've started it, whether you realize
355
+ it yet or not.[6]
356
+ It shouldn't be that surprising that colleges can't teach
357
+ students how to be good startup founders, because they can't teach
358
+ them how to be good employees either.The way universities "teach" students how to be employees is to
359
+ hand off the task to companies via internship programs. But you
360
+ couldn't do the equivalent thing for startups, because by definition
361
+ if the students did well they would never come back.[7]
362
+ Charles Darwin was 22 when he received an invitation to travel
363
+ aboard the HMS Beagle as a naturalist. It was only because he was
364
+ otherwise unoccupied, to a degree that alarmed his family, that he
365
+ could accept it. And yet if he hadn't we probably would not know
366
+ his name.[8]
367
+ Parents can sometimes be especially conservative in this
368
+ department. There are some whose definition of important problems
369
+ includes only those on the critical path to med school.[9]
370
+ I did manage to think of a heuristic for detecting whether you
371
+ have a taste for interesting ideas: whether you find known boring
372
+ ideas intolerable. Could you endure studying literary theory, or
373
+ working in middle management at a large company?[10]
374
+ In fact, if your goal is to start a startup, you can stick
375
+ even more closely to the ideal of a liberal education than past
376
+ generations have. Back when students focused mainly on getting a
377
+ job after college, they thought at least a little about how the
378
+ courses they took might look to an employer. And perhaps even
379
+ worse, they might shy away from taking a difficult class lest they
380
+ get a low grade, which would harm their all-important GPA. Good
381
+ news: users don't care what your GPA
382
+ was. And I've never heard of investors caring either. Y Combinator
383
+ certainly never asks what classes you took in college or what grades
384
+ you got in them.
385
+ Thanks to Sam Altman, Paul Buchheit, John Collison, Patrick
386
+ Collison, Jessica Livingston, Robert Morris, Geoff Ralston, and
387
+ Fred Wilson for reading drafts of this.
PaulGrahamEssays/bias.txt ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ October 2015This will come as a surprise to a lot of people, but in some cases
2
+ it's possible to detect bias in a selection process without knowing
3
+ anything about the applicant pool. Which is exciting because among
4
+ other things it means third parties can use this technique to detect
5
+ bias whether those doing the selecting want them to or not.You can use this technique whenever (a) you have at least
6
+ a random sample of the applicants that were selected, (b) their
7
+ subsequent performance is measured, and (c) the groups of
8
+ applicants you're comparing have roughly equal distribution of ability.How does it work? Think about what it means to be biased. What
9
+ it means for a selection process to be biased against applicants
10
+ of type x is that it's harder for them to make it through. Which
11
+ means applicants of type x have to be better to get selected than
12
+ applicants not of type x.
13
+ [1]
14
+ Which means applicants of type x
15
+ who do make it through the selection process will outperform other
16
+ successful applicants. And if the performance of all the successful
17
+ applicants is measured, you'll know if they do.Of course, the test you use to measure performance must be a valid
18
+ one. And in particular it must not be invalidated by the bias you're
19
+ trying to measure.
20
+ But there are some domains where performance can be measured, and
21
+ in those detecting bias is straightforward. Want to know if the
22
+ selection process was biased against some type of applicant? Check
23
+ whether they outperform the others. This is not just a heuristic
24
+ for detecting bias. It's what bias means.For example, many suspect that venture capital firms are biased
25
+ against female founders. This would be easy to detect: among their
26
+ portfolio companies, do startups with female founders outperform
27
+ those without? A couple months ago, one VC firm (almost certainly
28
+ unintentionally) published a study showing bias of this type. First
29
+ Round Capital found that among its portfolio companies, startups
30
+ with female founders outperformed
31
+ those without by 63%.
32
+ [2]The reason I began by saying that this technique would come as a
33
+ surprise to many people is that we so rarely see analyses of this
34
+ type. I'm sure it will come as a surprise to First Round that they
35
+ performed one. I doubt anyone there realized that by limiting their
36
+ sample to their own portfolio, they were producing a study not of
37
+ startup trends but of their own biases when selecting companies.I predict we'll see this technique used more in the future. The
38
+ information needed to conduct such studies is increasingly available.
39
+ Data about who applies for things is usually closely guarded by the
40
+ organizations selecting them, but nowadays data about who gets
41
+ selected is often publicly available to anyone who takes the trouble
42
+ to aggregate it.
43
+ Notes[1]
44
+ This technique wouldn't work if the selection process looked
45
+ for different things from different types of applicants—for
46
+ example, if an employer hired men based on their ability but women
47
+ based on their appearance.[2]
48
+ As Paul Buchheit points out, First Round excluded their most
49
+ successful investment, Uber, from the study. And while it
50
+ makes sense to exclude outliers from some types of studies,
51
+ studies of returns from startup investing, which is all about
52
+ hitting outliers, are not one of them.
53
+ Thanks to Sam Altman, Jessica Livingston, and Geoff Ralston for reading
54
+ drafts of this.
PaulGrahamEssays/boss.txt ADDED
@@ -0,0 +1,218 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ March 2008, rev. June 2008Technology tends to separate normal from natural. Our bodies
10
+ weren't designed to eat the foods that people in rich countries eat, or
11
+ to get so little exercise.
12
+ There may be a similar problem with the way we work:
13
+ a normal job may be as bad for us intellectually as white flour
14
+ or sugar is for us physically.I began to suspect this after spending several years working
15
+ with startup founders. I've now worked with over 200 of them, and I've
16
+ noticed a definite difference between programmers working on their
17
+ own startups and those working for large organizations.
18
+ I wouldn't say founders seem happier, necessarily;
19
+ starting a startup can be very stressful. Maybe the best way to put
20
+ it is to say that they're happier in the sense that your body is
21
+ happier during a long run than sitting on a sofa eating
22
+ doughnuts.Though they're statistically abnormal, startup founders seem to be
23
+ working in a way that's more natural for humans.I was in Africa last year and saw a lot of animals in the wild that
24
+ I'd only seen in zoos before. It was remarkable how different they
25
+ seemed. Particularly lions. Lions in the wild seem about ten times
26
+ more alive. They're like different animals. I suspect that working
27
+ for oneself feels better to humans in much the same way that living
28
+ in the wild must feel better to a wide-ranging predator like a lion.
29
+ Life in a zoo is easier, but it isn't the life they were designed
30
+ for.
31
+ TreesWhat's so unnatural about working for a big company? The root of
32
+ the problem is that humans weren't meant to work in such large
33
+ groups.Another thing you notice when you see animals in the wild is that
34
+ each species thrives in groups of a certain size. A herd of impalas
35
+ might have 100 adults; baboons maybe 20; lions rarely 10. Humans
36
+ also seem designed to work in groups, and what I've read about
37
+ hunter-gatherers accords with research on organizations and my own
38
+ experience to suggest roughly what the ideal size is: groups of 8
39
+ work well; by 20 they're getting hard to manage; and a group of 50
40
+ is really unwieldy.
41
+ [1]
42
+ Whatever the upper limit is, we are clearly not meant to work in
43
+ groups of several hundred. And yet—for reasons having more
44
+ to do with technology than human nature—a great many people
45
+ work for companies with hundreds or thousands of employees.Companies know groups that large wouldn't work, so they divide
46
+ themselves into units small enough to work together. But to
47
+ coordinate these they have to introduce something new: bosses.These smaller groups are always arranged in a tree structure. Your
48
+ boss is the point where your group attaches to the tree. But when
49
+ you use this trick for dividing a large group into smaller ones,
50
+ something strange happens that I've never heard anyone mention
51
+ explicitly. In the group one level up from yours, your boss
52
+ represents your entire group. A group of 10 managers is not merely
53
+ a group of 10 people working together in the usual way. It's really
54
+ a group of groups. Which means for a group of 10 managers to work
55
+ together as if they were simply a group of 10 individuals, the group
56
+ working for each manager would have to work as if they were a single
57
+ person—the workers and manager would each share only one
58
+ person's worth of freedom between them.In practice a group of people are never able to act as if they were
59
+ one person. But in a large organization divided into groups in
60
+ this way, the pressure is always in that direction. Each group
61
+ tries its best to work as if it were the small group of individuals
62
+ that humans were designed to work in. That was the point of creating
63
+ it. And when you propagate that constraint, the result is that
64
+ each person gets freedom of action in inverse proportion to the
65
+ size of the entire tree.
66
+ [2]Anyone who's worked for a large organization has felt this. You
67
+ can feel the difference between working for a company with 100
68
+ employees and one with 10,000, even if your group has only 10 people.
69
+ Corn SyrupA group of 10 people within a large organization is a kind of fake
70
+ tribe. The number of people you interact with is about right. But
71
+ something is missing: individual initiative. Tribes of hunter-gatherers
72
+ have much more freedom. The leaders have a little more power than other
73
+ members of the tribe, but they don't generally tell them what to
74
+ do and when the way a boss can.It's not your boss's fault. The real problem is that in the group
75
+ above you in the hierarchy, your entire group is one virtual person.
76
+ Your boss is just the way that constraint is imparted to you.So working in a group of 10 people within a large organization feels
77
+ both right and wrong at the same time. On the surface it feels
78
+ like the kind of group you're meant to work in, but something major
79
+ is missing. A job at a big company is like high fructose corn
80
+ syrup: it has some of the qualities of things you're meant to like,
81
+ but is disastrously lacking in others.Indeed, food is an excellent metaphor to explain what's wrong with
82
+ the usual sort of job.For example, working for a big company is the default thing to do,
83
+ at least for programmers. How bad could it be? Well, food shows
84
+ that pretty clearly. If you were dropped at a random point in
85
+ America today, nearly all the food around you would be bad for you.
86
+ Humans were not designed to eat white flour, refined sugar, high
87
+ fructose corn syrup, and hydrogenated vegetable oil. And yet if
88
+ you analyzed the contents of the average grocery store you'd probably
89
+ find these four ingredients accounted for most of the calories.
90
+ "Normal" food is terribly bad for you. The only people who eat
91
+ what humans were actually designed to eat are a few Birkenstock-wearing
92
+ weirdos in Berkeley.If "normal" food is so bad for us, why is it so common? There are
93
+ two main reasons. One is that it has more immediate appeal. You
94
+ may feel lousy an hour after eating that pizza, but eating the first
95
+ couple bites feels great. The other is economies of scale.
96
+ Producing junk food scales; producing fresh vegetables doesn't.
97
+ Which means (a) junk food can be very cheap, and (b) it's worth
98
+ spending a lot to market it.If people have to choose between something that's cheap, heavily
99
+ marketed, and appealing in the short term, and something that's
100
+ expensive, obscure, and appealing in the long term, which do you
101
+ think most will choose?It's the same with work. The average MIT graduate wants to work
102
+ at Google or Microsoft, because it's a recognized brand, it's safe,
103
+ and they'll get paid a good salary right away. It's the job
104
+ equivalent of the pizza they had for lunch. The drawbacks will
105
+ only become apparent later, and then only in a vague sense of
106
+ malaise.And founders and early employees of startups, meanwhile, are like
107
+ the Birkenstock-wearing weirdos of Berkeley: though a tiny minority
108
+ of the population, they're the ones living as humans are meant to.
109
+ In an artificial world, only extremists live naturally.
110
+ ProgrammersThe restrictiveness of big company jobs is particularly hard on
111
+ programmers, because the essence of programming is to build new
112
+ things. Sales people make much the same pitches every day; support
113
+ people answer much the same questions; but once you've written a
114
+ piece of code you don't need to write it again. So a programmer
115
+ working as programmers are meant to is always making new things.
116
+ And when you're part of an organization whose structure gives each
117
+ person freedom in inverse proportion to the size of the tree, you're
118
+ going to face resistance when you do something new.This seems an inevitable consequence of bigness. It's true even
119
+ in the smartest companies. I was talking recently to a founder who
120
+ considered starting a startup right out of college, but went to
121
+ work for Google instead because he thought he'd learn more there.
122
+ He didn't learn as much as he expected. Programmers learn by doing,
123
+ and most of the things he wanted to do, he couldn't—sometimes
124
+ because the company wouldn't let him, but often because the company's
125
+ code wouldn't let him. Between the drag of legacy code, the overhead
126
+ of doing development in such a large organization, and the restrictions
127
+ imposed by interfaces owned by other groups, he could only try a
128
+ fraction of the things he would have liked to. He said he has
129
+ learned much more in his own startup, despite the fact that he has
130
+ to do all the company's errands as well as programming, because at
131
+ least when he's programming he can do whatever he wants.An obstacle downstream propagates upstream. If you're not allowed
132
+ to implement new ideas, you stop having them. And vice versa: when
133
+ you can do whatever you want, you have more ideas about what to do.
134
+ So working for yourself makes your brain more powerful in the same
135
+ way a low-restriction exhaust system makes an engine more powerful.Working for yourself doesn't have to mean starting a startup, of
136
+ course. But a programmer deciding between a regular job at a big
137
+ company and their own startup is probably going to learn more doing
138
+ the startup.You can adjust the amount of freedom you get by scaling the size
139
+ of company you work for. If you start the company, you'll have the
140
+ most freedom. If you become one of the first 10 employees you'll
141
+ have almost as much freedom as the founders. Even a company with
142
+ 100 people will feel different from one with 1000.Working for a small company doesn't ensure freedom. The tree
143
+ structure of large organizations sets an upper bound on freedom,
144
+ not a lower bound. The head of a small company may still choose
145
+ to be a tyrant. The point is that a large organization is compelled
146
+ by its structure to be one.
147
+ ConsequencesThat has real consequences for both organizations and individuals.
148
+ One is that companies will inevitably slow down as they grow larger,
149
+ no matter how hard they try to keep their startup mojo. It's a
150
+ consequence of the tree structure that every large organization is
151
+ forced to adopt.Or rather, a large organization could only avoid slowing down if
152
+ they avoided tree structure. And since human nature limits the
153
+ size of group that can work together, the only way I can imagine
154
+ for larger groups to avoid tree structure would be to have no
155
+ structure: to have each group actually be independent, and to work
156
+ together the way components of a market economy do.That might be worth exploring. I suspect there are already some
157
+ highly partitionable businesses that lean this way. But I don't
158
+ know any technology companies that have done it.There is one thing companies can do short of structuring themselves
159
+ as sponges: they can stay small. If I'm right, then it really
160
+ pays to keep a company as small as it can be at every stage.
161
+ Particularly a technology company. Which means it's doubly important
162
+ to hire the best people. Mediocre hires hurt you twice: they get
163
+ less done, but they also make you big, because you need more of
164
+ them to solve a given problem.For individuals the upshot is the same: aim small. It will always
165
+ suck to work for large organizations, and the larger the organization,
166
+ the more it will suck.In an essay I wrote a couple years ago
167
+ I advised graduating seniors
168
+ to work for a couple years for another company before starting their
169
+ own. I'd modify that now. Work for another company if you want
170
+ to, but only for a small one, and if you want to start your own
171
+ startup, go ahead.The reason I suggested college graduates not start startups immediately
172
+ was that I felt most would fail. And they will. But ambitious
173
+ programmers are better off doing their own thing and failing than
174
+ going to work at a big company. Certainly they'll learn more. They
175
+ might even be better off financially. A lot of people in their
176
+ early twenties get into debt, because their expenses grow even
177
+ faster than the salary that seemed so high when they left school.
178
+ At least if you start a startup and fail your net worth will be
179
+ zero rather than negative.
180
+ [3]We've now funded so many different types of founders that we have
181
+ enough data to see patterns, and there seems to be no benefit from
182
+ working for a big company. The people who've worked for a few years
183
+ do seem better than the ones straight out of college, but only
184
+ because they're that much older.The people who come to us from big companies often seem kind of
185
+ conservative. It's hard to say how much is because big companies
186
+ made them that way, and how much is the natural conservatism that
187
+ made them work for the big companies in the first place. But
188
+ certainly a large part of it is learned. I know because I've seen
189
+ it burn off.Having seen that happen so many times is one of the things that
190
+ convinces me that working for oneself, or at least for a small
191
+ group, is the natural way for programmers to live. Founders arriving
192
+ at Y Combinator often have the downtrodden air of refugees. Three
193
+ months later they're transformed: they have so much more
194
+ confidence
195
+ that they seem as if they've grown several inches taller.
196
+ [4]
197
+ Strange as this sounds, they seem both more worried and happier at the same
198
+ time. Which is exactly how I'd describe the way lions seem in the
199
+ wild.Watching employees get transformed into founders makes it clear
200
+ that the difference between the two is due mostly to environment—and
201
+ in particular that the environment in big companies is toxic to
202
+ programmers. In the first couple weeks of working on their own
203
+ startup they seem to come to life, because finally they're working
204
+ the way people are meant to.Notes[1]
205
+ When I talk about humans being meant or designed to live a
206
+ certain way, I mean by evolution.[2]
207
+ It's not only the leaves who suffer. The constraint propagates
208
+ up as well as down. So managers are constrained too; instead of
209
+ just doing things, they have to act through subordinates.[3]
210
+ Do not finance your startup with credit cards. Financing a
211
+ startup with debt is usually a stupid move, and credit card debt
212
+ stupidest of all. Credit card debt is a bad idea, period. It is
213
+ a trap set by evil companies for the desperate and the foolish.[4]
214
+ The founders we fund used to be younger (initially we encouraged
215
+ undergrads to apply), and the first couple times I saw this I used
216
+ to wonder if they were actually getting physically taller.Thanks to Trevor Blackwell, Ross Boucher, Aaron Iba, Abby
217
+ Kirigin, Ivan Kirigin, Jessica Livingston, and Robert Morris for
218
+ reading drafts of this.
PaulGrahamEssays/copy.txt ADDED
@@ -0,0 +1,81 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ July 2006
2
+ When I was in high school I spent a lot of time imitating bad
3
+ writers. What we studied in English classes was mostly fiction,
4
+ so I assumed that was the highest form of writing. Mistake number
5
+ one. The stories that seemed to be most admired were ones in which
6
+ people suffered in complicated ways. Anything funny or
7
+ gripping was ipso facto suspect, unless it was old enough to be hard to
8
+ understand, like Shakespeare or Chaucer. Mistake number two. The
9
+ ideal medium seemed the short story, which I've since learned had
10
+ quite a brief life, roughly coincident with the peak of magazine
11
+ publishing. But since their size made them perfect for use in
12
+ high school classes, we read a lot of them, which gave us the
13
+ impression the short story was flourishing. Mistake number three.
14
+ And because they were so short, nothing really had to happen; you
15
+ could just show a randomly truncated slice of life, and that was
16
+ considered advanced. Mistake number four. The result was that I
17
+ wrote a lot of stories in which nothing happened except that someone
18
+ was unhappy in a way that seemed deep.For most of college I was a philosophy major. I was very impressed
19
+ by the papers published in philosophy journals. They were so
20
+ beautifully typeset, and their tone was just captivating—alternately
21
+ casual and buffer-overflowingly technical. A fellow would be walking
22
+ along a street and suddenly modality qua modality would spring upon
23
+ him. I didn't ever quite understand these papers, but I figured
24
+ I'd get around to that later, when I had time to reread them more
25
+ closely. In the meantime I tried my best to imitate them. This
26
+ was, I can now see, a doomed undertaking, because they weren't
27
+ really saying anything. No philosopher ever refuted another, for
28
+ example, because no one said anything definite enough to refute.
29
+ Needless to say, my imitations didn't say anything either.In grad school I was still wasting time imitating the wrong things.
30
+ There was then a fashionable type of program called an expert system,
31
+ at the core of which was something called an inference engine. I
32
+ looked at what these things did and thought "I could write that in
33
+ a thousand lines of code." And yet eminent professors were writing
34
+ books about them, and startups were selling them for a year's salary
35
+ a copy. What an opportunity, I thought; these impressive things
36
+ seem easy to me; I must be pretty sharp. Wrong. It was simply a
37
+ fad. The books the professors wrote about expert systems are now
38
+ ignored. They were not even on a path to anything interesting.
39
+ And the customers paying so much for them were largely the same
40
+ government agencies that paid thousands for screwdrivers and toilet
41
+ seats.How do you avoid copying the wrong things? Copy only what you
42
+ genuinely like. That would have saved me in all three cases. I
43
+ didn't enjoy the short stories we had to read in English classes;
44
+ I didn't learn anything from philosophy papers; I didn't use expert
45
+ systems myself. I believed these things were good because they
46
+ were admired.It can be hard to separate the things you like from the things
47
+ you're impressed with. One trick is to ignore presentation. Whenever
48
+ I see a painting impressively hung in a museum, I ask myself: how
49
+ much would I pay for this if I found it at a garage sale, dirty and
50
+ frameless, and with no idea who painted it? If you walk around a
51
+ museum trying this experiment, you'll find you get some truly
52
+ startling results. Don't ignore this data point just because it's
53
+ an outlier.Another way to figure out what you like is to look at what you enjoy
54
+ as guilty pleasures. Many things people like, especially if they're
55
+ young and ambitious, they like largely for the feeling of virtue
56
+ in liking them. 99% of people reading Ulysses are thinking
57
+ "I'm reading Ulysses" as they do it. A guilty pleasure is
58
+ at least a pure one. What do you read when you don't feel up to being
59
+ virtuous? What kind of book do you read and feel sad that there's
60
+ only half of it left, instead of being impressed that you're half
61
+ way through? That's what you really like.Even when you find genuinely good things to copy, there's another
62
+ pitfall to be avoided. Be careful to copy what makes them good,
63
+ rather than their flaws. It's easy to be drawn into imitating
64
+ flaws, because they're easier to see, and of course easier to copy
65
+ too. For example, most painters in the eighteenth and nineteenth
66
+ centuries used brownish colors. They were imitating the great
67
+ painters of the Renaissance, whose paintings by that time were brown
68
+ with dirt. Those paintings have since been cleaned, revealing
69
+ brilliant colors; their imitators are of course still brown.It was painting, incidentally, that cured me of copying the wrong
70
+ things. Halfway through grad school I decided I wanted to try being
71
+ a painter, and the art world was so manifestly corrupt that it
72
+ snapped the leash of credulity. These people made philosophy
73
+ professors seem as scrupulous as mathematicians. It was so clearly
74
+ a choice of doing good work xor being an insider that I was forced
75
+ to see the distinction. It's there to some degree in almost every
76
+ field, but I had till then managed to avoid facing it.That was one of the most valuable things I learned from painting:
77
+ you have to figure out for yourself what's
78
+ good. You can't trust
79
+ authorities. They'll lie to you on this one.
80
+
81
+ Comment on this essay.
PaulGrahamEssays/corpdev.txt ADDED
@@ -0,0 +1,107 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ January 2015Corporate Development, aka corp dev, is the group within companies
2
+ that buys other companies. If you're talking to someone from corp
3
+ dev, that's why, whether you realize it yet or not.It's usually a mistake to talk to corp dev unless (a) you want to
4
+ sell your company right now and (b) you're sufficiently likely to
5
+ get an offer at an acceptable price. In practice that means startups
6
+ should only talk to corp dev when they're either doing really well
7
+ or really badly. If you're doing really badly, meaning the company
8
+ is about to die, you may as well talk to them, because you have
9
+ nothing to lose. And if you're doing really well, you can safely
10
+ talk to them, because you both know the price will have to be high,
11
+ and if they show the slightest sign of wasting your time, you'll
12
+ be confident enough to tell them to get lost.The danger is to companies in the middle. Particularly to young
13
+ companies that are growing fast, but haven't been doing it for long
14
+ enough to have grown big yet. It's usually a mistake for a promising
15
+ company less than a year old even to talk to corp dev.But it's a mistake founders constantly make. When someone from
16
+ corp dev wants to meet, the founders tell themselves they should
17
+ at least find out what they want. Besides, they don't want to
18
+ offend Big Company by refusing to meet.Well, I'll tell you what they want. They want to talk about buying
19
+ you. That's what the title "corp dev" means. So before agreeing
20
+ to meet with someone from corp dev, ask yourselves, "Do we want to
21
+ sell the company right now?" And if the answer is no, tell them
22
+ "Sorry, but we're focusing on growing the company." They won't be
23
+ offended. And certainly the founders of Big Company won't be
24
+ offended. If anything they'll think more highly of you. You'll
25
+ remind them of themselves. They didn't sell either; that's why
26
+ they're in a position now to buy other companies.
27
+ [1]Most founders who get contacted by corp dev already know what it
28
+ means. And yet even when they know what corp dev does and know
29
+ they don't want to sell, they take the meeting. Why do they do it?
30
+ The same mix of denial and wishful thinking that underlies most
31
+ mistakes founders make. It's flattering to talk to someone who wants
32
+ to buy you. And who knows, maybe their offer will be surprisingly
33
+ high. You should at least see what it is, right?No. If they were going to send you an offer immediately by email,
34
+ sure, you might as well open it. But that is not how conversations
35
+ with corp dev work. If you get an offer at all, it will be at the
36
+ end of a long and unbelievably distracting process. And if the
37
+ offer is surprising, it will be surprisingly low.Distractions are the thing you can least afford in a startup. And
38
+ conversations with corp dev are the worst sort of distraction,
39
+ because as well as consuming your attention they undermine your
40
+ morale. One of the tricks to surviving a grueling process is not
41
+ to stop and think how tired you are. Instead you get into a sort
42
+ of flow.
43
+ [2]
44
+ Imagine what it would do to you if at mile 20 of a
45
+ marathon, someone ran up beside you and said "You must feel really
46
+ tired. Would you like to stop and take a rest?" Conversations
47
+ with corp dev are like that but worse, because the suggestion of
48
+ stopping gets combined in your mind with the imaginary high price
49
+ you think they'll offer.And then you're really in trouble. If they can, corp dev people
50
+ like to turn the tables on you. They like to get you to the point
51
+ where you're trying to convince them to buy instead of them trying
52
+ to convince you to sell. And surprisingly often they succeed.This is a very slippery slope, greased with some of the most powerful
53
+ forces that can work on founders' minds, and attended by an experienced
54
+ professional whose full time job is to push you down it.Their tactics in pushing you down that slope are usually fairly
55
+ brutal. Corp dev people's whole job is to buy companies, and they
56
+ don't even get to choose which. The only way their performance is
57
+ measured is by how cheaply they can buy you, and the more ambitious
58
+ ones will stop at nothing to achieve that. For example, they'll
59
+ almost always start with a lowball offer, just to see if you'll
60
+ take it. Even if you don't, a low initial offer will demoralize you
61
+ and make you easier to manipulate.And that is the most innocent of their tactics. Just wait till
62
+ you've agreed on a price and think you have a done deal, and then
63
+ they come back and say their boss has vetoed the deal and won't do
64
+ it for more than half the agreed upon price. Happens all the time.
65
+ If you think investors can behave badly, it's nothing compared to
66
+ what corp dev people can do. Even corp dev people at companies
67
+ that are otherwise benevolent.I remember once complaining to a
68
+ friend at Google about some nasty trick their corp dev people had
69
+ pulled on a YC startup."What happened to Don't be Evil?" I asked."I don't think corp dev got the memo," he replied.The tactics you encounter in M&A conversations can be like nothing
70
+ you've experienced in the otherwise comparatively
71
+ upstanding world
72
+ of Silicon Valley. It's as if a chunk of genetic material from the
73
+ old-fashioned robber baron business world got incorporated into the
74
+ startup world.
75
+ [3]The simplest way to protect yourself is to use the trick that John
76
+ D. Rockefeller, whose grandfather was an alcoholic, used to protect
77
+ himself from becoming one. He once told a Sunday school class
78
+
79
+ Boys, do you know why I never became a drunkard? Because I never
80
+ took the first drink.
81
+
82
+ Do you want to sell your company right now? Not eventually, right
83
+ now. If not, just don't take the first meeting. They won't be
84
+ offended. And you in turn will be guaranteed to be spared one of
85
+ the worst experiences that can happen to a startup.If you do want to sell, there's another set of
86
+ techniques
87
+ for doing
88
+ that. But the biggest mistake founders make in dealing with corp
89
+ dev is not doing a bad job of talking to them when they're ready
90
+ to, but talking to them before they are. So if you remember only
91
+ the title of this essay, you already know most of what you need to
92
+ know about M&A in the first year.Notes[1]
93
+ I'm not saying you should never sell. I'm saying you should
94
+ be clear in your own mind about whether you want to sell or not,
95
+ and not be led by manipulation or wishful thinking into trying to
96
+ sell earlier than you otherwise would have.[2]
97
+ In a startup, as in most competitive sports, the task at hand
98
+ almost does this for you; you're too busy to feel tired. But when
99
+ you lose that protection, e.g. at the final whistle, the fatigue
100
+ hits you like a wave. To talk to corp dev is to let yourself feel
101
+ it mid-game.[3]
102
+ To be fair, the apparent misdeeds of corp dev people are magnified
103
+ by the fact that they function as the face of a large organization
104
+ that often doesn't know its own mind. Acquirers can be surprisingly
105
+ indecisive about acquisitions, and their flakiness is indistinguishable
106
+ from dishonesty by the time it filters down to you.Thanks to Marc Andreessen, Jessica Livingston, Geoff
107
+ Ralston, and Qasar Younis for reading drafts of this.
PaulGrahamEssays/desres.txt ADDED
@@ -0,0 +1,234 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ January 2003(This article is derived from a keynote talk at the fall 2002 meeting
2
+ of NEPLS.)Visitors to this country are often surprised to find that
3
+ Americans like to begin a conversation by asking "what do you do?"
4
+ I've never liked this question. I've rarely had a
5
+ neat answer to it. But I think I have finally solved the problem.
6
+ Now, when someone asks me what I do, I look them straight
7
+ in the eye and say "I'm designing a
8
+ new dialect of Lisp."
9
+ I recommend this answer to anyone who doesn't like being asked what
10
+ they do. The conversation will turn immediately to other topics.I don't consider myself to be doing research on programming languages.
11
+ I'm just designing one, in the same way that someone might design
12
+ a building or a chair or a new typeface.
13
+ I'm not trying to discover anything new. I just want
14
+ to make a language that will be good to program in. In some ways,
15
+ this assumption makes life a lot easier.The difference between design and research seems to be a question
16
+ of new versus good. Design doesn't have to be new, but it has to
17
+ be good. Research doesn't have to be good, but it has to be new.
18
+ I think these two paths converge at the top: the best design
19
+ surpasses its predecessors by using new ideas, and the best research
20
+ solves problems that are not only new, but actually worth solving.
21
+ So ultimately we're aiming for the same destination, just approaching
22
+ it from different directions.What I'm going to talk about today is what your target looks like
23
+ from the back. What do you do differently when you treat
24
+ programming languages as a design problem instead of a research topic?The biggest difference is that you focus more on the user.
25
+ Design begins by asking, who is this
26
+ for and what do they need from it? A good architect,
27
+ for example, does not begin by creating a design that he then
28
+ imposes on the users, but by studying the intended users and figuring
29
+ out what they need.Notice I said "what they need," not "what they want." I don't mean
30
+ to give the impression that working as a designer means working as
31
+ a sort of short-order cook, making whatever the client tells you
32
+ to. This varies from field to field in the arts, but
33
+ I don't think there is any field in which the best work is done by
34
+ the people who just make exactly what the customers tell them to.The customer is always right in
35
+ the sense that the measure of good design is how well it works
36
+ for the user. If you make a novel that bores everyone, or a chair
37
+ that's horribly uncomfortable to sit in, then you've done a bad
38
+ job, period. It's no defense to say that the novel or the chair
39
+ is designed according to the most advanced theoretical principles.And yet, making what works for the user doesn't mean simply making
40
+ what the user tells you to. Users don't know what all the choices
41
+ are, and are often mistaken about what they really want.The answer to the paradox, I think, is that you have to design
42
+ for the user, but you have to design what the user needs, not simply
43
+ what he says he wants.
44
+ It's much like being a doctor. You can't just treat a patient's
45
+ symptoms. When a patient tells you his symptoms, you have to figure
46
+ out what's actually wrong with him, and treat that.This focus on the user is a kind of axiom from which most of the
47
+ practice of good design can be derived, and around which most design
48
+ issues center.If good design must do what the user needs, who is the user? When
49
+ I say that design must be for users, I don't mean to imply that good
50
+ design aims at some kind of
51
+ lowest common denominator. You can pick any group of users you
52
+ want. If you're designing a tool, for example, you can design it
53
+ for anyone from beginners to experts, and what's good design
54
+ for one group might be bad for another. The point
55
+ is, you have to pick some group of users. I don't think you can
56
+ even talk about good or bad design except with
57
+ reference to some intended user.You're most likely to get good design if the intended users include
58
+ the designer himself. When you design something
59
+ for a group that doesn't include you, it tends to be for people
60
+ you consider to be less sophisticated than you, not more sophisticated.That's a problem, because looking down on the user, however benevolently,
61
+ seems inevitably to corrupt the designer.
62
+ I suspect that very few housing
63
+ projects in the US were designed by architects who expected to live
64
+ in them. You can see the same thing
65
+ in programming languages. C, Lisp, and Smalltalk were created for
66
+ their own designers to use. Cobol, Ada, and Java, were created
67
+ for other people to use.If you think you're designing something for idiots, the odds are
68
+ that you're not designing something good, even for idiots.
69
+ Even if you're designing something for the most sophisticated
70
+ users, though, you're still designing for humans. It's different
71
+ in research. In math you
72
+ don't choose abstractions because they're
73
+ easy for humans to understand; you choose whichever make the
74
+ proof shorter. I think this is true for the sciences generally.
75
+ Scientific ideas are not meant to be ergonomic.Over in the arts, things are very different. Design is
76
+ all about people. The human body is a strange
77
+ thing, but when you're designing a chair,
78
+ that's what you're designing for, and there's no way around it.
79
+ All the arts have to pander to the interests and limitations
80
+ of humans. In painting, for example, all other things being
81
+ equal a painting with people in it will be more interesting than
82
+ one without. It is not merely an accident of history that
83
+ the great paintings of the Renaissance are all full of people.
84
+ If they hadn't been, painting as a medium wouldn't have the prestige
85
+ that it does.Like it or not, programming languages are also for people,
86
+ and I suspect the human brain is just as lumpy and idiosyncratic
87
+ as the human body. Some ideas are easy for people to grasp
88
+ and some aren't. For example, we seem to have a very limited
89
+ capacity for dealing with detail. It's this fact that makes
90
+ programing languages a good idea in the first place; if we
91
+ could handle the detail, we could just program in machine
92
+ language.Remember, too, that languages are not
93
+ primarily a form for finished programs, but something that
94
+ programs have to be developed in. Anyone in the arts could
95
+ tell you that you might want different mediums for the
96
+ two situations. Marble, for example, is a nice, durable
97
+ medium for finished ideas, but a hopelessly inflexible one
98
+ for developing new ideas.A program, like a proof,
99
+ is a pruned version of a tree that in the past has had
100
+ false starts branching off all over it. So the test of
101
+ a language is not simply how clean the finished program looks
102
+ in it, but how clean the path to the finished program was.
103
+ A design choice that gives you elegant finished programs
104
+ may not give you an elegant design process. For example,
105
+ I've written a few macro-defining macros full of nested
106
+ backquotes that look now like little gems, but writing them
107
+ took hours of the ugliest trial and error, and frankly, I'm still
108
+ not entirely sure they're correct.We often act as if the test of a language were how good
109
+ finished programs look in it.
110
+ It seems so convincing when you see the same program
111
+ written in two languages, and one version is much shorter.
112
+ When you approach the problem from the direction of the
113
+ arts, you're less likely to depend on this sort of
114
+ test. You don't want to end up with a programming
115
+ language like marble.For example, it is a huge win in developing software to
116
+ have an interactive toplevel, what in Lisp is called a
117
+ read-eval-print loop. And when you have one this has
118
+ real effects on the design of the language. It would not
119
+ work well for a language where you have to declare
120
+ variables before using them, for example. When you're
121
+ just typing expressions into the toplevel, you want to be
122
+ able to set x to some value and then start doing things
123
+ to x. You don't want to have to declare the type of x
124
+ first. You may dispute either of the premises, but if
125
+ a language has to have a toplevel to be convenient, and
126
+ mandatory type declarations are incompatible with a
127
+ toplevel, then no language that makes type declarations
128
+ mandatory could be convenient to program in.In practice, to get good design you have to get close, and stay
129
+ close, to your users. You have to calibrate your ideas on actual
130
+ users constantly, especially in the beginning. One of the reasons
131
+ Jane Austen's novels are so good is that she read them out loud to
132
+ her family. That's why she never sinks into self-indulgently arty
133
+ descriptions of landscapes,
134
+ or pretentious philosophizing. (The philosophy's there, but it's
135
+ woven into the story instead of being pasted onto it like a label.)
136
+ If you open an average "literary" novel and imagine reading it out loud
137
+ to your friends as something you'd written, you'll feel all too
138
+ keenly what an imposition that kind of thing is upon the reader.In the software world, this idea is known as Worse is Better.
139
+ Actually, there are several ideas mixed together in the concept of
140
+ Worse is Better, which is why people are still arguing about
141
+ whether worse
142
+ is actually better or not. But one of the main ideas in that
143
+ mix is that if you're building something new, you should get a
144
+ prototype in front of users as soon as possible.The alternative approach might be called the Hail Mary strategy.
145
+ Instead of getting a prototype out quickly and gradually refining
146
+ it, you try to create the complete, finished, product in one long
147
+ touchdown pass. As far as I know, this is a
148
+ recipe for disaster. Countless startups destroyed themselves this
149
+ way during the Internet bubble. I've never heard of a case
150
+ where it worked.What people outside the software world may not realize is that
151
+ Worse is Better is found throughout the arts.
152
+ In drawing, for example, the idea was discovered during the
153
+ Renaissance. Now almost every drawing teacher will tell you that
154
+ the right way to get an accurate drawing is not to
155
+ work your way slowly around the contour of an object, because errors will
156
+ accumulate and you'll find at the end that the lines don't meet.
157
+ Instead you should draw a few quick lines in roughly the right place,
158
+ and then gradually refine this initial sketch.In most fields, prototypes
159
+ have traditionally been made out of different materials.
160
+ Typefaces to be cut in metal were initially designed
161
+ with a brush on paper. Statues to be cast in bronze
162
+ were modelled in wax. Patterns to be embroidered on tapestries
163
+ were drawn on paper with ink wash. Buildings to be
164
+ constructed from stone were tested on a smaller scale in wood.What made oil paint so exciting, when it
165
+ first became popular in the fifteenth century, was that you
166
+ could actually make the finished work from the prototype.
167
+ You could make a preliminary drawing if you wanted to, but you
168
+ weren't held to it; you could work out all the details, and
169
+ even make major changes, as you finished the painting.You can do this in software too. A prototype doesn't have to
170
+ be just a model; you can refine it into the finished product.
171
+ I think you should always do this when you can. It lets you
172
+ take advantage of new insights you have along the way. But
173
+ perhaps even more important, it's good for morale.Morale is key in design. I'm surprised people
174
+ don't talk more about it. One of my first
175
+ drawing teachers told me: if you're bored when you're
176
+ drawing something, the drawing will look boring.
177
+ For example, suppose you have to draw a building, and you
178
+ decide to draw each brick individually. You can do this
179
+ if you want, but if you get bored halfway through and start
180
+ making the bricks mechanically instead of observing each one,
181
+ the drawing will look worse than if you had merely suggested
182
+ the bricks.Building something by gradually refining a prototype is good
183
+ for morale because it keeps you engaged. In software, my
184
+ rule is: always have working code. If you're writing
185
+ something that you'll be able to test in an hour, then you
186
+ have the prospect of an immediate reward to motivate you.
187
+ The same is true in the arts, and particularly in oil painting.
188
+ Most painters start with a blurry sketch and gradually
189
+ refine it.
190
+ If you work this way, then in principle
191
+ you never have to end the day with something that actually
192
+ looks unfinished. Indeed, there is even a saying among
193
+ painters: "A painting is never finished, you just stop
194
+ working on it." This idea will be familiar to anyone who
195
+ has worked on software.Morale is another reason that it's hard to design something
196
+ for an unsophisticated user. It's hard to stay interested in
197
+ something you don't like yourself. To make something
198
+ good, you have to be thinking, "wow, this is really great,"
199
+ not "what a piece of shit; those fools will love it."Design means making things for humans. But it's not just the
200
+ user who's human. The designer is human too.Notice all this time I've been talking about "the designer."
201
+ Design usually has to be under the control of a single person to
202
+ be any good. And yet it seems to be possible for several people
203
+ to collaborate on a research project. This seems to
204
+ me one of the most interesting differences between research and
205
+ design.There have been famous instances of collaboration in the arts,
206
+ but most of them seem to have been cases of molecular bonding rather
207
+ than nuclear fusion. In an opera it's common for one person to
208
+ write the libretto and another to write the music. And during the Renaissance,
209
+ journeymen from northern
210
+ Europe were often employed to do the landscapes in the
211
+ backgrounds of Italian paintings. But these aren't true collaborations.
212
+ They're more like examples of Robert Frost's
213
+ "good fences make good neighbors." You can stick instances
214
+ of good design together, but within each individual project,
215
+ one person has to be in control.I'm not saying that good design requires that one person think
216
+ of everything. There's nothing more valuable than the advice
217
+ of someone whose judgement you trust. But after the talking is
218
+ done, the decision about what to do has to rest with one person.Why is it that research can be done by collaborators and
219
+ design can't? This is an interesting question. I don't
220
+ know the answer. Perhaps,
221
+ if design and research converge, the best research is also
222
+ good design, and in fact can't be done by collaborators.
223
+ A lot of the most famous scientists seem to have worked alone.
224
+ But I don't know enough to say whether there
225
+ is a pattern here. It could be simply that many famous scientists
226
+ worked when collaboration was less common.Whatever the story is in the sciences, true collaboration
227
+ seems to be vanishingly rare in the arts. Design by committee is a
228
+ synonym for bad design. Why is that so? Is there some way to
229
+ beat this limitation?I'm inclined to think there isn't-- that good design requires
230
+ a dictator. One reason is that good design has to
231
+ be all of a piece. Design is not just for humans, but
232
+ for individual humans. If a design represents an idea that
233
+ fits in one person's head, then the idea will fit in the user's
234
+ head too.Related:
PaulGrahamEssays/diff.txt ADDED
@@ -0,0 +1,73 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ December 2001 (rev. May 2002)
2
+
3
+ (This article came about in response to some questions on
4
+ the LL1 mailing list. It is now
5
+ incorporated in Revenge of the Nerds.)When McCarthy designed Lisp in the late 1950s, it was
6
+ a radical departure from existing languages,
7
+ the most important of which was Fortran.Lisp embodied nine new ideas:
8
+ 1. Conditionals. A conditional is an if-then-else
9
+ construct. We take these for granted now. They were
10
+ invented
11
+ by McCarthy in the course of developing Lisp.
12
+ (Fortran at that time only had a conditional
13
+ goto, closely based on the branch instruction in the
14
+ underlying hardware.) McCarthy, who was on the Algol committee, got
15
+ conditionals into Algol, whence they spread to most other
16
+ languages.2. A function type. In Lisp, functions are first class
17
+ objects-- they're a data type just like integers, strings,
18
+ etc, and have a literal representation, can be stored in variables,
19
+ can be passed as arguments, and so on.3. Recursion. Recursion existed as a mathematical concept
20
+ before Lisp of course, but Lisp was the first programming language to support
21
+ it. (It's arguably implicit in making functions first class
22
+ objects.)4. A new concept of variables. In Lisp, all variables
23
+ are effectively pointers. Values are what
24
+ have types, not variables, and assigning or binding
25
+ variables means copying pointers, not what they point to.5. Garbage-collection.6. Programs composed of expressions. Lisp programs are
26
+ trees of expressions, each of which returns a value.
27
+ (In some Lisps expressions
28
+ can return multiple values.) This is in contrast to Fortran
29
+ and most succeeding languages, which distinguish between
30
+ expressions and statements.It was natural to have this
31
+ distinction in Fortran because (not surprisingly in a language
32
+ where the input format was punched cards) the language was
33
+ line-oriented. You could not nest statements. And
34
+ so while you needed expressions for math to work, there was
35
+ no point in making anything else return a value, because
36
+ there could not be anything waiting for it.This limitation
37
+ went away with the arrival of block-structured languages,
38
+ but by then it was too late. The distinction between
39
+ expressions and statements was entrenched. It spread from
40
+ Fortran into Algol and thence to both their descendants.When a language is made entirely of expressions, you can
41
+ compose expressions however you want. You can say either
42
+ (using Arc syntax)(if foo (= x 1) (= x 2))or(= x (if foo 1 2))7. A symbol type. Symbols differ from strings in that
43
+ you can test equality by comparing a pointer.8. A notation for code using trees of symbols.9. The whole language always available.
44
+ There is
45
+ no real distinction between read-time, compile-time, and runtime.
46
+ You can compile or run code while reading, read or run code
47
+ while compiling, and read or compile code at runtime.Running code at read-time lets users reprogram Lisp's syntax;
48
+ running code at compile-time is the basis of macros; compiling
49
+ at runtime is the basis of Lisp's use as an extension
50
+ language in programs like Emacs; and reading at runtime
51
+ enables programs to communicate using s-expressions, an
52
+ idea recently reinvented as XML.
53
+ When Lisp was first invented, all these ideas were far
54
+ removed from ordinary programming practice, which was
55
+ dictated largely by the hardware available in the late 1950s.Over time, the default language, embodied
56
+ in a succession of popular languages, has
57
+ gradually evolved toward Lisp. 1-5 are now widespread.
58
+ 6 is starting to appear in the mainstream.
59
+ Python has a form of 7, though there doesn't seem to be
60
+ any syntax for it.
61
+ 8, which (with 9) is what makes Lisp macros
62
+ possible, is so far still unique to Lisp,
63
+ perhaps because (a) it requires those parens, or something
64
+ just as bad, and (b) if you add that final increment of power,
65
+ you can no
66
+ longer claim to have invented a new language, but only
67
+ to have designed a new dialect of Lisp ; -)Though useful to present-day programmers, it's
68
+ strange to describe Lisp in terms of its
69
+ variation from the random expedients other languages
70
+ adopted. That was not, probably, how McCarthy
71
+ thought of it. Lisp wasn't designed to fix the mistakes
72
+ in Fortran; it came about more as the byproduct of an
73
+ attempt to axiomatize computation.
PaulGrahamEssays/ecw.txt ADDED
@@ -0,0 +1,98 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ December 2014If the world were static, we could have monotonically increasing
2
+ confidence in our beliefs. The more (and more varied) experience
3
+ a belief survived, the less likely it would be false. Most people
4
+ implicitly believe something like this about their opinions. And
5
+ they're justified in doing so with opinions about things that don't
6
+ change much, like human nature. But you can't trust your opinions
7
+ in the same way about things that change, which could include
8
+ practically everything else.When experts are wrong, it's often because they're experts on an
9
+ earlier version of the world.Is it possible to avoid that? Can you protect yourself against
10
+ obsolete beliefs? To some extent, yes. I spent almost a decade
11
+ investing in early stage startups, and curiously enough protecting
12
+ yourself against obsolete beliefs is exactly what you have to do
13
+ to succeed as a startup investor. Most really good startup ideas
14
+ look like bad ideas at first, and many of those look bad specifically
15
+ because some change in the world just switched them from bad to
16
+ good. I spent a lot of time learning to recognize such ideas, and
17
+ the techniques I used may be applicable to ideas in general.The first step is to have an explicit belief in change. People who
18
+ fall victim to a monotonically increasing confidence in their
19
+ opinions are implicitly concluding the world is static. If you
20
+ consciously remind yourself it isn't, you start to look for change.Where should one look for it? Beyond the moderately useful
21
+ generalization that human nature doesn't change much, the unfortunate
22
+ fact is that change is hard to predict. This is largely a tautology
23
+ but worth remembering all the same: change that matters usually
24
+ comes from an unforeseen quarter.So I don't even try to predict it. When I get asked in interviews
25
+ to predict the future, I always have to struggle to come up with
26
+ something plausible-sounding on the fly, like a student who hasn't
27
+ prepared for an exam.
28
+ [1]
29
+ But it's not out of laziness that I haven't
30
+ prepared. It seems to me that beliefs about the future are so
31
+ rarely correct that they usually aren't worth the extra rigidity
32
+ they impose, and that the best strategy is simply to be aggressively
33
+ open-minded. Instead of trying to point yourself in the right
34
+ direction, admit you have no idea what the right direction is, and
35
+ try instead to be super sensitive to the winds of change.It's ok to have working hypotheses, even though they may constrain
36
+ you a bit, because they also motivate you. It's exciting to chase
37
+ things and exciting to try to guess answers. But you have to be
38
+ disciplined about not letting your hypotheses harden into anything
39
+ more.
40
+ [2]I believe this passive m.o. works not just for evaluating new ideas
41
+ but also for having them. The way to come up with new ideas is not
42
+ to try explicitly to, but to try to solve problems and simply not
43
+ discount weird hunches you have in the process.The winds of change originate in the unconscious minds of domain
44
+ experts. If you're sufficiently expert in a field, any weird idea
45
+ or apparently irrelevant question that occurs to you is ipso facto
46
+ worth exploring.
47
+ [3]
48
+ Within Y Combinator, when an idea is described
49
+ as crazy, it's a compliment—in fact, on average probably a
50
+ higher compliment than when an idea is described as good.Startup investors have extraordinary incentives for correcting
51
+ obsolete beliefs. If they can realize before other investors that
52
+ some apparently unpromising startup isn't, they can make a huge
53
+ amount of money. But the incentives are more than just financial.
54
+ Investors' opinions are explicitly tested: startups come to them
55
+ and they have to say yes or no, and then, fairly quickly, they learn
56
+ whether they guessed right. The investors who say no to a Google
57
+ (and there were several) will remember it for the rest of their
58
+ lives.Anyone who must in some sense bet on ideas rather than merely
59
+ commenting on them has similar incentives. Which means anyone who
60
+ wants such incentives can have them, by turning their comments into
61
+ bets: if you write about a topic in some fairly durable and public
62
+ form, you'll find you worry much more about getting things right
63
+ than most people would in a casual conversation.
64
+ [4]Another trick I've found to protect myself against obsolete beliefs
65
+ is to focus initially on people rather than ideas. Though the nature
66
+ of future discoveries is hard to predict, I've found I can predict
67
+ quite well what sort of people will make them. Good new ideas come
68
+ from earnest, energetic, independent-minded people.Betting on people over ideas saved me countless times as an investor.
69
+ We thought Airbnb was a bad idea, for example. But we could tell
70
+ the founders were earnest, energetic, and independent-minded.
71
+ (Indeed, almost pathologically so.) So we suspended disbelief and
72
+ funded them.This too seems a technique that should be generally applicable.
73
+ Surround yourself with the sort of people new ideas come from. If
74
+ you want to notice quickly when your beliefs become obsolete, you
75
+ can't do better than to be friends with the people whose discoveries
76
+ will make them so.It's hard enough already not to become the prisoner of your own
77
+ expertise, but it will only get harder, because change is accelerating.
78
+ That's not a recent trend; change has been accelerating since the
79
+ paleolithic era. Ideas beget ideas. I don't expect that to change.
80
+ But I could be wrong.
81
+ Notes[1]
82
+ My usual trick is to talk about aspects of the present that
83
+ most people haven't noticed yet.[2]
84
+ Especially if they become well enough known that people start
85
+ to identify them with you. You have to be extra skeptical about
86
+ things you want to believe, and once a hypothesis starts to be
87
+ identified with you, it will almost certainly start to be in that
88
+ category.[3]
89
+ In practice "sufficiently expert" doesn't require one to be
90
+ recognized as an expert—which is a trailing indicator in any
91
+ case. In many fields a year of focused work plus caring a lot would
92
+ be enough.[4]
93
+ Though they are public and persist indefinitely, comments on
94
+ e.g. forums and places like Twitter seem empirically to work like
95
+ casual conversation. The threshold may be whether what you write
96
+ has a title.
97
+ Thanks to Sam Altman, Patrick Collison, and Robert Morris
98
+ for reading drafts of this.
PaulGrahamEssays/founders.txt ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ October 2010
10
+
11
+ (I wrote this for Forbes, who asked me to write something
12
+ about the qualities we look for in founders. In print they had to cut
13
+ the last item because they didn't have room.)1. DeterminationThis has turned out to be the most important quality in startup
14
+ founders. We thought when we started Y Combinator that the most
15
+ important quality would be intelligence. That's the myth in the
16
+ Valley. And certainly you don't want founders to be stupid. But
17
+ as long as you're over a certain threshold of intelligence, what
18
+ matters most is determination. You're going to hit a lot of
19
+ obstacles. You can't be the sort of person who gets demoralized
20
+ easily.Bill Clerico and Rich Aberman of WePay
21
+ are a good example. They're
22
+ doing a finance startup, which means endless negotiations with big,
23
+ bureaucratic companies. When you're starting a startup that depends
24
+ on deals with big companies to exist, it often feels like they're
25
+ trying to ignore you out of existence. But when Bill Clerico starts
26
+ calling you, you may as well do what he asks, because he is not
27
+ going away.
28
+ 2. FlexibilityYou do not however want the sort of determination implied by phrases
29
+ like "don't give up on your dreams." The world of startups is so
30
+ unpredictable that you need to be able to modify your dreams on the
31
+ fly. The best metaphor I've found for the combination of determination
32
+ and flexibility you need is a running back.
33
+ He's determined to get
34
+ downfield, but at any given moment he may need to go sideways or
35
+ even backwards to get there.The current record holder for flexibility may be Daniel Gross of
36
+ Greplin. He applied to YC with
37
+ some bad ecommerce idea. We told
38
+ him we'd fund him if he did something else. He thought for a second,
39
+ and said ok. He then went through two more ideas before settling
40
+ on Greplin. He'd only been working on it for a couple days when
41
+ he presented to investors at Demo Day, but he got a lot of interest.
42
+ He always seems to land on his feet.
43
+ 3. ImaginationIntelligence does matter a lot of course. It seems like the type
44
+ that matters most is imagination. It's not so important to be able
45
+ to solve predefined problems quickly as to be able to come up with
46
+ surprising new ideas. In the startup world, most good ideas
47
+ seem
48
+ bad initially. If they were obviously good, someone would already
49
+ be doing them. So you need the kind of intelligence that produces
50
+ ideas with just the right level of craziness.Airbnb is that kind of idea.
51
+ In fact, when we funded Airbnb, we
52
+ thought it was too crazy. We couldn't believe large numbers of
53
+ people would want to stay in other people's places. We funded them
54
+ because we liked the founders so much. As soon as we heard they'd
55
+ been supporting themselves by selling Obama and McCain branded
56
+ breakfast cereal, they were in. And it turned out the idea was on
57
+ the right side of crazy after all.
58
+ 4. NaughtinessThough the most successful founders are usually good people, they
59
+ tend to have a piratical gleam in their eye. They're not Goody
60
+ Two-Shoes type good. Morally, they care about getting the big
61
+ questions right, but not about observing proprieties. That's why
62
+ I'd use the word naughty rather than evil. They delight in
63
+ breaking
64
+ rules, but not rules that matter. This quality may be redundant
65
+ though; it may be implied by imagination.Sam Altman of Loopt
66
+ is one of the most successful alumni, so we
67
+ asked him what question we could put on the Y Combinator application
68
+ that would help us discover more people like him. He said to ask
69
+ about a time when they'd hacked something to their advantage—hacked in the sense of beating the system, not breaking into
70
+ computers. It has become one of the questions we pay most attention
71
+ to when judging applications.
72
+ 5. FriendshipEmpirically it seems to be hard to start a startup with just
73
+ one
74
+ founder. Most of the big successes have two or three. And the
75
+ relationship between the founders has to be strong. They must
76
+ genuinely like one another, and work well together. Startups do
77
+ to the relationship between the founders what a dog does to a sock:
78
+ if it can be pulled apart, it will be.Emmett Shear and Justin Kan of Justin.tv
79
+ are a good example of close
80
+ friends who work well together. They've known each other since
81
+ second grade. They can practically read one another's minds. I'm
82
+ sure they argue, like all founders, but I have never once sensed
83
+ any unresolved tension between them.Thanks to Jessica Livingston and Chris Steiner for reading drafts of this.
PaulGrahamEssays/foundervisa.txt ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
1
+
2
+
3
+ April 2009I usually avoid politics, but since we now seem to have an administration that's open to suggestions, I'm going to risk making one. The single biggest thing the government could do to increase the number of startups in this country is a policy that would cost nothing: establish a new class of visa for startup founders.The biggest constraint on the number of new startups that get created in the US is not tax policy or employment law or even Sarbanes-Oxley. It's that we won't let the people who want to start them into the country.Letting just 10,000 startup founders into the country each year could have a visible effect on the economy. If we assume 4 people per startup, which is probably an overestimate, that's 2500 new companies. Each year. They wouldn't all grow as big as Google, but out of 2500 some would come close.By definition these 10,000 founders wouldn't be taking jobs from Americans: it could be part of the terms of the visa that they couldn't work for existing companies, only new ones they'd founded. In fact they'd cause there to be
4
+ more jobs for Americans, because the companies they started would hire more employees as they grew.The tricky part might seem to be how one defined a startup. But that could be solved quite easily: let the market decide. Startup investors work hard to find the best startups. The government could not do better than to piggyback on their expertise, and use investment by recognized startup investors as the test of whether a company was a real startup.How would the government decide who's a startup investor? The same way they decide what counts as a university for student visas. We'll establish our own accreditation procedure. We know who one another are.10,000 people is a drop in the bucket by immigration standards, but would represent a huge increase in the pool of startup founders. I think this would have such a visible effect on the economy that it would make the legislator who introduced the bill famous. The only way to know for sure would be to try it, and that would cost practically nothing.
5
+ Thanks to Trevor Blackwell, Paul Buchheit, Jeff Clavier, David Hornik, Jessica Livingston, Greg Mcadoo, Aydin Senkut, and Fred Wilson for reading drafts of this.Related:
PaulGrahamEssays/gap.txt ADDED
@@ -0,0 +1,485 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2004When people care enough about something to do it well, those who
2
+ do it best tend to be far better than everyone else. There's a
3
+ huge gap between Leonardo and second-rate contemporaries like
4
+ Borgognone. You see the same gap between Raymond Chandler and the
5
+ average writer of detective novels. A top-ranked professional chess
6
+ player could play ten thousand games against an ordinary club player
7
+ without losing once.Like chess or painting or writing novels, making money is a very
8
+ specialized skill. But for some reason we treat this skill
9
+ differently. No one complains when a few people surpass all the
10
+ rest at playing chess or writing novels, but when a few people make
11
+ more money than the rest, we get editorials saying this is wrong.Why? The pattern of variation seems no different than for any other
12
+ skill. What causes people to react so strongly when the skill is
13
+ making money?I think there are three reasons we treat making money as different:
14
+ the misleading model of wealth we learn as children; the disreputable
15
+ way in which, till recently, most fortunes were accumulated; and
16
+ the worry that great variations in income are somehow bad for
17
+ society. As far as I can tell, the first is mistaken, the second
18
+ outdated, and the third empirically false. Could it be that, in a
19
+ modern democracy, variation in income is actually a sign of health?The Daddy Model of WealthWhen I was five I thought electricity was created by electric
20
+ sockets. I didn't realize there were power plants out there
21
+ generating it. Likewise, it doesn't occur to most kids that wealth
22
+ is something that has to be generated. It seems to be something
23
+ that flows from parents.Because of the circumstances in which they encounter it, children
24
+ tend to misunderstand wealth. They confuse it with money. They
25
+ think that there is a fixed amount of it. And they think of it as
26
+ something that's distributed by authorities (and so should be
27
+ distributed equally), rather than something that has to be created
28
+ (and might be created unequally).In fact, wealth is not money. Money is just a convenient way of
29
+ trading one form of wealth for another. Wealth is the underlying
30
+ stuff—the goods and services we buy. When you travel to a
31
+ rich or poor country, you don't have to look at people's bank
32
+ accounts to tell which kind you're in. You can see
33
+ wealth—in buildings and streets, in the clothes and the health
34
+ of the people.Where does wealth come from? People make it. This was easier to
35
+ grasp when most people lived on farms, and made many of the things
36
+ they wanted with their own hands. Then you could see in the house,
37
+ the herds, and the granary the wealth that each family created. It
38
+ was obvious then too that the wealth of the world was not a fixed
39
+ quantity that had to be shared out, like slices of a pie. If you
40
+ wanted more wealth, you could make it.This is just as true today, though few of us create wealth directly
41
+ for ourselves (except for a few vestigial domestic tasks). Mostly
42
+ we create wealth for other people in exchange for money, which we
43
+ then trade for the forms of wealth we want.
44
+ [1]Because kids are unable to create wealth, whatever they have has
45
+ to be given to them. And when wealth is something you're given,
46
+ then of course it seems that it should be distributed equally.
47
+ [2]
48
+ As in most families it is. The kids see to that. "Unfair," they
49
+ cry, when one sibling gets more than another.In the real world, you can't keep living off your parents. If you
50
+ want something, you either have to make it, or do something of
51
+ equivalent value for someone else, in order to get them to give you
52
+ enough money to buy it. In the real world, wealth is (except for
53
+ a few specialists like thieves and speculators) something you have
54
+ to create, not something that's distributed by Daddy. And since
55
+ the ability and desire to create it vary from person to person,
56
+ it's not made equally.You get paid by doing or making something people want, and those
57
+ who make more money are often simply better at doing what people
58
+ want. Top actors make a lot more money than B-list actors. The
59
+ B-list actors might be almost as charismatic, but when people go
60
+ to the theater and look at the list of movies playing, they want
61
+ that extra oomph that the big stars have.Doing what people want is not the only way to get money, of course.
62
+ You could also rob banks, or solicit bribes, or establish a monopoly.
63
+ Such tricks account for some variation in wealth, and indeed for
64
+ some of the biggest individual fortunes, but they are not the root
65
+ cause of variation in income. The root cause of variation in income,
66
+ as Occam's Razor implies, is the same as the root cause of variation
67
+ in every other human skill.In the United States, the CEO of a large public company makes about
68
+ 100 times as much as the average person.
69
+ [3]
70
+ Basketball players
71
+ make about 128 times as much, and baseball players 72 times as much.
72
+ Editorials quote this kind of statistic with horror. But I have
73
+ no trouble imagining that one person could be 100 times as productive
74
+ as another. In ancient Rome the price of slaves varied by
75
+ a factor of 50 depending on their skills.
76
+ [4]
77
+ And that's without
78
+ considering motivation, or the extra leverage in productivity that
79
+ you can get from modern technology.Editorials about athletes' or CEOs' salaries remind me of early
80
+ Christian writers, arguing from first principles about whether the
81
+ Earth was round, when they could just walk outside and check.
82
+ [5]
83
+ How much someone's work is worth is not a policy question. It's
84
+ something the market already determines."Are they really worth 100 of us?" editorialists ask. Depends on
85
+ what you mean by worth. If you mean worth in the sense of what
86
+ people will pay for their skills, the answer is yes, apparently.A few CEOs' incomes reflect some kind of wrongdoing. But are there
87
+ not others whose incomes really do reflect the wealth they generate?
88
+ Steve Jobs saved a company that was in a terminal decline. And not
89
+ merely in the way a turnaround specialist does, by cutting costs;
90
+ he had to decide what Apple's next products should be. Few others
91
+ could have done it. And regardless of the case with CEOs, it's
92
+ hard to see how anyone could argue that the salaries of professional
93
+ basketball players don't reflect supply and demand.It may seem unlikely in principle that one individual could really
94
+ generate so much more wealth than another. The key to this mystery
95
+ is to revisit that question, are they really worth 100 of us?
96
+ Would a basketball team trade one of their players for 100
97
+ random people? What would Apple's next product look like if you
98
+ replaced Steve Jobs with a committee of 100 random people?
99
+ [6]
100
+ These
101
+ things don't scale linearly. Perhaps the CEO or the professional
102
+ athlete has only ten times (whatever that means) the skill and
103
+ determination of an ordinary person. But it makes all the difference
104
+ that it's concentrated in one individual.When we say that one kind of work is overpaid and another underpaid,
105
+ what are we really saying? In a free market, prices are determined
106
+ by what buyers want. People like baseball more than poetry, so
107
+ baseball players make more than poets. To say that a certain kind
108
+ of work is underpaid is thus identical with saying that people want
109
+ the wrong things.Well, of course people want the wrong things. It seems odd to be
110
+ surprised by that. And it seems even odder to say that it's
111
+ unjust that certain kinds of work are underpaid.
112
+ [7]
113
+ Then
114
+ you're saying that it's unjust that people want the wrong things.
115
+ It's lamentable that people prefer reality TV and corndogs to
116
+ Shakespeare and steamed vegetables, but unjust? That seems like
117
+ saying that blue is heavy, or that up is circular.The appearance of the word "unjust" here is the unmistakable spectral
118
+ signature of the Daddy Model. Why else would this idea occur in
119
+ this odd context? Whereas if the speaker were still operating on
120
+ the Daddy Model, and saw wealth as something that flowed from a
121
+ common source and had to be shared out, rather than something
122
+ generated by doing what other people wanted, this is exactly what
123
+ you'd get on noticing that some people made much more than others.When we talk about "unequal distribution of income," we should
124
+ also ask, where does that income come from?
125
+ [8]
126
+ Who made the wealth
127
+ it represents? Because to the extent that income varies simply
128
+ according to how much wealth people create, the distribution may
129
+ be unequal, but it's hardly unjust.Stealing ItThe second reason we tend to find great disparities of wealth
130
+ alarming is that for most of human history the usual way to accumulate
131
+ a fortune was to steal it: in pastoral societies by cattle raiding;
132
+ in agricultural societies by appropriating others' estates in times
133
+ of war, and taxing them in times of peace.In conflicts, those on the winning side would receive the estates
134
+ confiscated from the losers. In England in the 1060s, when William
135
+ the Conqueror distributed the estates of the defeated Anglo-Saxon
136
+ nobles to his followers, the conflict was military. By the 1530s,
137
+ when Henry VIII distributed the estates of the monasteries to his
138
+ followers, it was mostly political.
139
+ [9]
140
+ But the principle was the
141
+ same. Indeed, the same principle is at work now in Zimbabwe.In more organized societies, like China, the ruler and his officials
142
+ used taxation instead of confiscation. But here too we see the
143
+ same principle: the way to get rich was not to create wealth, but
144
+ to serve a ruler powerful enough to appropriate it.This started to change in Europe with the rise of the middle class.
145
+ Now we think of the middle class as people who are neither rich nor
146
+ poor, but originally they were a distinct group. In a feudal
147
+ society, there are just two classes: a warrior aristocracy, and the
148
+ serfs who work their estates. The middle class were a new, third
149
+ group who lived in towns and supported themselves by manufacturing
150
+ and trade.Starting in the tenth and eleventh centuries, petty nobles and
151
+ former serfs banded together in towns that gradually became powerful
152
+ enough to ignore the local feudal lords.
153
+ [10]
154
+ Like serfs, the middle
155
+ class made a living largely by creating wealth. (In port cities
156
+ like Genoa and Pisa, they also engaged in piracy.) But unlike serfs
157
+ they had an incentive to create a lot of it. Any wealth a serf
158
+ created belonged to his master. There was not much point in making
159
+ more than you could hide. Whereas the independence of the townsmen
160
+ allowed them to keep whatever wealth they created.Once it became possible to get rich by creating wealth, society as
161
+ a whole started to get richer very rapidly. Nearly everything we
162
+ have was created by the middle class. Indeed, the other two classes
163
+ have effectively disappeared in industrial societies, and their
164
+ names been given to either end of the middle class. (In the original
165
+ sense of the word, Bill Gates is middle class.)But it was not till the Industrial Revolution that wealth creation
166
+ definitively replaced corruption as the best way to get rich. In
167
+ England, at least, corruption only became unfashionable (and in
168
+ fact only started to be called "corruption") when there started to
169
+ be other, faster ways to get rich.Seventeenth-century England was much like the third world today,
170
+ in that government office was a recognized route to wealth. The
171
+ great fortunes of that time still derived more from what we would
172
+ now call corruption than from commerce.
173
+ [11]
174
+ By the nineteenth
175
+ century that had changed. There continued to be bribes, as there
176
+ still are everywhere, but politics had by then been left to men who
177
+ were driven more by vanity than greed. Technology had made it
178
+ possible to create wealth faster than you could steal it. The
179
+ prototypical rich man of the nineteenth century was not a courtier
180
+ but an industrialist.With the rise of the middle class, wealth stopped being a zero-sum
181
+ game. Jobs and Wozniak didn't have to make us poor to make themselves
182
+ rich. Quite the opposite: they created things that made our lives
183
+ materially richer. They had to, or we wouldn't have paid for them.But since for most of the world's history the main route to wealth
184
+ was to steal it, we tend to be suspicious of rich people. Idealistic
185
+ undergraduates find their unconsciously preserved child's model of
186
+ wealth confirmed by eminent writers of the past. It is a case of
187
+ the mistaken meeting the outdated."Behind every great fortune, there is a crime," Balzac wrote. Except
188
+ he didn't. What he actually said was that a great fortune with no
189
+ apparent cause was probably due to a crime well enough executed
190
+ that it had been forgotten. If we were talking about Europe in
191
+ 1000, or most of the third world today, the standard misquotation
192
+ would be spot on. But Balzac lived in nineteenth-century France,
193
+ where the Industrial Revolution was well advanced. He knew you
194
+ could make a fortune without stealing it. After all, he did himself,
195
+ as a popular novelist.
196
+ [12]Only a few countries (by no coincidence, the richest ones) have
197
+ reached this stage. In most, corruption still has the upper hand.
198
+ In most, the fastest way to get wealth is by stealing it. And so
199
+ when we see increasing differences in income in a rich country,
200
+ there is a tendency to worry that it's sliding back toward becoming
201
+ another Venezuela. I think the opposite is happening. I think
202
+ you're seeing a country a full step ahead of Venezuela.The Lever of TechnologyWill technology increase the gap between rich and poor? It will
203
+ certainly increase the gap between the productive and the unproductive.
204
+ That's the whole point of technology. With a tractor an energetic
205
+ farmer could plow six times as much land in a day as he could with
206
+ a team of horses. But only if he mastered a new kind of farming.I've seen the lever of technology grow visibly in my own time. In
207
+ high school I made money by mowing lawns and scooping ice cream at
208
+ Baskin-Robbins. This was the only kind of work available at the
209
+ time. Now high school kids could write software or design web
210
+ sites. But only some of them will; the rest will still be scooping
211
+ ice cream.I remember very vividly when in 1985 improved technology made it
212
+ possible for me to buy a computer of my own. Within months I was
213
+ using it to make money as a freelance programmer. A few years
214
+ before, I couldn't have done this. A few years before, there was
215
+ no such thing as a freelance programmer. But Apple created
216
+ wealth, in the form of powerful, inexpensive computers, and programmers
217
+ immediately set to work using it to create more.As this example suggests, the rate at which technology increases
218
+ our productive capacity is probably exponential, rather than linear.
219
+ So we should expect to see ever-increasing variation in individual
220
+ productivity as time goes on. Will that increase the gap between
221
+ rich and the poor? Depends which gap you mean.Technology should increase the gap in income, but it seems to
222
+ decrease other gaps. A hundred years ago, the rich led a different
223
+ kind of life from ordinary people. They lived in houses
224
+ full of servants, wore elaborately uncomfortable clothes, and
225
+ travelled about in carriages drawn by teams of horses which themselves
226
+ required their own houses and servants. Now, thanks to technology,
227
+ the rich live more like the average person.Cars are a good example of why. It's possible to buy expensive,
228
+ handmade cars that cost hundreds of thousands of dollars. But there
229
+ is not much point. Companies make more money by building a large
230
+ number of ordinary cars than a small number of expensive ones. So
231
+ a company making a mass-produced car can afford to spend a lot more
232
+ on its design. If you buy a custom-made car, something will always
233
+ be breaking. The only point of buying one now is to advertise that
234
+ you can.Or consider watches. Fifty years ago, by spending a lot of money
235
+ on a watch you could get better performance. When watches had
236
+ mechanical movements, expensive watches kept better time. Not any
237
+ more. Since the invention of the quartz movement, an ordinary Timex
238
+ is more accurate than a Patek Philippe costing hundreds of thousands
239
+ of dollars.
240
+ [13]
241
+ Indeed, as with expensive cars, if you're determined
242
+ to spend a lot of money on a watch, you have to put up with some
243
+ inconvenience to do it: as well as keeping worse time, mechanical
244
+ watches have to be wound.The only thing technology can't cheapen is brand. Which is precisely
245
+ why we hear ever more about it. Brand is the residue left as the
246
+ substantive differences between rich and poor evaporate. But what
247
+ label you have on your stuff is a much smaller matter than having
248
+ it versus not having it. In 1900, if you kept a carriage, no one
249
+ asked what year or brand it was. If you had one, you were rich.
250
+ And if you weren't rich, you took the omnibus or walked. Now even
251
+ the poorest Americans drive cars, and it is only because we're so
252
+ well trained by advertising that we can even recognize the especially
253
+ expensive ones.
254
+ [14]The same pattern has played out in industry after industry. If
255
+ there is enough demand for something, technology will make it cheap
256
+ enough to sell in large volumes, and the mass-produced versions
257
+ will be, if not better, at least more convenient.
258
+ [15]
259
+ And there
260
+ is nothing the rich like more than convenience. The rich people I
261
+ know drive the same cars, wear the same clothes, have the same kind
262
+ of furniture, and eat the same foods as my other friends. Their
263
+ houses are in different neighborhoods, or if in the same neighborhood
264
+ are different sizes, but within them life is similar. The houses
265
+ are made using the same construction techniques and contain much
266
+ the same objects. It's inconvenient to do something expensive and
267
+ custom.The rich spend their time more like everyone else too. Bertie
268
+ Wooster seems long gone. Now, most people who are rich enough not
269
+ to work do anyway. It's not just social pressure that makes them;
270
+ idleness is lonely and demoralizing.Nor do we have the social distinctions there were a hundred years
271
+ ago. The novels and etiquette manuals of that period read now
272
+ like descriptions of some strange tribal society. "With respect
273
+ to the continuance of friendships..." hints Mrs. Beeton's Book
274
+ of Household Management (1880), "it may be found necessary, in
275
+ some cases, for a mistress to relinquish, on assuming the responsibility
276
+ of a household, many of those commenced in the earlier part of her
277
+ life." A woman who married a rich man was expected to drop friends
278
+ who didn't. You'd seem a barbarian if you behaved that way today.
279
+ You'd also have a very boring life. People still tend to segregate
280
+ themselves somewhat, but much more on the basis of education than
281
+ wealth.
282
+ [16]Materially and socially, technology seems to be decreasing the gap
283
+ between the rich and the poor, not increasing it. If Lenin walked
284
+ around the offices of a company like Yahoo or Intel or Cisco, he'd
285
+ think communism had won. Everyone would be wearing the same clothes,
286
+ have the same kind of office (or rather, cubicle) with the same
287
+ furnishings, and address one another by their first names instead
288
+ of by honorifics. Everything would seem exactly as he'd predicted,
289
+ until he looked at their bank accounts. Oops.Is it a problem if technology increases that gap? It doesn't seem
290
+ to be so far. As it increases the gap in income, it seems to
291
+ decrease most other gaps.Alternative to an AxiomOne often hears a policy criticized on the grounds that it would
292
+ increase the income gap between rich and poor. As if it were an
293
+ axiom that this would be bad. It might be true that increased
294
+ variation in income would be bad, but I don't see how we can say
295
+ it's axiomatic.Indeed, it may even be false, in industrial democracies. In a
296
+ society of serfs and warlords, certainly, variation in income is a
297
+ sign of an underlying problem. But serfdom is not the only cause
298
+ of variation in income. A 747 pilot doesn't make 40 times as much
299
+ as a checkout clerk because he is a warlord who somehow holds her
300
+ in thrall. His skills are simply much more valuable.I'd like to propose an alternative idea: that in a modern society,
301
+ increasing variation in income is a sign of health. Technology
302
+ seems to increase the variation in productivity at faster than
303
+ linear rates. If we don't see corresponding variation in income,
304
+ there are three possible explanations: (a) that technical innovation
305
+ has stopped, (b) that the people who would create the most wealth
306
+ aren't doing it, or (c) that they aren't getting paid for it.I think we can safely say that (a) and (b) would be bad. If you
307
+ disagree, try living for a year using only the resources available
308
+ to the average Frankish nobleman in 800, and report back to us.
309
+ (I'll be generous and not send you back to the stone age.)The only option, if you're going to have an increasingly prosperous
310
+ society without increasing variation in income, seems to be (c),
311
+ that people will create a lot of wealth without being paid for it.
312
+ That Jobs and Wozniak, for example, will cheerfully work 20-hour
313
+ days to produce the Apple computer for a society that allows them,
314
+ after taxes, to keep just enough of their income to match what they
315
+ would have made working 9 to 5 at a big company.Will people create wealth if they can't get paid for it? Only if
316
+ it's fun. People will write operating systems for free. But they
317
+ won't install them, or take support calls, or train customers to
318
+ use them. And at least 90% of the work that even the highest tech
319
+ companies do is of this second, unedifying kind.All the unfun kinds of wealth creation slow dramatically in a society
320
+ that confiscates private fortunes. We can confirm this empirically.
321
+ Suppose you hear a strange noise that you think may be due to a
322
+ nearby fan. You turn the fan off, and the noise stops. You turn
323
+ the fan back on, and the noise starts again. Off, quiet. On,
324
+ noise. In the absence of other information, it would seem the noise
325
+ is caused by the fan.At various times and places in history, whether you could accumulate
326
+ a fortune by creating wealth has been turned on and off. Northern
327
+ Italy in 800, off (warlords would steal it). Northern Italy in
328
+ 1100, on. Central France in 1100, off (still feudal). England in
329
+ 1800, on. England in 1974, off (98% tax on investment income).
330
+ United States in 1974, on. We've even had a twin study: West
331
+ Germany, on; East Germany, off. In every case, the creation of
332
+ wealth seems to appear and disappear like the noise of a fan as you
333
+ switch on and off the prospect of keeping it.There is some momentum involved. It probably takes at least a
334
+ generation to turn people into East Germans (luckily for England).
335
+ But if it were merely a fan we were studying, without all the extra
336
+ baggage that comes from the controversial topic of wealth, no one
337
+ would have any doubt that the fan was causing the noise.If you suppress variations in income, whether by stealing private
338
+ fortunes, as feudal rulers used to do, or by taxing them away, as
339
+ some modern governments have done, the result always seems to be
340
+ the same. Society as a whole ends up poorer.If I had a choice of living in a society where I was materially
341
+ much better off than I am now, but was among the poorest, or in one
342
+ where I was the richest, but much worse off than I am now, I'd take
343
+ the first option. If I had children, it would arguably be immoral
344
+ not to. It's absolute poverty you want to avoid, not relative
345
+ poverty. If, as the evidence so far implies, you have to have one
346
+ or the other in your society, take relative poverty.You need rich people in your society not so much because in spending
347
+ their money they create jobs, but because of what they have to do
348
+ to get rich. I'm not talking about the trickle-down effect
349
+ here. I'm not saying that if you let Henry Ford get rich, he'll
350
+ hire you as a waiter at his next party. I'm saying that he'll make
351
+ you a tractor to replace your horse.Notes[1]
352
+ Part of the reason this subject is so contentious is that some
353
+ of those most vocal on the subject of wealth—university
354
+ students, heirs, professors, politicians, and journalists—have
355
+ the least experience creating it. (This phenomenon will be familiar
356
+ to anyone who has overheard conversations about sports in a bar.)Students are mostly still on the parental dole, and have not stopped
357
+ to think about where that money comes from. Heirs will be on the
358
+ parental dole for life. Professors and politicians live within
359
+ socialist eddies of the economy, at one remove from the creation
360
+ of wealth, and are paid a flat rate regardless of how hard they
361
+ work. And journalists as part of their professional code segregate
362
+ themselves from the revenue-collecting half of the businesses they
363
+ work for (the ad sales department). Many of these people never
364
+ come face to face with the fact that the money they receive represents
365
+ wealth—wealth that, except in the case of journalists, someone
366
+ else created earlier. They live in a world in which income is
367
+ doled out by a central authority according to some abstract notion
368
+ of fairness (or randomly, in the case of heirs), rather than given
369
+ by other people in return for something they wanted, so it may seem
370
+ to them unfair that things don't work the same in the rest of the
371
+ economy.(Some professors do create a great deal of wealth for
372
+ society. But the money they're paid isn't a quid pro quo.
373
+ It's more in the nature of an investment.)[2]
374
+ When one reads about the origins of the Fabian Society, it
375
+ sounds like something cooked up by the high-minded Edwardian
376
+ child-heroes of Edith Nesbit's The Wouldbegoods.[3]
377
+ According to a study by the Corporate Library, the median total
378
+ compensation, including salary, bonus, stock grants, and the exercise
379
+ of stock options, of S&P 500 CEOs in 2002 was $3.65 million.
380
+ According to Sports Illustrated, the average NBA player's
381
+ salary during the 2002-03 season was $4.54 million, and the average
382
+ major league baseball player's salary at the start of the 2003
383
+ season was $2.56 million. According to the Bureau of Labor
384
+ Statistics, the mean annual wage in the US in 2002 was $35,560.[4]
385
+ In the early empire the price of an ordinary adult slave seems
386
+ to have been about 2,000 sestertii (e.g. Horace, Sat. ii.7.43).
387
+ A servant girl cost 600 (Martial vi.66), while Columella (iii.3.8)
388
+ says that a skilled vine-dresser was worth 8,000. A doctor, P.
389
+ Decimus Eros Merula, paid 50,000 sestertii for his freedom (Dessau,
390
+ Inscriptiones 7812). Seneca (Ep. xxvii.7) reports
391
+ that one Calvisius Sabinus paid 100,000 sestertii apiece for slaves
392
+ learned in the Greek classics. Pliny (Hist. Nat. vii.39)
393
+ says that the highest price paid for a slave up to his time was
394
+ 700,000 sestertii, for the linguist (and presumably teacher) Daphnis,
395
+ but that this had since been exceeded by actors buying their own
396
+ freedom.Classical Athens saw a similar variation in prices. An ordinary
397
+ laborer was worth about 125 to 150 drachmae. Xenophon (Mem.
398
+ ii.5) mentions prices ranging from 50 to 6,000 drachmae (for the
399
+ manager of a silver mine).For more on the economics of ancient slavery see:Jones, A. H. M., "Slavery in the Ancient World," Economic History
400
+ Review, 2:9 (1956), 185-199, reprinted in Finley, M. I. (ed.),
401
+ Slavery in Classical Antiquity, Heffer, 1964.[5]
402
+ Eratosthenes (276—195 BC) used shadow lengths in different
403
+ cities to estimate the Earth's circumference. He was off by only
404
+ about 2%.[6]
405
+ No, and Windows, respectively.[7]
406
+ One of the biggest divergences between the Daddy Model and
407
+ reality is the valuation of hard work. In the Daddy Model, hard
408
+ work is in itself deserving. In reality, wealth is measured by
409
+ what one delivers, not how much effort it costs. If I paint someone's
410
+ house, the owner shouldn't pay me extra for doing it with a toothbrush.It will seem to someone still implicitly operating on the Daddy
411
+ Model that it is unfair when someone works hard and doesn't get
412
+ paid much. To help clarify the matter, get rid of everyone else
413
+ and put our worker on a desert island, hunting and gathering fruit.
414
+ If he's bad at it he'll work very hard and not end up with much
415
+ food. Is this unfair? Who is being unfair to him?[8]
416
+ Part of the reason for the tenacity of the Daddy Model may be
417
+ the dual meaning of "distribution." When economists talk about
418
+ "distribution of income," they mean statistical distribution. But
419
+ when you use the phrase frequently, you can't help associating it
420
+ with the other sense of the word (as in e.g. "distribution of alms"),
421
+ and thereby subconsciously seeing wealth as something that flows
422
+ from some central tap. The word "regressive" as applied to tax
423
+ rates has a similar effect, at least on me; how can anything
424
+ regressive be good?[9]
425
+ "From the beginning of the reign Thomas Lord Roos was an assiduous
426
+ courtier of the young Henry VIII and was soon to reap the rewards.
427
+ In 1525 he was made a Knight of the Garter and given the Earldom
428
+ of Rutland. In the thirties his support of the breach with Rome,
429
+ his zeal in crushing the Pilgrimage of Grace, and his readiness to
430
+ vote the death-penalty in the succession of spectacular treason
431
+ trials that punctuated Henry's erratic matrimonial progress made
432
+ him an obvious candidate for grants of monastic property."Stone, Lawrence, Family and Fortune: Studies in Aristocratic
433
+ Finance in the Sixteenth and Seventeenth Centuries, Oxford
434
+ University Press, 1973, p. 166.[10]
435
+ There is archaeological evidence for large settlements earlier,
436
+ but it's hard to say what was happening in them.Hodges, Richard and David Whitehouse, Mohammed, Charlemagne and
437
+ the Origins of Europe, Cornell University Press, 1983.[11]
438
+ William Cecil and his son Robert were each in turn the most
439
+ powerful minister of the crown, and both used their position to
440
+ amass fortunes among the largest of their times. Robert in particular
441
+ took bribery to the point of treason. "As Secretary of State and
442
+ the leading advisor to King James on foreign policy, [he] was a
443
+ special recipient of favour, being offered large bribes by the Dutch
444
+ not to make peace with Spain, and large bribes by Spain to make
445
+ peace." (Stone, op. cit., p. 17.)[12]
446
+ Though Balzac made a lot of money from writing, he was notoriously
447
+ improvident and was troubled by debts all his life.[13]
448
+ A Timex will gain or lose about .5 seconds per day. The most
449
+ accurate mechanical watch, the Patek Philippe 10 Day Tourbillon,
450
+ is rated at -1.5 to +2 seconds. Its retail price is about $220,000.[14]
451
+ If asked to choose which was more expensive, a well-preserved
452
+ 1989 Lincoln Town Car ten-passenger limousine ($5,000) or a 2004
453
+ Mercedes S600 sedan ($122,000), the average Edwardian might well
454
+ guess wrong.[15]
455
+ To say anything meaningful about income trends, you have to
456
+ talk about real income, or income as measured in what it can buy.
457
+ But the usual way of calculating real income ignores much of the
458
+ growth in wealth over time, because it depends on a consumer price
459
+ index created by bolting end to end a series of numbers that are
460
+ only locally accurate, and that don't include the prices of new
461
+ inventions until they become so common that their prices stabilize.So while we might think it was very much better to live in a world
462
+ with antibiotics or air travel or an electric power grid than
463
+ without, real income statistics calculated in the usual way will
464
+ prove to us that we are only slightly richer for having these things.Another approach would be to ask, if you were going back to the
465
+ year x in a time machine, how much would you have to spend on trade
466
+ goods to make your fortune? For example, if you were going back
467
+ to 1970 it would certainly be less than $500, because the processing
468
+ power you can get for $500 today would have been worth at least
469
+ $150 million in 1970. The function goes asymptotic fairly quickly,
470
+ because for times over a hundred years or so you could get all you
471
+ needed in present-day trash. In 1800 an empty plastic drink bottle
472
+ with a screw top would have seemed a miracle of workmanship.[16]
473
+ Some will say this amounts to the same thing, because the rich
474
+ have better opportunities for education. That's a valid point. It
475
+ is still possible, to a degree, to buy your kids' way into top
476
+ colleges by sending them to private schools that in effect hack the
477
+ college admissions process.According to a 2002 report by the National Center for Education
478
+ Statistics, about 1.7% of American kids attend private, non-sectarian
479
+ schools. At Princeton, 36% of the class of 2007 came from such
480
+ schools. (Interestingly, the number at Harvard is significantly
481
+ lower, about 28%.) Obviously this is a huge loophole. It does at
482
+ least seem to be closing, not widening.Perhaps the designers of admissions processes should take a lesson
483
+ from the example of computer security, and instead of just assuming
484
+ that their system can't be hacked, measure the degree to which it
485
+ is.
PaulGrahamEssays/gba.txt ADDED
@@ -0,0 +1,198 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ April 2004To the popular press, "hacker" means someone who breaks
2
+ into computers. Among programmers it means a good programmer.
3
+ But the two meanings are connected. To programmers,
4
+ "hacker" connotes mastery in the most literal sense: someone
5
+ who can make a computer do what he wants—whether the computer
6
+ wants to or not.To add to the confusion, the noun "hack" also has two senses. It can
7
+ be either a compliment or an insult. It's called a hack when
8
+ you do something in an ugly way. But when you do something
9
+ so clever that you somehow beat the system, that's also
10
+ called a hack. The word is used more often in the former than
11
+ the latter sense, probably because ugly solutions are more
12
+ common than brilliant ones.Believe it or not, the two senses of "hack" are also
13
+ connected. Ugly and imaginative solutions have something in
14
+ common: they both break the rules. And there is a gradual
15
+ continuum between rule breaking that's merely ugly (using
16
+ duct tape to attach something to your bike) and rule breaking
17
+ that is brilliantly imaginative (discarding Euclidean space).Hacking predates computers. When he
18
+ was working on the Manhattan Project, Richard Feynman used to
19
+ amuse himself by breaking into safes containing secret documents.
20
+ This tradition continues today.
21
+ When we were in grad school, a hacker friend of mine who spent too much
22
+ time around MIT had
23
+ his own lock picking kit.
24
+ (He now runs a hedge fund, a not unrelated enterprise.)It is sometimes hard to explain to authorities why one would
25
+ want to do such things.
26
+ Another friend of mine once got in trouble with the government for
27
+ breaking into computers. This had only recently been declared
28
+ a crime, and the FBI found that their usual investigative
29
+ technique didn't work. Police investigation apparently begins with
30
+ a motive. The usual motives are few: drugs, money, sex,
31
+ revenge. Intellectual curiosity was not one of the motives on
32
+ the FBI's list. Indeed, the whole concept seemed foreign to
33
+ them.Those in authority tend to be annoyed by hackers'
34
+ general attitude of disobedience. But that disobedience is
35
+ a byproduct of the qualities that make them good programmers.
36
+ They may laugh at the CEO when he talks in generic corporate
37
+ newspeech, but they also laugh at someone who tells them
38
+ a certain problem can't be solved.
39
+ Suppress one, and you suppress the other.This attitude is sometimes affected. Sometimes young programmers
40
+ notice the eccentricities of eminent hackers and decide to
41
+ adopt some of their own in order to seem smarter.
42
+ The fake version is not merely
43
+ annoying; the prickly attitude of these posers
44
+ can actually slow the process of innovation.But even factoring in their annoying eccentricities,
45
+ the disobedient attitude of hackers is a net win. I wish its
46
+ advantages were better understood.For example, I suspect people in Hollywood are
47
+ simply mystified by
48
+ hackers' attitudes toward copyrights. They are a perennial
49
+ topic of heated discussion on Slashdot.
50
+ But why should people who program computers
51
+ be so concerned about copyrights, of all things?Partly because some companies use mechanisms to prevent
52
+ copying. Show any hacker a lock and his first thought is
53
+ how to pick it. But there is a deeper reason that
54
+ hackers are alarmed by measures like copyrights and patents.
55
+ They see increasingly aggressive measures to protect
56
+ "intellectual property"
57
+ as a threat to the intellectual
58
+ freedom they need to do their job.
59
+ And they are right.It is by poking about inside current technology that
60
+ hackers get ideas for the next generation. No thanks,
61
+ intellectual homeowners may say, we don't need any
62
+ outside help. But they're wrong.
63
+ The next generation of computer technology has
64
+ often—perhaps more often than not—been developed by outsiders.In 1977 there was no doubt some group within IBM developing
65
+ what they expected to be
66
+ the next generation of business computer. They were mistaken.
67
+ The next generation of business computer was
68
+ being developed on entirely different lines by two long-haired
69
+ guys called Steve in a garage in Los Altos. At about the
70
+ same time, the powers that be
71
+ were cooperating to develop the
72
+ official next generation operating system, Multics.
73
+ But two guys who thought Multics excessively complex went off
74
+ and wrote their own. They gave it a name that
75
+ was a joking reference to Multics: Unix.The latest intellectual property laws impose
76
+ unprecedented restrictions on the sort of poking around that
77
+ leads to new ideas. In the past, a competitor might use patents
78
+ to prevent you from selling a copy of something they
79
+ made, but they couldn't prevent you from
80
+ taking one apart to see how it worked. The latest
81
+ laws make this a crime. How are we
82
+ to develop new technology if we can't study current
83
+ technology to figure out how to improve it?Ironically, hackers have brought this on themselves.
84
+ Computers are responsible for the problem. The control systems
85
+ inside machines used to be physical: gears and levers and cams.
86
+ Increasingly, the brains (and thus the value) of products is
87
+ in software. And by this I mean software in the general sense:
88
+ i.e. data. A song on an LP is physically stamped into the
89
+ plastic. A song on an iPod's disk is merely stored on it.Data is by definition easy to copy. And the Internet
90
+ makes copies easy to distribute. So it is no wonder
91
+ companies are afraid. But, as so often happens, fear has
92
+ clouded their judgement. The government has responded
93
+ with draconian laws to protect intellectual property.
94
+ They probably mean well. But
95
+ they may not realize that such laws will do more harm
96
+ than good.Why are programmers so violently opposed to these laws?
97
+ If I were a legislator, I'd be interested in this
98
+ mystery—for the same reason that, if I were a farmer and suddenly
99
+ heard a lot of squawking coming from my hen house one night,
100
+ I'd want to go out and investigate. Hackers are not stupid,
101
+ and unanimity is very rare in this world.
102
+ So if they're all squawking,
103
+ perhaps there is something amiss.Could it be that such laws, though intended to protect America,
104
+ will actually harm it? Think about it. There is something
105
+ very American about Feynman breaking into safes during
106
+ the Manhattan Project. It's hard to imagine the authorities
107
+ having a sense of humor about such things over
108
+ in Germany at that time. Maybe it's not a coincidence.Hackers are unruly. That is the essence of hacking. And it
109
+ is also the essence of Americanness. It is no accident
110
+ that Silicon Valley
111
+ is in America, and not France, or Germany,
112
+ or England, or Japan. In those countries, people color inside
113
+ the lines.I lived for a while in Florence. But after I'd been there
114
+ a few months I realized that what I'd been unconsciously hoping
115
+ to find there was back in the place I'd just left.
116
+ The reason Florence is famous is that in 1450, it was New York.
117
+ In 1450 it was filled with the kind of turbulent and ambitious
118
+ people you find now in America. (So I went back to America.)It is greatly to America's advantage that it is
119
+ a congenial atmosphere for the right sort of unruliness—that
120
+ it is a home not just for the smart, but for smart-alecks.
121
+ And hackers are invariably smart-alecks. If we had a national
122
+ holiday, it would be April 1st. It says a great deal about
123
+ our work that we use the same word for a brilliant or a
124
+ horribly cheesy solution. When we cook one up we're not
125
+ always 100% sure which kind it is. But as long as it has
126
+ the right sort of wrongness, that's a promising sign.
127
+ It's odd that people
128
+ think of programming as precise and methodical. Computers
129
+ are precise and methodical. Hacking is something you do
130
+ with a gleeful laugh.In our world some of the most characteristic solutions
131
+ are not far removed from practical
132
+ jokes. IBM was no doubt rather surprised by the consequences
133
+ of the licensing deal for DOS, just as the hypothetical
134
+ "adversary" must be when Michael Rabin solves a problem by
135
+ redefining it as one that's easier to solve.Smart-alecks have to develop a keen sense of how much they
136
+ can get away with. And lately hackers
137
+ have sensed a change
138
+ in the atmosphere.
139
+ Lately hackerliness seems rather frowned upon.To hackers the recent contraction in civil liberties seems
140
+ especially ominous. That must also mystify outsiders.
141
+ Why should we care especially about civil
142
+ liberties? Why programmers, more than
143
+ dentists or salesmen or landscapers?Let me put the case in terms a government official would appreciate.
144
+ Civil liberties are not just an ornament, or a quaint
145
+ American tradition. Civil liberties make countries rich.
146
+ If you made a graph of
147
+ GNP per capita vs. civil liberties, you'd notice a definite
148
+ trend. Could civil liberties really be a cause, rather
149
+ than just an effect? I think so. I think a society in which
150
+ people can do and say what they want will also tend to
151
+ be one in which the most efficient solutions win, rather than
152
+ those sponsored by the most influential people.
153
+ Authoritarian countries become corrupt;
154
+ corrupt countries become poor; and poor countries are weak.
155
+ It seems to me there is
156
+ a Laffer curve for government power, just as for
157
+ tax revenues. At least, it seems likely enough that it
158
+ would be stupid to try the experiment and find out. Unlike
159
+ high tax rates, you can't repeal totalitarianism if it
160
+ turns out to be a mistake.This is why hackers worry. The government spying on people doesn't
161
+ literally make programmers write worse code. It just leads
162
+ eventually to a world in which bad ideas win. And because
163
+ this is so important to hackers, they're especially sensitive
164
+ to it. They can sense totalitarianism approaching from a
165
+ distance, as animals can sense an approaching
166
+ thunderstorm.It would be ironic if, as hackers fear, recent measures
167
+ intended to protect national security and intellectual property
168
+ turned out to be a missile aimed right at what makes
169
+ America successful. But it would not be the first time that
170
+ measures taken in an atmosphere of panic had
171
+ the opposite of the intended effect.There is such a thing as Americanness.
172
+ There's nothing like living abroad to teach you that.
173
+ And if you want to know whether something will nurture or squash
174
+ this quality, it would be hard to find a better focus
175
+ group than hackers, because they come closest of any group
176
+ I know to embodying it. Closer, probably, than
177
+ the men running our government,
178
+ who for all their talk of patriotism
179
+ remind me more of Richelieu or Mazarin
180
+ than Thomas Jefferson or George Washington.When you read what the founding fathers had to say for
181
+ themselves, they sound more like hackers.
182
+ "The spirit of resistance to government,"
183
+ Jefferson wrote, "is so valuable on certain occasions, that I wish
184
+ it always to be kept alive."Imagine an American president saying that today.
185
+ Like the remarks of an outspoken old grandmother, the sayings of
186
+ the founding fathers have embarrassed generations of
187
+ their less confident successors. They remind us where we come from.
188
+ They remind us that it is the people who break rules that are
189
+ the source of America's wealth and power.Those in a position to impose rules naturally want them to be
190
+ obeyed. But be careful what you ask for. You might get it.Thanks to Ken Anderson, Trevor Blackwell, Daniel Giffin,
191
+ Sarah Harlin, Shiro Kawai, Jessica Livingston, Matz,
192
+ Jackie McDonough, Robert Morris, Eric Raymond, Guido van Rossum,
193
+ David Weinberger, and
194
+ Steven Wolfram for reading drafts of this essay.
195
+ (The image shows Steves Jobs and Wozniak
196
+ with a "blue box."
197
+ Photo by Margret Wozniak. Reproduced by permission of Steve
198
+ Wozniak.)
PaulGrahamEssays/gh.txt ADDED
@@ -0,0 +1,434 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ July 2004(This essay is derived from a talk at Oscon 2004.)
10
+ A few months ago I finished a new
11
+ book,
12
+ and in reviews I keep
13
+ noticing words like "provocative'' and "controversial.'' To say
14
+ nothing of "idiotic.''I didn't mean to make the book controversial. I was trying to make
15
+ it efficient. I didn't want to waste people's time telling them
16
+ things they already knew. It's more efficient just to give them
17
+ the diffs. But I suppose that's bound to yield an alarming book.EdisonsThere's no controversy about which idea is most controversial:
18
+ the suggestion that variation in wealth might not be as big a
19
+ problem as we think.I didn't say in the book that variation in wealth was in itself a
20
+ good thing. I said in some situations it might be a sign of good
21
+ things. A throbbing headache is not a good thing, but it can be
22
+ a sign of a good thing-- for example, that you're recovering
23
+ consciousness after being hit on the head.Variation in wealth can be a sign of variation in productivity.
24
+ (In a society of one, they're identical.) And that
25
+ is almost certainly a good thing: if your society has no variation
26
+ in productivity, it's probably not because everyone is Thomas
27
+ Edison. It's probably because you have no Thomas Edisons.In a low-tech society you don't see much variation in productivity.
28
+ If you have a tribe of nomads collecting sticks for a fire, how
29
+ much more productive is the best stick gatherer going to be than
30
+ the worst? A factor of two? Whereas when you hand people a complex tool
31
+ like a computer, the variation in what they can do with
32
+ it is enormous.That's not a new idea. Fred Brooks wrote about it in 1974, and
33
+ the study he quoted was published in 1968. But I think he
34
+ underestimated the variation between programmers. He wrote about productivity in lines
35
+ of code: the best programmers can solve a given problem in a tenth
36
+ the time. But what if the problem isn't given? In programming, as
37
+ in many fields, the hard part isn't solving problems, but deciding
38
+ what problems to solve. Imagination is hard to measure, but
39
+ in practice it dominates the kind of productivity that's measured
40
+ in lines of code.Productivity varies in any field, but there are few in which it
41
+ varies so much. The variation between programmers
42
+ is so great that it becomes a difference in kind. I don't
43
+ think this is something intrinsic to programming, though. In every field,
44
+ technology magnifies differences in productivity. I think what's
45
+ happening in programming is just that we have a lot of technological
46
+ leverage. But in every field the lever is getting longer, so the
47
+ variation we see is something that more and more fields will see
48
+ as time goes on. And the success of companies, and countries, will
49
+ depend increasingly on how they deal with it.If variation in productivity increases with technology, then the
50
+ contribution of the most productive individuals will not only be
51
+ disproportionately large, but will actually grow with time. When
52
+ you reach the point where 90% of a group's output is created by 1%
53
+ of its members, you lose big if something (whether Viking raids,
54
+ or central planning) drags their productivity down to the average.If we want to get the most out of them, we need to understand these
55
+ especially productive people. What motivates them? What do they
56
+ need to do their jobs? How do you recognize them? How do you
57
+ get them to come and work for you? And then of course there's the
58
+ question, how do you become one?More than MoneyI know a handful of super-hackers, so I sat down and thought about
59
+ what they have in common. Their defining quality is probably that
60
+ they really love to program. Ordinary programmers write code to pay
61
+ the bills. Great hackers think of it as something they do for fun,
62
+ and which they're delighted to find people will pay them for.Great programmers are sometimes said to be indifferent to money.
63
+ This isn't quite true. It is true that all they really care about
64
+ is doing interesting work. But if you make enough money, you get
65
+ to work on whatever you want, and for that reason hackers are
66
+ attracted by the idea of making really large amounts of money.
67
+ But as long as they still have to show up for work every day, they
68
+ care more about what they do there than how much they get paid for
69
+ it.Economically, this is a fact of the greatest importance, because
70
+ it means you don't have to pay great hackers anything like what
71
+ they're worth. A great programmer might be ten or a hundred times
72
+ as productive as an ordinary one, but he'll consider himself lucky
73
+ to get paid three times as much. As I'll explain later, this is
74
+ partly because great hackers don't know how good they are. But
75
+ it's also because money is not the main thing they want.What do hackers want? Like all craftsmen, hackers like good tools.
76
+ In fact, that's an understatement. Good hackers find it unbearable
77
+ to use bad tools. They'll simply refuse to work on projects with
78
+ the wrong infrastructure.At a startup I once worked for, one of the things pinned up on our
79
+ bulletin board was an ad from IBM. It was a picture of an AS400,
80
+ and the headline read, I think, "hackers despise
81
+ it.'' [1]When you decide what infrastructure to use for a project, you're
82
+ not just making a technical decision. You're also making a social
83
+ decision, and this may be the more important of the two. For
84
+ example, if your company wants to write some software, it might
85
+ seem a prudent choice to write it in Java. But when you choose a
86
+ language, you're also choosing a community. The programmers you'll
87
+ be able to hire to work on a Java project won't be as
88
+ smart as the
89
+ ones you could get to work on a project written in Python.
90
+ And the quality of your hackers probably matters more than the
91
+ language you choose. Though, frankly, the fact that good hackers
92
+ prefer Python to Java should tell you something about the relative
93
+ merits of those languages.Business types prefer the most popular languages because they view
94
+ languages as standards. They don't want to bet the company on
95
+ Betamax. The thing about languages, though, is that they're not
96
+ just standards. If you have to move bits over a network, by all
97
+ means use TCP/IP. But a programming language isn't just a format.
98
+ A programming language is a medium of expression.I've read that Java has just overtaken Cobol as the most popular
99
+ language. As a standard, you couldn't wish for more. But as a
100
+ medium of expression, you could do a lot better. Of all the great
101
+ programmers I can think of, I know of only one who would voluntarily
102
+ program in Java. And of all the great programmers I can think of
103
+ who don't work for Sun, on Java, I know of zero.Great hackers also generally insist on using open source software.
104
+ Not just because it's better, but because it gives them more control.
105
+ Good hackers insist on control. This is part of what makes them
106
+ good hackers: when something's broken, they need to fix it. You
107
+ want them to feel this way about the software they're writing for
108
+ you. You shouldn't be surprised when they feel the same way about
109
+ the operating system.A couple years ago a venture capitalist friend told me about a new
110
+ startup he was involved with. It sounded promising. But the next
111
+ time I talked to him, he said they'd decided to build their software
112
+ on Windows NT, and had just hired a very experienced NT developer
113
+ to be their chief technical officer. When I heard this, I thought,
114
+ these guys are doomed. One, the CTO couldn't be a first rate
115
+ hacker, because to become an eminent NT developer he would have
116
+ had to use NT voluntarily, multiple times, and I couldn't imagine
117
+ a great hacker doing that; and two, even if he was good, he'd have
118
+ a hard time hiring anyone good to work for him if the project had
119
+ to be built on NT. [2]The Final FrontierAfter software, the most important tool to a hacker is probably
120
+ his office. Big companies think the function of office space is to express
121
+ rank. But hackers use their offices for more than that: they
122
+ use their office as a place to think in. And if you're a technology
123
+ company, their thoughts are your product. So making hackers work
124
+ in a noisy, distracting environment is like having a paint factory
125
+ where the air is full of soot.The cartoon strip Dilbert has a lot to say about cubicles, and with
126
+ good reason. All the hackers I know despise them. The mere prospect
127
+ of being interrupted is enough to prevent hackers from working on
128
+ hard problems. If you want to get real work done in an office with
129
+ cubicles, you have two options: work at home, or come in early or
130
+ late or on a weekend, when no one else is there. Don't companies
131
+ realize this is a sign that something is broken? An office
132
+ environment is supposed to be something that helps
133
+ you work, not something you work despite.Companies like Cisco are proud that everyone there has a cubicle,
134
+ even the CEO. But they're not so advanced as they think; obviously
135
+ they still view office space as a badge of rank. Note too that
136
+ Cisco is famous for doing very little product development in house.
137
+ They get new technology by buying the startups that created it-- where
138
+ presumably the hackers did have somewhere quiet to work.One big company that understands what hackers need is Microsoft.
139
+ I once saw a recruiting ad for Microsoft with a big picture of a
140
+ door. Work for us, the premise was, and we'll give you a place to
141
+ work where you can actually get work done. And you know, Microsoft
142
+ is remarkable among big companies in that they are able to develop
143
+ software in house. Not well, perhaps, but well enough.If companies want hackers to be productive, they should look at
144
+ what they do at home. At home, hackers can arrange things themselves
145
+ so they can get the most done. And when they work at home, hackers
146
+ don't work in noisy, open spaces; they work in rooms with doors. They
147
+ work in cosy, neighborhoody places with people around and somewhere
148
+ to walk when they need to mull something over, instead of in glass
149
+ boxes set in acres of parking lots. They have a sofa they can take
150
+ a nap on when they feel tired, instead of sitting in a coma at
151
+ their desk, pretending to work. There's no crew of people with
152
+ vacuum cleaners that roars through every evening during the prime
153
+ hacking hours. There are no meetings or, God forbid, corporate
154
+ retreats or team-building exercises. And when you look at what
155
+ they're doing on that computer, you'll find it reinforces what I
156
+ said earlier about tools. They may have to use Java and Windows
157
+ at work, but at home, where they can choose for themselves, you're
158
+ more likely to find them using Perl and Linux.Indeed, these statistics about Cobol or Java being the most popular
159
+ language can be misleading. What we ought to look at, if we want
160
+ to know what tools are best, is what hackers choose when they can
161
+ choose freely-- that is, in projects of their own. When you ask
162
+ that question, you find that open source operating systems already
163
+ have a dominant market share, and the number one language is probably
164
+ Perl.InterestingAlong with good tools, hackers want interesting projects. What
165
+ makes a project interesting? Well, obviously overtly sexy
166
+ applications like stealth planes or special effects software would
167
+ be interesting to work on. But any application can be interesting
168
+ if it poses novel technical challenges. So it's hard to predict
169
+ which problems hackers will like, because some become
170
+ interesting only when the people working on them discover a new
171
+ kind of solution. Before ITA
172
+ (who wrote the software inside Orbitz),
173
+ the people working on airline fare searches probably thought it
174
+ was one of the most boring applications imaginable. But ITA made
175
+ it interesting by
176
+ redefining the problem in a more ambitious way.I think the same thing happened at Google. When Google was founded,
177
+ the conventional wisdom among the so-called portals was that search
178
+ was boring and unimportant. But the guys at Google didn't think
179
+ search was boring, and that's why they do it so well.This is an area where managers can make a difference. Like a parent
180
+ saying to a child, I bet you can't clean up your whole room in
181
+ ten minutes, a good manager can sometimes redefine a problem as a
182
+ more interesting one. Steve Jobs seems to be particularly good at
183
+ this, in part simply by having high standards. There were a lot
184
+ of small, inexpensive computers before the Mac. He redefined the
185
+ problem as: make one that's beautiful. And that probably drove
186
+ the developers harder than any carrot or stick could.They certainly delivered. When the Mac first appeared, you didn't
187
+ even have to turn it on to know it would be good; you could tell
188
+ from the case. A few weeks ago I was walking along the street in
189
+ Cambridge, and in someone's trash I saw what appeared to be a Mac
190
+ carrying case. I looked inside, and there was a Mac SE. I carried
191
+ it home and plugged it in, and it booted. The happy Macintosh
192
+ face, and then the finder. My God, it was so simple. It was just
193
+ like ... Google.Hackers like to work for people with high standards. But it's not
194
+ enough just to be exacting. You have to insist on the right things.
195
+ Which usually means that you have to be a hacker yourself. I've
196
+ seen occasional articles about how to manage programmers. Really
197
+ there should be two articles: one about what to do if
198
+ you are yourself a programmer, and one about what to do if you're not. And the
199
+ second could probably be condensed into two words: give up.The problem is not so much the day to day management. Really good
200
+ hackers are practically self-managing. The problem is, if you're
201
+ not a hacker, you can't tell who the good hackers are. A similar
202
+ problem explains why American cars are so ugly. I call it the
203
+ design paradox. You might think that you could make your products
204
+ beautiful just by hiring a great designer to design them. But if
205
+ you yourself don't have good taste,
206
+ how are you going to recognize
207
+ a good designer? By definition you can't tell from his portfolio.
208
+ And you can't go by the awards he's won or the jobs he's had,
209
+ because in design, as in most fields, those tend to be driven by
210
+ fashion and schmoozing, with actual ability a distant third.
211
+ There's no way around it: you can't manage a process intended to
212
+ produce beautiful things without knowing what beautiful is. American
213
+ cars are ugly because American car companies are run by people with
214
+ bad taste.Many people in this country think of taste as something elusive,
215
+ or even frivolous. It is neither. To drive design, a manager must
216
+ be the most demanding user of a company's products. And if you
217
+ have really good taste, you can, as Steve Jobs does, make satisfying
218
+ you the kind of problem that good people like to work on.Nasty Little ProblemsIt's pretty easy to say what kinds of problems are not interesting:
219
+ those where instead of solving a few big, clear, problems, you have
220
+ to solve a lot of nasty little ones. One of the worst kinds of
221
+ projects is writing an interface to a piece of software that's
222
+ full of bugs. Another is when you have to customize
223
+ something for an individual client's complex and ill-defined needs.
224
+ To hackers these kinds of projects are the death of a thousand
225
+ cuts.The distinguishing feature of nasty little problems is that you
226
+ don't learn anything from them. Writing a compiler is interesting
227
+ because it teaches you what a compiler is. But writing an interface
228
+ to a buggy piece of software doesn't teach you anything, because the
229
+ bugs are random. [3] So it's not just fastidiousness that makes good
230
+ hackers avoid nasty little problems. It's more a question of
231
+ self-preservation. Working on nasty little problems makes you
232
+ stupid. Good hackers avoid it for the same reason models avoid
233
+ cheeseburgers.Of course some problems inherently have this character. And because
234
+ of supply and demand, they pay especially well. So a company that
235
+ found a way to get great hackers to work on tedious problems would
236
+ be very successful. How would you do it?One place this happens is in startups. At our startup we had
237
+ Robert Morris working as a system administrator. That's like having the
238
+ Rolling Stones play at a bar mitzvah. You can't hire that kind of
239
+ talent. But people will do any amount of drudgery for companies
240
+ of which they're the founders. [4]Bigger companies solve the problem by partitioning the company.
241
+ They get smart people to work for them by establishing a separate
242
+ R&D department where employees don't have to work directly on
243
+ customers' nasty little problems. [5] In this model, the research
244
+ department functions like a mine. They produce new ideas; maybe
245
+ the rest of the company will be able to use them.You may not have to go to this extreme.
246
+ Bottom-up programming
247
+ suggests another way to partition the company: have the smart people
248
+ work as toolmakers. If your company makes software to do x, have
249
+ one group that builds tools for writing software of that type, and
250
+ another that uses these tools to write the applications. This way
251
+ you might be able to get smart people to write 99% of your code,
252
+ but still keep them almost as insulated from users as they would
253
+ be in a traditional research department. The toolmakers would have
254
+ users, but they'd only be the company's own developers. [6]If Microsoft used this approach, their software wouldn't be so full
255
+ of security holes, because the less smart people writing the actual
256
+ applications wouldn't be doing low-level stuff like allocating
257
+ memory. Instead of writing Word directly in C, they'd be plugging
258
+ together big Lego blocks of Word-language. (Duplo, I believe, is
259
+ the technical term.)ClumpingAlong with interesting problems, what good hackers like is other
260
+ good hackers. Great hackers tend to clump together-- sometimes
261
+ spectacularly so, as at Xerox Parc. So you won't attract good
262
+ hackers in linear proportion to how good an environment you create
263
+ for them. The tendency to clump means it's more like the square
264
+ of the environment. So it's winner take all. At any given time,
265
+ there are only about ten or twenty places where hackers most want to
266
+ work, and if you aren't one of them, you won't just have fewer
267
+ great hackers, you'll have zero.Having great hackers is not, by itself, enough to make a company
268
+ successful. It works well for Google and ITA, which are two of
269
+ the hot spots right now, but it didn't help Thinking Machines or
270
+ Xerox. Sun had a good run for a while, but their business model
271
+ is a down elevator. In that situation, even the best hackers can't
272
+ save you.I think, though, that all other things being equal, a company that
273
+ can attract great hackers will have a huge advantage. There are
274
+ people who would disagree with this. When we were making the rounds
275
+ of venture capital firms in the 1990s, several told us that software
276
+ companies didn't win by writing great software, but through brand,
277
+ and dominating channels, and doing the right deals.They really seemed to believe this, and I think I know why. I
278
+ think what a lot of VCs are looking for, at least unconsciously,
279
+ is the next Microsoft. And of course if Microsoft is your model,
280
+ you shouldn't be looking for companies that hope to win by writing
281
+ great software. But VCs are mistaken to look for the next Microsoft,
282
+ because no startup can be the next Microsoft unless some other
283
+ company is prepared to bend over at just the right moment and be
284
+ the next IBM.It's a mistake to use Microsoft as a model, because their whole
285
+ culture derives from that one lucky break. Microsoft is a bad data
286
+ point. If you throw them out, you find that good products do tend
287
+ to win in the market. What VCs should be looking for is the next
288
+ Apple, or the next Google.I think Bill Gates knows this. What worries him about Google is
289
+ not the power of their brand, but the fact that they have
290
+ better hackers. [7]
291
+ RecognitionSo who are the great hackers? How do you know when you meet one?
292
+ That turns out to be very hard. Even hackers can't tell. I'm
293
+ pretty sure now that my friend Trevor Blackwell is a great hacker.
294
+ You may have read on Slashdot how he made his
295
+ own Segway. The
296
+ remarkable thing about this project was that he wrote all the
297
+ software in one day (in Python, incidentally).For Trevor, that's
298
+ par for the course. But when I first met him, I thought he was a
299
+ complete idiot. He was standing in Robert Morris's office babbling
300
+ at him about something or other, and I remember standing behind
301
+ him making frantic gestures at Robert to shoo this nut out of his
302
+ office so we could go to lunch. Robert says he misjudged Trevor
303
+ at first too. Apparently when Robert first met him, Trevor had
304
+ just begun a new scheme that involved writing down everything about
305
+ every aspect of his life on a stack of index cards, which he carried
306
+ with him everywhere. He'd also just arrived from Canada, and had
307
+ a strong Canadian accent and a mullet.The problem is compounded by the fact that hackers, despite their
308
+ reputation for social obliviousness, sometimes put a good deal of
309
+ effort into seeming smart. When I was in grad school I used to
310
+ hang around the MIT AI Lab occasionally. It was kind of intimidating
311
+ at first. Everyone there spoke so fast. But after a while I
312
+ learned the trick of speaking fast. You don't have to think any
313
+ faster; just use twice as many words to say everything. With this amount of noise in the signal, it's hard to tell good
314
+ hackers when you meet them. I can't tell, even now. You also
315
+ can't tell from their resumes. It seems like the only way to judge
316
+ a hacker is to work with him on something.And this is the reason that high-tech areas
317
+ only happen around universities. The active ingredient
318
+ here is not so much the professors as the students. Startups grow up
319
+ around universities because universities bring together promising young
320
+ people and make them work on the same projects. The
321
+ smart ones learn who the other smart ones are, and together
322
+ they cook up new projects of their own.Because you can't tell a great hacker except by working with him,
323
+ hackers themselves can't tell how good they are. This is true to
324
+ a degree in most fields. I've found that people who
325
+ are great at something are not so much convinced of their own
326
+ greatness as mystified at why everyone else seems so incompetent.
327
+ But it's particularly hard for hackers to know how good they are,
328
+ because it's hard to compare their work. This is easier in most
329
+ other fields. In the hundred meters, you know in 10 seconds who's
330
+ fastest. Even in math there seems to be a general consensus about
331
+ which problems are hard to solve, and what constitutes a good
332
+ solution. But hacking is like writing. Who can say which of two
333
+ novels is better? Certainly not the authors.With hackers, at least, other hackers can tell. That's because,
334
+ unlike novelists, hackers collaborate on projects. When you get
335
+ to hit a few difficult problems over the net at someone, you learn
336
+ pretty quickly how hard they hit them back. But hackers can't
337
+ watch themselves at work. So if you ask a great hacker how good
338
+ he is, he's almost certain to reply, I don't know. He's not just
339
+ being modest. He really doesn't know.And none of us know, except about people we've actually worked
340
+ with. Which puts us in a weird situation: we don't know who our
341
+ heroes should be. The hackers who become famous tend to become
342
+ famous by random accidents of PR. Occasionally I need to give an
343
+ example of a great hacker, and I never know who to use. The first
344
+ names that come to mind always tend to be people I know personally,
345
+ but it seems lame to use them. So, I think, maybe I should say
346
+ Richard Stallman, or Linus Torvalds, or Alan Kay, or someone famous
347
+ like that. But I have no idea if these guys are great hackers.
348
+ I've never worked with them on anything.If there is a Michael Jordan of hacking, no one knows, including
349
+ him.CultivationFinally, the question the hackers have all been wondering about:
350
+ how do you become a great hacker? I don't know if it's possible
351
+ to make yourself into one. But it's certainly possible to do things
352
+ that make you stupid, and if you can make yourself stupid, you
353
+ can probably make yourself smart too.The key to being a good hacker may be to work on what you like.
354
+ When I think about the great hackers I know, one thing they have
355
+ in common is the extreme
356
+ difficulty of making them work
357
+ on anything they
358
+ don't want to. I don't know if this is cause or effect; it may be
359
+ both.To do something well you have to love it.
360
+ So to the extent you
361
+ can preserve hacking as something you love, you're likely to do it
362
+ well. Try to keep the sense of wonder you had about programming at
363
+ age 14. If you're worried that your current job is rotting your
364
+ brain, it probably is.The best hackers tend to be smart, of course, but that's true in
365
+ a lot of fields. Is there some quality that's unique to hackers?
366
+ I asked some friends, and the number one thing they mentioned was
367
+ curiosity.
368
+ I'd always supposed that all smart people were curious--
369
+ that curiosity was simply the first derivative of knowledge. But
370
+ apparently hackers are particularly curious, especially about how
371
+ things work. That makes sense, because programs are in effect
372
+ giant descriptions of how things work.Several friends mentioned hackers' ability to concentrate-- their
373
+ ability, as one put it, to "tune out everything outside their own
374
+ heads.'' I've certainly noticed this. And I've heard several
375
+ hackers say that after drinking even half a beer they can't program at
376
+ all. So maybe hacking does require some special ability to focus.
377
+ Perhaps great hackers can load a large amount of context into their
378
+ head, so that when they look at a line of code, they see not just
379
+ that line but the whole program around it. John McPhee
380
+ wrote that Bill Bradley's success as a basketball player was due
381
+ partly to his extraordinary peripheral vision. "Perfect'' eyesight
382
+ means about 47 degrees of vertical peripheral vision. Bill Bradley
383
+ had 70; he could see the basket when he was looking at the floor.
384
+ Maybe great hackers have some similar inborn ability. (I cheat by
385
+ using a very dense language,
386
+ which shrinks the court.)This could explain the disconnect over cubicles. Maybe the people
387
+ in charge of facilities, not having any concentration to shatter,
388
+ have no idea that working in a cubicle feels to a hacker like having
389
+ one's brain in a blender. (Whereas Bill, if the rumors of autism
390
+ are true, knows all too well.)One difference I've noticed between great hackers and smart people
391
+ in general is that hackers are more
392
+ politically incorrect. To the
393
+ extent there is a secret handshake among good hackers, it's when they
394
+ know one another well enough to express opinions that would get
395
+ them stoned to death by the general public. And I can see why
396
+ political incorrectness would be a useful quality in programming.
397
+ Programs are very complex and, at least in the hands of good
398
+ programmers, very fluid. In such situations it's helpful to have
399
+ a habit of questioning assumptions.Can you cultivate these qualities? I don't know. But you can at
400
+ least not repress them. So here is my best shot at a recipe. If
401
+ it is possible to make yourself into a great hacker, the way to do
402
+ it may be to make the following deal with yourself: you never have
403
+ to work on boring projects (unless your family will starve otherwise),
404
+ and in return, you'll never allow yourself to do a half-assed job.
405
+ All the great hackers I know seem to have made that deal, though
406
+ perhaps none of them had any choice in the matter.Notes
407
+ [1] In fairness, I have to say that IBM makes decent hardware. I
408
+ wrote this on an IBM laptop.[2] They did turn out to be doomed. They shut down a few months
409
+ later.[3] I think this is what people mean when they talk
410
+ about the "meaning of life." On the face of it, this seems an
411
+ odd idea. Life isn't an expression; how could it have meaning?
412
+ But it can have a quality that feels a lot like meaning. In a project
413
+ like a compiler, you have to solve a lot of problems, but the problems
414
+ all fall into a pattern, as in a signal. Whereas when the problems
415
+ you have to solve are random, they seem like noise.
416
+ [4] Einstein at one point worked designing refrigerators. (He had equity.)[5] It's hard to say exactly what constitutes research in the
417
+ computer world, but as a first approximation, it's software that
418
+ doesn't have users.I don't think it's publication that makes the best hackers want to work
419
+ in research departments. I think it's mainly not having to have a
420
+ three hour meeting with a product manager about problems integrating
421
+ the Korean version of Word 13.27 with the talking paperclip.[6] Something similar has been happening for a long time in the
422
+ construction industry. When you had a house built a couple hundred
423
+ years ago, the local builders built everything in it. But increasingly
424
+ what builders do is assemble components designed and manufactured
425
+ by someone else. This has, like the arrival of desktop publishing,
426
+ given people the freedom to experiment in disastrous ways, but it
427
+ is certainly more efficient.[7] Google is much more dangerous to Microsoft than Netscape was.
428
+ Probably more dangerous than any other company has ever been. Not
429
+ least because they're determined to fight. On their job listing
430
+ page, they say that one of their "core values'' is "Don't be evil.''
431
+ From a company selling soybean oil or mining equipment, such a
432
+ statement would merely be eccentric. But I think all of us in the
433
+ computer world recognize who that is a declaration of war on.Thanks to Jessica Livingston, Robert Morris, and Sarah Harlin
434
+ for reading earlier versions of this talk.
PaulGrahamEssays/goodtaste.txt ADDED
@@ -0,0 +1,86 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ November 2021(This essay is derived from a talk at the Cambridge Union.)When I was a kid, I'd have said there wasn't. My father told me so.
2
+ Some people like some things, and other people like other things,
3
+ and who's to say who's right?It seemed so obvious that there was no such thing as good taste
4
+ that it was only through indirect evidence that I realized my father
5
+ was wrong. And that's what I'm going to give you here: a proof by
6
+ reductio ad absurdum. If we start from the premise that there's no
7
+ such thing as good taste, we end up with conclusions that are
8
+ obviously false, and therefore the premise must be wrong.We'd better start by saying what good taste is. There's a narrow
9
+ sense in which it refers to aesthetic judgements and a broader one
10
+ in which it refers to preferences of any kind. The strongest proof
11
+ would be to show that taste exists in the narrowest sense, so I'm
12
+ going to talk about taste in art. You have better taste than me if
13
+ the art you like is better than the art I like.If there's no such thing as good taste, then there's no such thing
14
+ as good art. Because if there is such a
15
+ thing as good art, it's
16
+ easy to tell which of two people has better taste. Show them a lot
17
+ of works by artists they've never seen before and ask them to
18
+ choose the best, and whoever chooses the better art has better
19
+ taste.So if you want to discard the concept of good taste, you also have
20
+ to discard the concept of good art. And that means you have to
21
+ discard the possibility of people being good at making it. Which
22
+ means there's no way for artists to be good at their jobs. And not
23
+ just visual artists, but anyone who is in any sense an artist. You
24
+ can't have good actors, or novelists, or composers, or dancers
25
+ either. You can have popular novelists, but not good ones.We don't realize how far we'd have to go if we discarded the concept
26
+ of good taste, because we don't even debate the most obvious cases.
27
+ But it doesn't just mean we can't say which of two famous painters
28
+ is better. It means we can't say that any painter is better than a
29
+ randomly chosen eight year old.That was how I realized my father was wrong. I started studying
30
+ painting. And it was just like other kinds of work I'd done: you
31
+ could do it well, or badly, and if you tried hard, you could get
32
+ better at it. And it was obvious that Leonardo and Bellini were
33
+ much better at it than me. That gap between us was not imaginary.
34
+ They were so good. And if they could be good, then art could be
35
+ good, and there was such a thing as good taste after all.Now that I've explained how to show there is such a thing as good
36
+ taste, I should also explain why people think there isn't. There
37
+ are two reasons. One is that there's always so much disagreement
38
+ about taste. Most people's response to art is a tangle of unexamined
39
+ impulses. Is the artist famous? Is the subject attractive? Is this
40
+ the sort of art they're supposed to like? Is it hanging in a famous
41
+ museum, or reproduced in a big, expensive book? In practice most
42
+ people's response to art is dominated by such extraneous factors.And the people who do claim to have good taste are so often mistaken.
43
+ The paintings admired by the so-called experts in one generation
44
+ are often so different from those admired a few generations later.
45
+ It's easy to conclude there's nothing real there at all. It's only
46
+ when you isolate this force, for example by trying to paint and
47
+ comparing your work to Bellini's, that you can see that it does in
48
+ fact exist.The other reason people doubt that art can be good is that there
49
+ doesn't seem to be any room in the art for this goodness. The
50
+ argument goes like this. Imagine several people looking at a work
51
+ of art and judging how good it is. If being good art really is a
52
+ property of objects, it should be in the object somehow. But it
53
+ doesn't seem to be; it seems to be something happening in the heads
54
+ of each of the observers. And if they disagree, how do you choose
55
+ between them?The solution to this puzzle is to realize that the purpose of art
56
+ is to work on its human audience, and humans have a lot in common.
57
+ And to the extent the things an object acts upon respond in the
58
+ same way, that's arguably what it means for the object to have the
59
+ corresponding property. If everything a particle interacts with
60
+ behaves as if the particle had a mass of m, then it has a mass of
61
+ m. So the distinction between "objective" and "subjective" is not
62
+ binary, but a matter of degree, depending on how much the subjects
63
+ have in common. Particles interacting with one another are at one
64
+ pole, but people interacting with art are not all the way at the
65
+ other; their reactions aren't random.Because people's responses to art aren't random, art can be designed
66
+ to operate on people, and be good or bad depending on how effectively
67
+ it does so. Much as a vaccine can be. If someone were talking about
68
+ the ability of a vaccine to confer immunity, it would seem very
69
+ frivolous to object that conferring immunity wasn't really a property
70
+ of vaccines, because acquiring immunity is something that happens
71
+ in the immune system of each individual person. Sure, people's
72
+ immune systems vary, and a vaccine that worked on one might not
73
+ work on another, but that doesn't make it meaningless to talk about
74
+ the effectiveness of a vaccine.The situation with art is messier, of course. You can't measure
75
+ effectiveness by simply taking a vote, as you do with vaccines.
76
+ You have to imagine the responses of subjects with a deep knowledge
77
+ of art, and enough clarity of mind to be able to ignore extraneous
78
+ influences like the fame of the artist. And even then you'd still
79
+ see some disagreement. People do vary, and judging art is hard,
80
+ especially recent art. There is definitely not a total order either
81
+ of works or of people's ability to judge them. But there is equally
82
+ definitely a partial order of both. So while it's not possible to
83
+ have perfect taste, it is possible to have good taste.
84
+ Thanks to the Cambridge Union for inviting me, and to Trevor
85
+ Blackwell, Jessica Livingston, and Robert Morris for reading drafts
86
+ of this.
PaulGrahamEssays/hubs.txt ADDED
@@ -0,0 +1,156 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ October 2011If you look at a list of US cities sorted by population, the number
10
+ of successful startups per capita varies by orders of magnitude.
11
+ Somehow it's as if most places were sprayed with startupicide.I wondered about this for years. I could see the average town was
12
+ like a roach motel for startup ambitions: smart, ambitious people
13
+ went in, but no startups came out. But I was never able to figure
14
+ out exactly what happened inside the motel—exactly what was
15
+ killing all the potential startups.
16
+ [1]A couple weeks ago I finally figured it out. I was framing the
17
+ question wrong. The problem is not that most towns kill startups.
18
+ It's that death is the default for startups,
19
+ and most towns don't save them. Instead of thinking of most places
20
+ as being sprayed with startupicide, it's more accurate to think of
21
+ startups as all being poisoned, and a few places being sprayed with
22
+ the antidote.Startups in other places are just doing what startups naturally do:
23
+ fail. The real question is, what's saving startups in places
24
+ like Silicon Valley?
25
+ [2]EnvironmentI think there are two components to the antidote: being in a place
26
+ where startups are the cool thing to do, and chance meetings with
27
+ people who can help you. And what drives them both is the number
28
+ of startup people around you.The first component is particularly helpful in the first stage of
29
+ a startup's life, when you go from merely having an interest in
30
+ starting a company to actually doing it. It's quite a leap to start
31
+ a startup. It's an unusual thing to do. But in Silicon Valley it
32
+ seems normal.
33
+ [3]In most places, if you start a startup, people treat you as if
34
+ you're unemployed. People in the Valley aren't automatically
35
+ impressed with you just because you're starting a company, but they
36
+ pay attention. Anyone who's been here any amount of time knows not
37
+ to default to skepticism, no matter how inexperienced you seem or
38
+ how unpromising your idea sounds at first, because they've all seen
39
+ inexperienced founders with unpromising sounding ideas who a few
40
+ years later were billionaires.Having people around you care about what you're doing is an
41
+ extraordinarily powerful force. Even the
42
+ most willful people are susceptible to it. About a year after we
43
+ started Y Combinator I said something to a partner at a well known
44
+ VC firm that gave him the (mistaken) impression I was considering
45
+ starting another startup. He responded so eagerly that for about
46
+ half a second I found myself considering doing it.In most other cities, the prospect of starting a startup just doesn't
47
+ seem real. In the Valley it's not only real but fashionable. That
48
+ no doubt causes a lot of people to start startups who shouldn't.
49
+ But I think that's ok. Few people are suited to running a startup,
50
+ and it's very hard to predict beforehand which are (as I know all
51
+ too well from being in the business of trying to predict beforehand),
52
+ so lots of people starting startups who shouldn't is probably the
53
+ optimal state of affairs. As long as you're at a point in your
54
+ life when you can bear the risk of failure, the best way to find
55
+ out if you're suited to running a startup is to try
56
+ it.ChanceThe second component of the antidote is chance meetings with people
57
+ who can help you. This force works in both phases: both in the
58
+ transition from the desire to start a startup to starting one, and
59
+ the transition from starting a company to succeeding. The power
60
+ of chance meetings is more variable than people around you caring
61
+ about startups, which is like a sort of background radiation that
62
+ affects everyone equally, but at its strongest it is far stronger.Chance meetings produce miracles to compensate for the disasters
63
+ that characteristically befall startups. In the Valley, terrible
64
+ things happen to startups all the time, just like they do to startups
65
+ everywhere. The reason startups are more likely to make it here
66
+ is that great things happen to them too. In the Valley, lightning
67
+ has a sign bit.For example, you start a site for college students and you decide
68
+ to move to the Valley for the summer to work on it. And then on a
69
+ random suburban street in Palo Alto you happen to run into Sean
70
+ Parker, who understands the domain really well because he started
71
+ a similar startup himself, and also knows all the investors. And
72
+ moreover has advanced views, for 2004, on founders retaining control of their companies.You can't say precisely what the miracle will be, or even for sure
73
+ that one will happen. The best one can say is: if you're in a
74
+ startup hub, unexpected good things will probably happen to you,
75
+ especially if you deserve them.I bet this is true even for startups we fund. Even with us working
76
+ to make things happen for them on purpose rather than by accident,
77
+ the frequency of helpful chance meetings in the Valley is so high
78
+ that it's still a significant increment on what we can deliver.Chance meetings play a role like the role relaxation plays in having
79
+ ideas. Most people have had the experience of working hard on some
80
+ problem, not being able to solve it, giving up and going to bed,
81
+ and then thinking of the answer in the shower in the morning. What
82
+ makes the answer appear is letting your thoughts drift a bit—and thus drift off the wrong
83
+ path you'd been pursuing last night and onto the right one adjacent
84
+ to it.Chance meetings let your acquaintance drift in the same way taking
85
+ a shower lets your thoughts drift. The critical thing in both cases
86
+ is that they drift just the right amount. The meeting between Larry
87
+ Page and Sergey Brin was a good example. They let their acquaintance
88
+ drift, but only a little; they were both meeting someone they had
89
+ a lot in common with.For Larry Page the most important component of the antidote was
90
+ Sergey Brin, and vice versa. The antidote is
91
+ people. It's not the
92
+ physical infrastructure of Silicon Valley that makes it work, or
93
+ the weather, or anything like that. Those helped get it started,
94
+ but now that the reaction is self-sustaining what drives it is the
95
+ people.Many observers have noticed that one of the most distinctive things
96
+ about startup hubs is the degree to which people help one another
97
+ out, with no expectation of getting anything in return. I'm not
98
+ sure why this is so. Perhaps it's because startups are less of a
99
+ zero sum game than most types of business; they are rarely killed
100
+ by competitors. Or perhaps it's because so many startup founders
101
+ have backgrounds in the sciences, where collaboration is encouraged.A large part of YC's function is to accelerate that process. We're
102
+ a sort of Valley within the Valley, where the density of people
103
+ working on startups and their willingness to help one another are
104
+ both artificially amplified.NumbersBoth components of the antidote—an environment that encourages
105
+ startups, and chance meetings with people who help you—are
106
+ driven by the same underlying cause: the number of startup people
107
+ around you. To make a startup hub, you need a lot of people
108
+ interested in startups.There are three reasons. The first, obviously, is that if you don't
109
+ have enough density, the chance meetings don't happen.
110
+ [4]
111
+ The second is that different startups need such different things, so
112
+ you need a lot of people to supply each startup with what they need
113
+ most. Sean Parker was exactly what Facebook needed in 2004. Another
114
+ startup might have needed a database guy, or someone with connections
115
+ in the movie business.This is one of the reasons we fund such a large number of companies,
116
+ incidentally. The bigger the community, the greater the chance it
117
+ will contain the person who has that one thing you need most.The third reason you need a lot of people to make a startup hub is
118
+ that once you have enough people interested in the same problem,
119
+ they start to set the social norms. And it is a particularly
120
+ valuable thing when the atmosphere around you encourages you to do
121
+ something that would otherwise seem too ambitious. In most places
122
+ the atmosphere pulls you back toward the mean.I flew into the Bay Area a few days ago. I notice this every time
123
+ I fly over the Valley: somehow you can sense something is going on.
124
+ Obviously you can sense prosperity in how well kept a
125
+ place looks. But there are different kinds of prosperity. Silicon
126
+ Valley doesn't look like Boston, or New York, or LA, or DC. I tried
127
+ asking myself what word I'd use to describe the feeling the Valley
128
+ radiated, and the word that came to mind was optimism.Notes[1]
129
+ I'm not saying it's impossible to succeed in a city with few
130
+ other startups, just harder. If you're sufficiently good at
131
+ generating your own morale, you can survive without external
132
+ encouragement. Wufoo was based in Tampa and they succeeded. But
133
+ the Wufoos are exceptionally disciplined.[2]
134
+ Incidentally, this phenomenon is not limited to startups. Most
135
+ unusual ambitions fail, unless the person who has them manages to
136
+ find the right sort of community.[3]
137
+ Starting a company is common, but starting a startup is rare.
138
+ I've talked about the distinction between the two elsewhere, but
139
+ essentially a startup is a new business designed for scale. Most
140
+ new businesses are service businesses and except in rare cases those
141
+ don't scale.[4]
142
+ As I was writing this, I had a demonstration of the density of
143
+ startup people in the Valley. Jessica and I bicycled to University
144
+ Ave in Palo Alto to have lunch at the fabulous Oren's Hummus. As
145
+ we walked in, we met Charlie Cheever sitting near the door. Selina
146
+ Tobaccowala stopped to say hello on her way out. Then Josh Wilson
147
+ came in to pick up a take out order. After lunch we went to get
148
+ frozen yogurt. On the way we met Rajat Suri. When we got to the
149
+ yogurt place, we found Dave Shen there, and as we walked out we ran
150
+ into Yuri Sagalov. We walked with him for a block or so and we ran
151
+ into Muzzammil Zaveri, and then a block later we met Aydin Senkut.
152
+ This is everyday life in Palo Alto. I wasn't trying to meet people;
153
+ I was just having lunch. And I'm sure for every startup founder
154
+ or investor I saw that I knew, there were 5 more I didn't. If Ron
155
+ Conway had been with us he would have met 30 people he knew.Thanks to Sam Altman, Paul Buchheit, Jessica Livingston, and
156
+ Harj Taggar for reading drafts of this.
PaulGrahamEssays/iflisp.txt ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2003If Lisp is so great, why don't more people use it? I was
2
+ asked this question by a student in the audience at a
3
+ talk I gave recently. Not for the first time, either.In languages, as in so many things, there's not much
4
+ correlation between popularity and quality. Why does
5
+ John Grisham (King of Torts sales rank, 44) outsell
6
+ Jane Austen (Pride and Prejudice sales rank, 6191)?
7
+ Would even Grisham claim that it's because he's a better
8
+ writer?Here's the first sentence of Pride and Prejudice:
9
+
10
+ It is a truth universally acknowledged, that a single man
11
+ in possession of a good fortune must be in want of a
12
+ wife.
13
+
14
+ "It is a truth universally acknowledged?" Long words for
15
+ the first sentence of a love story.Like Jane Austen, Lisp looks hard. Its syntax, or lack
16
+ of syntax, makes it look completely unlike
17
+ the languages
18
+ most people are used to. Before I learned Lisp, I was afraid
19
+ of it too. I recently came across a notebook from 1983
20
+ in which I'd written:
21
+
22
+ I suppose I should learn Lisp, but it seems so foreign.
23
+
24
+ Fortunately, I was 19 at the time and not too resistant to learning
25
+ new things. I was so ignorant that learning
26
+ almost anything meant learning new things.People frightened by Lisp make up other reasons for not
27
+ using it. The standard
28
+ excuse, back when C was the default language, was that Lisp
29
+ was too slow. Now that Lisp dialects are among
30
+ the faster
31
+ languages available, that excuse has gone away.
32
+ Now the standard excuse is openly circular: that other languages
33
+ are more popular.(Beware of such reasoning. It gets you Windows.)Popularity is always self-perpetuating, but it's especially
34
+ so in programming languages. More libraries
35
+ get written for popular languages, which makes them still
36
+ more popular. Programs often have to work with existing programs,
37
+ and this is easier if they're written in the same language,
38
+ so languages spread from program to program like a virus.
39
+ And managers prefer popular languages, because they give them
40
+ more leverage over developers, who can more easily be replaced.Indeed, if programming languages were all more or less equivalent,
41
+ there would be little justification for using any but the most
42
+ popular. But they aren't all equivalent, not by a long
43
+ shot. And that's why less popular languages, like Jane Austen's
44
+ novels, continue to survive at all. When everyone else is reading
45
+ the latest John Grisham novel, there will always be a few people
46
+ reading Jane Austen instead.
PaulGrahamEssays/island.txt ADDED
@@ -0,0 +1,55 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ July 2006I've discovered a handy test for figuring out what you're addicted
2
+ to. Imagine you were going to spend the weekend at a friend's house
3
+ on a little island off the coast of Maine. There are no shops on
4
+ the island and you won't be able to leave while you're there. Also,
5
+ you've never been to this house before, so you can't assume it will
6
+ have more than any house might.What, besides clothes and toiletries, do you make a point of packing?
7
+ That's what you're addicted to. For example, if you find yourself
8
+ packing a bottle of vodka (just in case), you may want to stop and
9
+ think about that.For me the list is four things: books, earplugs, a notebook, and a
10
+ pen.There are other things I might bring if I thought of it, like music,
11
+ or tea, but I can live without them. I'm not so addicted to caffeine
12
+ that I wouldn't risk the house not having any tea, just for a
13
+ weekend.Quiet is another matter. I realize it seems a bit eccentric to
14
+ take earplugs on a trip to an island off the coast of Maine. If
15
+ anywhere should be quiet, that should. But what if the person in
16
+ the next room snored? What if there was a kid playing basketball?
17
+ (Thump, thump, thump... thump.) Why risk it? Earplugs are small.Sometimes I can think with noise. If I already have momentum on
18
+ some project, I can work in noisy places. I can edit an essay or
19
+ debug code in an airport. But airports are not so bad: most of the
20
+ noise is whitish. I couldn't work with the sound of a sitcom coming
21
+ through the wall, or a car in the street playing thump-thump music.And of course there's another kind of thinking, when you're starting
22
+ something new, that requires complete quiet. You never
23
+ know when this will strike. It's just as well to carry plugs.The notebook and pen are professional equipment, as it were. Though
24
+ actually there is something druglike about them, in the sense that
25
+ their main purpose is to make me feel better. I hardly ever go
26
+ back and read stuff I write down in notebooks. It's just that if
27
+ I can't write things down, worrying about remembering one idea gets
28
+ in the way of having the next. Pen and paper wick ideas.The best notebooks I've found are made by a company called Miquelrius.
29
+ I use their smallest size, which is about 2.5 x 4 in.
30
+ The secret to writing on such
31
+ narrow pages is to break words only when you run out of space, like
32
+ a Latin inscription. I use the cheapest plastic Bic ballpoints,
33
+ partly because their gluey ink doesn't seep through pages, and
34
+ partly so I don't worry about losing them.I only started carrying a notebook about three years ago. Before
35
+ that I used whatever scraps of paper I could find. But the problem
36
+ with scraps of paper is that they're not ordered. In a notebook
37
+ you can guess what a scribble means by looking at the pages
38
+ around it. In the scrap era I was constantly finding notes I'd
39
+ written years before that might say something I needed to remember,
40
+ if I could only figure out what.As for books, I know the house would probably have something to
41
+ read. On the average trip I bring four books and only read one of
42
+ them, because I find new books to read en route. Really bringing
43
+ books is insurance.I realize this dependence on books is not entirely good—that what
44
+ I need them for is distraction. The books I bring on trips are
45
+ often quite virtuous, the sort of stuff that might be assigned
46
+ reading in a college class. But I know my motives aren't virtuous.
47
+ I bring books because if the world gets boring I need to be able
48
+ to slip into another distilled by some writer. It's like eating
49
+ jam when you know you should be eating fruit.There is a point where I'll do without books. I was walking in
50
+ some steep mountains once, and decided I'd rather just think, if I
51
+ was bored, rather than carry a single unnecessary ounce. It wasn't
52
+ so bad. I found I could entertain myself by having ideas instead
53
+ of reading other people's. If you stop eating jam, fruit starts
54
+ to taste better.So maybe I'll try not bringing books on some future trip. They're
55
+ going to have to pry the plugs out of my cold, dead ears, however.
PaulGrahamEssays/know.txt ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ December 2014I've read Villehardouin's chronicle of the Fourth Crusade at least
2
+ two times, maybe three. And yet if I had to write down everything
3
+ I remember from it, I doubt it would amount to much more than a
4
+ page. Multiply this times several hundred, and I get an uneasy
5
+ feeling when I look at my bookshelves. What use is it to read all
6
+ these books if I remember so little from them?A few months ago, as I was reading Constance Reid's excellent
7
+ biography of Hilbert, I figured out if not the answer to this
8
+ question, at least something that made me feel better about it.
9
+ She writes:
10
+
11
+ Hilbert had no patience with mathematical lectures which filled
12
+ the students with facts but did not teach them how to frame a
13
+ problem and solve it. He often used to tell them that "a perfect
14
+ formulation of a problem is already half its solution."
15
+
16
+ That has always seemed to me an important point, and I was even
17
+ more convinced of it after hearing it confirmed by Hilbert.But how had I come to believe in this idea in the first place? A
18
+ combination of my own experience and other things I'd read. None
19
+ of which I could at that moment remember! And eventually I'd forget
20
+ that Hilbert had confirmed it too. But my increased belief in the
21
+ importance of this idea would remain something I'd learned from
22
+ this book, even after I'd forgotten I'd learned it.Reading and experience train your model of the world. And even if
23
+ you forget the experience or what you read, its effect on your model
24
+ of the world persists. Your mind is like a compiled program you've
25
+ lost the source of. It works, but you don't know why.The place to look for what I learned from Villehardouin's chronicle
26
+ is not what I remember from it, but my mental models of the crusades,
27
+ Venice, medieval culture, siege warfare, and so on. Which doesn't
28
+ mean I couldn't have read more attentively, but at least the harvest
29
+ of reading is not so miserably small as it might seem.This is one of those things that seem obvious in retrospect. But
30
+ it was a surprise to me and presumably would be to anyone else who
31
+ felt uneasy about (apparently) forgetting so much they'd read.Realizing it does more than make you feel a little better about
32
+ forgetting, though. There are specific implications.For example, reading and experience are usually "compiled" at the
33
+ time they happen, using the state of your brain at that time. The
34
+ same book would get compiled differently at different points in
35
+ your life. Which means it is very much worth reading important
36
+ books multiple times. I always used to feel some misgivings about
37
+ rereading books. I unconsciously lumped reading together with work
38
+ like carpentry, where having to do something again is a sign you
39
+ did it wrong the first time. Whereas now the phrase "already read"
40
+ seems almost ill-formed.Intriguingly, this implication isn't limited to books. Technology
41
+ will increasingly make it possible to relive our experiences. When
42
+ people do that today it's usually to enjoy them again (e.g. when
43
+ looking at pictures of a trip) or to find the origin of some bug in
44
+ their compiled code (e.g. when Stephen Fry succeeded in remembering
45
+ the childhood trauma that prevented him from singing). But as
46
+ technologies for recording and playing back your life improve, it
47
+ may become common for people to relive experiences without any goal
48
+ in mind, simply to learn from them again as one might when rereading
49
+ a book.Eventually we may be able not just to play back experiences but
50
+ also to index and even edit them. So although not knowing how you
51
+ know things may seem part of being human, it may not be.
52
+ Thanks to Sam Altman, Jessica Livingston, and Robert Morris for reading
53
+ drafts of this.
PaulGrahamEssays/langdes.txt ADDED
@@ -0,0 +1,242 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2001
2
+
3
+ (These are some notes I made
4
+ for a panel discussion on programming language design
5
+ at MIT on May 10, 2001.)1. Programming Languages Are for People.Programming languages
6
+ are how people talk to computers. The computer would be just as
7
+ happy speaking any language that was unambiguous. The reason we
8
+ have high level languages is because people can't deal with
9
+ machine language. The point of programming
10
+ languages is to prevent our poor frail human brains from being
11
+ overwhelmed by a mass of detail.Architects know that some kinds of design problems are more personal
12
+ than others. One of the cleanest, most abstract design problems
13
+ is designing bridges. There your job is largely a matter of spanning
14
+ a given distance with the least material. The other end of the
15
+ spectrum is designing chairs. Chair designers have to spend their
16
+ time thinking about human butts.Software varies in the same way. Designing algorithms for routing
17
+ data through a network is a nice, abstract problem, like designing
18
+ bridges. Whereas designing programming languages is like designing
19
+ chairs: it's all about dealing with human weaknesses.Most of us hate to acknowledge this. Designing systems of great
20
+ mathematical elegance sounds a lot more appealing to most of us
21
+ than pandering to human weaknesses. And there is a role for mathematical
22
+ elegance: some kinds of elegance make programs easier to understand.
23
+ But elegance is not an end in itself.And when I say languages have to be designed to suit human weaknesses,
24
+ I don't mean that languages have to be designed for bad programmers.
25
+ In fact I think you ought to design for the
26
+ best programmers, but
27
+ even the best programmers have limitations. I don't think anyone
28
+ would like programming in a language where all the variables were
29
+ the letter x with integer subscripts.2. Design for Yourself and Your Friends.If you look at the history of programming languages, a lot of the best
30
+ ones were languages designed for their own authors to use, and a
31
+ lot of the worst ones were designed for other people to use.When languages are designed for other people, it's always a specific
32
+ group of other people: people not as smart as the language designer.
33
+ So you get a language that talks down to you. Cobol is the most
34
+ extreme case, but a lot of languages are pervaded by this spirit.It has nothing to do with how abstract the language is. C is pretty
35
+ low-level, but it was designed for its authors to use, and that's
36
+ why hackers like it.The argument for designing languages for bad programmers is that
37
+ there are more bad programmers than good programmers. That may be
38
+ so. But those few good programmers write a disproportionately
39
+ large percentage of the software.I'm interested in the question, how do you design a language that
40
+ the very best hackers will like? I happen to think this is
41
+ identical to the question, how do you design a good programming
42
+ language?, but even if it isn't, it is at least an interesting
43
+ question.3. Give the Programmer as Much Control as Possible.Many languages
44
+ (especially the ones designed for other people) have the attitude
45
+ of a governess: they try to prevent you from
46
+ doing things that they think aren't good for you. I like the
47
+ opposite approach: give the programmer as much
48
+ control as you can.When I first learned Lisp, what I liked most about it was
49
+ that it considered me an equal partner. In the other languages
50
+ I had learned up till then, there was the language and there was my
51
+ program, written in the language, and the two were very separate.
52
+ But in Lisp the functions and macros I wrote were just like those
53
+ that made up the language itself. I could rewrite the language
54
+ if I wanted. It had the same appeal as open-source software.4. Aim for Brevity.Brevity is underestimated and even scorned.
55
+ But if you look into the hearts of hackers, you'll see that they
56
+ really love it. How many times have you heard hackers speak fondly
57
+ of how in, say, APL, they could do amazing things with just a couple
58
+ lines of code? I think anything that really smart people really
59
+ love is worth paying attention to.I think almost anything
60
+ you can do to make programs shorter is good. There should be lots
61
+ of library functions; anything that can be implicit should be;
62
+ the syntax should be terse to a fault; even the names of things
63
+ should be short.And it's not only programs that should be short. The manual should
64
+ be thin as well. A good part of manuals is taken up with clarifications
65
+ and reservations and warnings and special cases. If you force
66
+ yourself to shorten the manual, in the best case you do it by fixing
67
+ the things in the language that required so much explanation.5. Admit What Hacking Is.A lot of people wish that hacking was
68
+ mathematics, or at least something like a natural science. I think
69
+ hacking is more like architecture. Architecture is
70
+ related to physics, in the sense that architects have to design
71
+ buildings that don't fall down, but the actual goal of architects
72
+ is to make great buildings, not to make discoveries about statics.What hackers like to do is make great programs.
73
+ And I think, at least in our own minds, we have to remember that it's
74
+ an admirable thing to write great programs, even when this work
75
+ doesn't translate easily into the conventional intellectual
76
+ currency of research papers. Intellectually, it is just as
77
+ worthwhile to design a language programmers will love as it is to design a
78
+ horrible one that embodies some idea you can publish a paper
79
+ about.1. How to Organize Big Libraries?Libraries are becoming an
80
+ increasingly important component of programming languages. They're
81
+ also getting bigger, and this can be dangerous. If it takes longer
82
+ to find the library function that will do what you want than it
83
+ would take to write it yourself, then all that code is doing nothing
84
+ but make your manual thick. (The Symbolics manuals were a case in
85
+ point.) So I think we will have to work on ways to organize
86
+ libraries. The ideal would be to design them so that the programmer
87
+ could guess what library call would do the right thing.2. Are People Really Scared of Prefix Syntax?This is an open
88
+ problem in the sense that I have wondered about it for years and
89
+ still don't know the answer. Prefix syntax seems perfectly natural
90
+ to me, except possibly for math. But it could be that a lot of
91
+ Lisp's unpopularity is simply due to having an unfamiliar syntax.
92
+ Whether to do anything about it, if it is true, is another question.
93
+
94
+ 3. What Do You Need for Server-Based Software?
95
+
96
+ I think a lot of the most exciting new applications that get written
97
+ in the next twenty years will be Web-based applications, meaning
98
+ programs that sit on the server and talk to you through a Web
99
+ browser. And to write these kinds of programs we may need some
100
+ new things.One thing we'll need is support for the new way that server-based
101
+ apps get released. Instead of having one or two big releases a
102
+ year, like desktop software, server-based apps get released as a
103
+ series of small changes. You may have as many as five or ten
104
+ releases a day. And as a rule everyone will always use the latest
105
+ version.You know how you can design programs to be debuggable?
106
+ Well, server-based software likewise has to be designed to be
107
+ changeable. You have to be able to change it easily, or at least
108
+ to know what is a small change and what is a momentous one.Another thing that might turn out to be useful for server based
109
+ software, surprisingly, is continuations. In Web-based software
110
+ you can use something like continuation-passing style to get the
111
+ effect of subroutines in the inherently
112
+ stateless world of a Web
113
+ session. Maybe it would be worthwhile having actual continuations,
114
+ if it was not too expensive.4. What New Abstractions Are Left to Discover?I'm not sure how
115
+ reasonable a hope this is, but one thing I would really love to
116
+ do, personally, is discover a new abstraction-- something that would
117
+ make as much of a difference as having first class functions or
118
+ recursion or even keyword parameters. This may be an impossible
119
+ dream. These things don't get discovered that often. But I am always
120
+ looking.1. You Can Use Whatever Language You Want.Writing application
121
+ programs used to mean writing desktop software. And in desktop
122
+ software there is a big bias toward writing the application in the
123
+ same language as the operating system. And so ten years ago,
124
+ writing software pretty much meant writing software in C.
125
+ Eventually a tradition evolved:
126
+ application programs must not be written in unusual languages.
127
+ And this tradition had so long to develop that nontechnical people
128
+ like managers and venture capitalists also learned it.Server-based software blows away this whole model. With server-based
129
+ software you can use any language you want. Almost nobody understands
130
+ this yet (especially not managers and venture capitalists).
131
+ A few hackers understand it, and that's why we even hear
132
+ about new, indy languages like Perl and Python. We're not hearing
133
+ about Perl and Python because people are using them to write Windows
134
+ apps.What this means for us, as people interested in designing programming
135
+ languages, is that there is now potentially an actual audience for
136
+ our work.2. Speed Comes from Profilers.Language designers, or at least
137
+ language implementors, like to write compilers that generate fast
138
+ code. But I don't think this is what makes languages fast for users.
139
+ Knuth pointed out long ago that speed only matters in a few critical
140
+ bottlenecks. And anyone who's tried it knows that you can't guess
141
+ where these bottlenecks are. Profilers are the answer.Language designers are solving the wrong problem. Users don't need
142
+ benchmarks to run fast. What they need is a language that can show
143
+ them what parts of their own programs need to be rewritten. That's
144
+ where speed comes from in practice. So maybe it would be a net
145
+ win if language implementors took half the time they would
146
+ have spent doing compiler optimizations and spent it writing a
147
+ good profiler instead.3. You Need an Application to Drive the Design of a Language.This may not be an absolute rule, but it seems like the best languages
148
+ all evolved together with some application they were being used to
149
+ write. C was written by people who needed it for systems programming.
150
+ Lisp was developed partly to do symbolic differentiation, and
151
+ McCarthy was so eager to get started that he was writing differentiation
152
+ programs even in the first paper on Lisp, in 1960.It's especially good if your application solves some new problem.
153
+ That will tend to drive your language to have new features that
154
+ programmers need. I personally am interested in writing
155
+ a language that will be good for writing server-based applications.[During the panel, Guy Steele also made this point, with the
156
+ additional suggestion that the application should not consist of
157
+ writing the compiler for your language, unless your language
158
+ happens to be intended for writing compilers.]4. A Language Has to Be Good for Writing Throwaway Programs.You know what a throwaway program is: something you write quickly for
159
+ some limited task. I think if you looked around you'd find that
160
+ a lot of big, serious programs started as throwaway programs. I
161
+ would not be surprised if most programs started as throwaway
162
+ programs. And so if you want to make a language that's good for
163
+ writing software in general, it has to be good for writing throwaway
164
+ programs, because that is the larval stage of most software.5. Syntax Is Connected to Semantics.It's traditional to think of
165
+ syntax and semantics as being completely separate. This will
166
+ sound shocking, but it may be that they aren't.
167
+ I think that what you want in your language may be related
168
+ to how you express it.I was talking recently to Robert Morris, and he pointed out that
169
+ operator overloading is a bigger win in languages with infix
170
+ syntax. In a language with prefix syntax, any function you define
171
+ is effectively an operator. If you want to define a plus for a
172
+ new type of number you've made up, you can just define a new function
173
+ to add them. If you do that in a language with infix syntax,
174
+ there's a big difference in appearance between the use of an
175
+ overloaded operator and a function call.1. New Programming Languages.Back in the 1970s
176
+ it was fashionable to design new programming languages. Recently
177
+ it hasn't been. But I think server-based software will make new
178
+ languages fashionable again. With server-based software, you can
179
+ use any language you want, so if someone does design a language that
180
+ actually seems better than others that are available, there will be
181
+ people who take a risk and use it.2. Time-Sharing.Richard Kelsey gave this as an idea whose time
182
+ has come again in the last panel, and I completely agree with him.
183
+ My guess (and Microsoft's guess, it seems) is that much computing
184
+ will move from the desktop onto remote servers. In other words,
185
+ time-sharing is back. And I think there will need to be support
186
+ for it at the language level. For example, I know that Richard
187
+ and Jonathan Rees have done a lot of work implementing process
188
+ scheduling within Scheme 48.3. Efficiency.Recently it was starting to seem that computers
189
+ were finally fast enough. More and more we were starting to hear
190
+ about byte code, which implies to me at least that we feel we have
191
+ cycles to spare. But I don't think we will, with server-based
192
+ software. Someone is going to have to pay for the servers that
193
+ the software runs on, and the number of users they can support per
194
+ machine will be the divisor of their capital cost.So I think efficiency will matter, at least in computational
195
+ bottlenecks. It will be especially important to do i/o fast,
196
+ because server-based applications do a lot of i/o.It may turn out that byte code is not a win, in the end. Sun and
197
+ Microsoft seem to be facing off in a kind of a battle of the byte
198
+ codes at the moment. But they're doing it because byte code is a
199
+ convenient place to insert themselves into the process, not because
200
+ byte code is in itself a good idea. It may turn out that this
201
+ whole battleground gets bypassed. That would be kind of amusing.1. Clients.This is just a guess, but my guess is that
202
+ the winning model for most applications will be purely server-based.
203
+ Designing software that works on the assumption that everyone will
204
+ have your client is like designing a society on the assumption that
205
+ everyone will just be honest. It would certainly be convenient, but
206
+ you have to assume it will never happen.I think there will be a proliferation of devices that have some
207
+ kind of Web access, and all you'll be able to assume about them is
208
+ that they can support simple html and forms. Will you have a
209
+ browser on your cell phone? Will there be a phone in your palm
210
+ pilot? Will your blackberry get a bigger screen? Will you be able
211
+ to browse the Web on your gameboy? Your watch? I don't know.
212
+ And I don't have to know if I bet on
213
+ everything just being on the server. It's
214
+ just so much more robust to have all the
215
+ brains on the server.2. Object-Oriented Programming.I realize this is a
216
+ controversial one, but I don't think object-oriented programming
217
+ is such a big deal. I think it is a fine model for certain kinds
218
+ of applications that need that specific kind of data structure,
219
+ like window systems, simulations, and cad programs. But I don't
220
+ see why it ought to be the model for all programming.I think part of the reason people in big companies like object-oriented
221
+ programming is because it yields a lot of what looks like work.
222
+ Something that might naturally be represented as, say, a list of
223
+ integers, can now be represented as a class with all kinds of
224
+ scaffolding and hustle and bustle.Another attraction of
225
+ object-oriented programming is that methods give you some of the
226
+ effect of first class functions. But this is old news to Lisp
227
+ programmers. When you have actual first class functions, you can
228
+ just use them in whatever way is appropriate to the task at hand,
229
+ instead of forcing everything into a mold of classes and methods.What this means for language design, I think, is that you shouldn't
230
+ build object-oriented programming in too deeply. Maybe the
231
+ answer is to offer more general, underlying stuff, and let people design
232
+ whatever object systems they want as libraries.3. Design by Committee.Having your language designed by a committee is a big pitfall,
233
+ and not just for the reasons everyone knows about. Everyone
234
+ knows that committees tend to yield lumpy, inconsistent designs.
235
+ But I think a greater danger is that they won't take risks.
236
+ When one person is in charge he can take risks
237
+ that a committee would never agree on.Is it necessary to take risks to design a good language though?
238
+ Many people might suspect
239
+ that language design is something where you should stick fairly
240
+ close to the conventional wisdom. I bet this isn't true.
241
+ In everything else people do, reward is proportionate to risk.
242
+ Why should language design be any different?
PaulGrahamEssays/laundry.txt ADDED
@@ -0,0 +1,487 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ October 2004
2
+ As E. B. White said, "good writing is rewriting." I didn't
3
+ realize this when I was in school. In writing, as in math and
4
+ science, they only show you the finished product.
5
+ You don't see all the false starts. This gives students a
6
+ misleading view of how things get made.Part of the reason it happens is that writers don't want
7
+ people to see their mistakes. But I'm willing to let people
8
+ see an early draft if it will show how much you have
9
+ to rewrite to beat an essay into shape.Below is the oldest version I can find of
10
+ The Age of the Essay
11
+ (probably the second or third day), with
12
+ text that ultimately survived in
13
+ red and text that later
14
+ got deleted in gray.
15
+ There seem to be several categories of cuts: things I got wrong,
16
+ things that seem like bragging, flames,
17
+ digressions, stretches of awkward prose, and unnecessary words.I discarded more from the beginning. That's
18
+ not surprising; it takes a while to hit your stride. There
19
+ are more digressions at the start, because I'm not sure where
20
+ I'm heading.The amount of cutting is about average. I probably write
21
+ three to four words for every one that appears in the final
22
+ version of an essay.(Before anyone gets mad at me for opinions expressed here, remember
23
+ that anything you see here that's not in the final version is obviously
24
+ something I chose not to publish, often because I disagree
25
+ with it.)
26
+ Recently a friend said that what he liked about
27
+ my essays was that they weren't written the way
28
+ we'd been taught to write essays in school. You
29
+ remember: topic sentence, introductory paragraph,
30
+ supporting paragraphs, conclusion. It hadn't
31
+ occurred to me till then that those horrible things
32
+ we had to write in school were even connected to
33
+ what I was doing now. But sure enough, I thought,
34
+ they did call them "essays," didn't they?Well, they're not. Those things you have to write
35
+ in school are not only not essays, they're one of the
36
+ most pointless of all the pointless hoops you have
37
+ to jump through in school. And I worry that they
38
+ not only teach students the wrong things about writing,
39
+ but put them off writing entirely.So I'm going to give the other side of the story: what
40
+ an essay really is, and how you write one. Or at least,
41
+ how I write one. Students be forewarned: if you actually write
42
+ the kind of essay I describe, you'll probably get bad
43
+ grades. But knowing how it's really done should
44
+ at least help you to understand the feeling of futility
45
+ you have when you're writing the things they tell you to.
46
+ The most obvious difference between real essays and
47
+ the things one has to write in school is that real
48
+ essays are not exclusively about English literature.
49
+ It's a fine thing for schools to
50
+
51
+ teach students how to
52
+ write. But for some bizarre reason (actually, a very specific bizarre
53
+ reason that I'll explain in a moment),
54
+
55
+ the teaching of
56
+ writing has gotten mixed together with the study
57
+ of literature. And so all over the country, students are
58
+ writing not about how a baseball team with a small budget
59
+ might compete with the Yankees, or the role of color in
60
+ fashion, or what constitutes a good dessert, but about
61
+ symbolism in Dickens.With obvious
62
+ results. Only a few people really
63
+
64
+ care about
65
+ symbolism in Dickens. The teacher doesn't.
66
+ The students don't. Most of the people who've had to write PhD
67
+ disserations about Dickens don't. And certainly
68
+
69
+ Dickens himself would be more interested in an essay
70
+ about color or baseball.How did things get this way? To answer that we have to go back
71
+ almost a thousand years. Between about 500 and 1000, life was
72
+ not very good in Europe. The term "dark ages" is presently
73
+ out of fashion as too judgemental (the period wasn't dark;
74
+ it was just different), but if this label didn't already
75
+ exist, it would seem an inspired metaphor. What little
76
+ original thought there was took place in lulls between
77
+ constant wars and had something of the character of
78
+ the thoughts of parents with a new baby.
79
+ The most amusing thing written during this
80
+ period, Liudprand of Cremona's Embassy to Constantinople, is,
81
+ I suspect, mostly inadvertantly so.Around 1000 Europe began to catch its breath.
82
+ And once they
83
+ had the luxury of curiosity, one of the first things they discovered
84
+ was what we call "the classics."
85
+ Imagine if we were visited
86
+ by aliens. If they could even get here they'd presumably know a
87
+ few things we don't. Immediately Alien Studies would become
88
+ the most dynamic field of scholarship: instead of painstakingly
89
+ discovering things for ourselves, we could simply suck up
90
+ everything they'd discovered. So it was in Europe in 1200.
91
+ When classical texts began to circulate in Europe, they contained
92
+ not just new answers, but new questions. (If anyone proved
93
+ a theorem in christian Europe before 1200, for example, there
94
+ is no record of it.)For a couple centuries, some of the most important work
95
+ being done was intellectual archaelogy. Those were also
96
+ the centuries during which schools were first established.
97
+ And since reading ancient texts was the essence of what
98
+ scholars did then, it became the basis of the curriculum.By 1700, someone who wanted to learn about
99
+ physics didn't need to start by mastering Greek in order to read Aristotle. But schools
100
+ change slower than scholarship: the study of
101
+ ancient texts
102
+ had such prestige that it remained the backbone of
103
+ education
104
+ until the late 19th century. By then it was merely a tradition.
105
+ It did serve some purposes: reading a foreign language was difficult,
106
+ and thus taught discipline, or at least, kept students busy;
107
+ it introduced students to
108
+ cultures quite different from their own; and its very uselessness
109
+ made it function (like white gloves) as a social bulwark.
110
+ But it certainly wasn't
111
+ true, and hadn't been true for centuries, that students were
112
+ serving apprenticeships in the hottest area of scholarship.Classical scholarship had also changed. In the early era, philology
113
+ actually mattered. The texts that filtered into Europe were
114
+ all corrupted to some degree by the errors of translators and
115
+ copyists. Scholars had to figure out what Aristotle said
116
+ before they could figure out what he meant. But by the modern
117
+ era such questions were answered as well as they were ever
118
+ going to be. And so the study of ancient texts became less
119
+ about ancientness and more about texts.The time was then ripe for the question: if the study of
120
+ ancient texts is a valid field for scholarship, why not modern
121
+ texts? The answer, of course, is that the raison d'etre
122
+ of classical scholarship was a kind of intellectual archaelogy that
123
+ does not need to be done in the case of contemporary authors.
124
+ But for obvious reasons no one wanted to give that answer.
125
+ The archaeological work being mostly done, it implied that
126
+ the people studying the classics were, if not wasting their
127
+ time, at least working on problems of minor importance.And so began the study of modern literature. There was some
128
+ initial resistance, but it didn't last long.
129
+ The limiting
130
+ reagent in the growth of university departments is what
131
+ parents will let undergraduates study. If parents will let
132
+ their children major in x, the rest follows straightforwardly.
133
+ There will be jobs teaching x, and professors to fill them.
134
+ The professors will establish scholarly journals and publish
135
+ one another's papers. Universities with x departments will
136
+ subscribe to the journals. Graduate students who want jobs
137
+ as professors of x will write dissertations about it. It may
138
+ take a good long while for the more prestigious universities
139
+ to cave in and establish departments in cheesier xes, but
140
+ at the other end of the scale there are so many universities
141
+ competing to attract students that the mere establishment of
142
+ a discipline requires little more than the desire to do it.High schools imitate universities.
143
+ And so once university
144
+ English departments were established in the late nineteenth century,
145
+ the 'riting component of the 3 Rs
146
+ was morphed into English.
147
+ With the bizarre consequence that high school students now
148
+ had to write about English literature-- to write, without
149
+ even realizing it, imitations of whatever
150
+ English professors had been publishing in their journals a
151
+ few decades before. It's no wonder if this seems to the
152
+ student a pointless exercise, because we're now three steps
153
+ removed from real work: the students are imitating English
154
+ professors, who are imitating classical scholars, who are
155
+ merely the inheritors of a tradition growing out of what
156
+ was, 700 years ago, fascinating and urgently needed work.Perhaps high schools should drop English and just teach writing.
157
+ The valuable part of English classes is learning to write, and
158
+ that could be taught better by itself. Students learn better
159
+ when they're interested in what they're doing, and it's hard
160
+ to imagine a topic less interesting than symbolism in Dickens.
161
+ Most of the people who write about that sort of thing professionally
162
+ are not really interested in it. (Though indeed, it's been a
163
+ while since they were writing about symbolism; now they're
164
+ writing about gender.)I have no illusions about how eagerly this suggestion will
165
+ be adopted. Public schools probably couldn't stop teaching
166
+ English even if they wanted to; they're probably required to by
167
+ law. But here's a related suggestion that goes with the grain
168
+ instead of against it: that universities establish a
169
+ writing major. Many of the students who now major in English
170
+ would major in writing if they could, and most would
171
+ be better off.It will be argued that it is a good thing for students to be
172
+ exposed to their literary heritage. Certainly. But is that
173
+ more important than that they learn to write well? And are
174
+ English classes even the place to do it? After all,
175
+ the average public high school student gets zero exposure to
176
+ his artistic heritage. No disaster results.
177
+ The people who are interested in art learn about it for
178
+ themselves, and those who aren't don't. I find that American
179
+ adults are no better or worse informed about literature than
180
+ art, despite the fact that they spent years studying literature
181
+ in high school and no time at all studying art. Which presumably
182
+ means that what they're taught in school is rounding error
183
+ compared to what they pick up on their own.Indeed, English classes may even be harmful. In my case they
184
+ were effectively aversion therapy. Want to make someone dislike
185
+ a book? Force him to read it and write an essay about it.
186
+ And make the topic so intellectually bogus that you
187
+ could not, if asked, explain why one ought to write about it.
188
+ I love to read more than anything, but by the end of high school
189
+ I never read the books we were assigned. I was so disgusted with
190
+ what we were doing that it became a point of honor
191
+ with me to write nonsense at least as good at the other students'
192
+ without having more than glanced over the book to learn the names
193
+ of the characters and a few random events in it.I hoped this might be fixed in college, but I found the same
194
+ problem there. It was not the teachers. It was English.
195
+ We were supposed to read novels and write essays about them.
196
+ About what, and why? That no one seemed to be able to explain.
197
+ Eventually by trial and error I found that what the teacher
198
+ wanted us to do was pretend that the story had really taken
199
+ place, and to analyze based on what the characters said and did (the
200
+ subtler clues, the better) what their motives must have been.
201
+ One got extra credit for motives having to do with class,
202
+ as I suspect one must now for those involving gender and
203
+ sexuality. I learned how to churn out such stuff well enough
204
+ to get an A, but I never took another English class.And the books we did these disgusting things to, like those
205
+ we mishandled in high school, I find still have black marks
206
+ against them in my mind. The one saving grace was that
207
+ English courses tend to favor pompous, dull writers like
208
+ Henry James, who deserve black marks against their names anyway.
209
+ One of the principles the IRS uses in deciding whether to
210
+ allow deductions is that, if something is fun, it isn't work.
211
+ Fields that are intellectually unsure of themselves rely on
212
+ a similar principle. Reading P.G. Wodehouse or Evelyn Waugh or
213
+ Raymond Chandler is too obviously pleasing to seem like
214
+ serious work, as reading Shakespeare would have been before
215
+ English evolved enough to make it an effort to understand him. [sh]
216
+ And so good writers (just you wait and see who's still in
217
+ print in 300 years) are less likely to have readers turned
218
+ against them by clumsy, self-appointed tour guides.
219
+ The other big difference between a real essay and the
220
+ things
221
+ they make you write in school is that a real essay doesn't
222
+ take a position and then defend it. That principle,
223
+ like the idea that we ought to be writing about literature,
224
+ turns out to be another intellectual hangover of long
225
+ forgotten origins. It's often mistakenly believed that
226
+ medieval universities were mostly seminaries. In fact they
227
+ were more law schools. And at least in our tradition
228
+ lawyers are advocates: they are
229
+ trained to be able to
230
+ take
231
+ either side of an argument and make as good a case for it
232
+ as they can. Whether or not this is a good idea (in the case of prosecutors,
233
+ it probably isn't), it tended to pervade
234
+ the atmosphere of
235
+ early universities. After the lecture the most common form
236
+ of discussion was the disputation. This idea
237
+ is at least
238
+ nominally preserved in our present-day thesis defense-- indeed,
239
+ in the very word thesis. Most people treat the words
240
+ thesis
241
+ and dissertation as interchangeable, but originally, at least,
242
+ a thesis was a position one took and the dissertation was
243
+ the argument by which one defended it.I'm not complaining that we blur these two words together.
244
+ As far as I'm concerned, the sooner we lose the original
245
+ sense of the word thesis, the better. For many, perhaps most,
246
+ graduate students, it is stuffing a square peg into a round
247
+ hole to try to recast one's work as a single thesis. And
248
+ as for the disputation, that seems clearly a net lose.
249
+ Arguing two sides of a case may be a necessary evil in a
250
+ legal dispute, but it's not the best way to get at the truth,
251
+ as I think lawyers would be the first to admit.
252
+ And yet this principle is built into the very structure of
253
+ the essays
254
+ they teach you to write in high school. The topic
255
+ sentence is your thesis, chosen in advance, the supporting
256
+ paragraphs the blows you strike in the conflict, and the
257
+ conclusion--- uh, what it the conclusion? I was never sure
258
+ about that in high school. If your thesis was well expressed,
259
+ what need was there to restate it? In theory it seemed that
260
+ the conclusion of a really good essay ought not to need to
261
+ say any more than QED.
262
+ But when you understand the origins
263
+ of this sort of "essay", you can see where the
264
+ conclusion comes from. It's the concluding remarks to the
265
+ jury.
266
+ What other alternative is there? To answer that
267
+ we have to
268
+ reach back into history again, though this time not so far.
269
+ To Michel de Montaigne, inventor of the essay.
270
+ He was
271
+ doing something quite different from what a
272
+ lawyer does,
273
+ and
274
+ the difference is embodied in the name. Essayer is the French
275
+ verb meaning "to try" (the cousin of our word assay),
276
+
277
+ and an "essai" is an effort.
278
+ An essay is something you
279
+ write in order
280
+ to figure something out.Figure out what? You don't know yet. And so you can't begin with a
281
+ thesis, because you don't have one, and may never have
282
+ one. An essay doesn't begin with a statement, but with a
283
+ question. In a real essay, you don't take a position and
284
+ defend it. You see a door that's ajar, and you open it and
285
+ walk in to see what's inside.If all you want to do is figure things out, why do you need
286
+ to write anything, though? Why not just sit and think? Well,
287
+ there precisely is Montaigne's great discovery. Expressing
288
+ ideas helps to form them. Indeed, helps is far too weak a
289
+ word. 90%
290
+ of what ends up in my essays was stuff
291
+ I only
292
+ thought of when I sat down to write them. That's why I
293
+ write them.So there's another difference between essays and
294
+ the things
295
+ you have to write in school. In school
296
+
297
+ you are, in theory,
298
+ explaining yourself to someone else. In the best case---if
299
+ you're really organized---you're just writing it down.
300
+ In a real essay you're writing for yourself. You're
301
+ thinking out loud.But not quite. Just as inviting people over forces you to
302
+ clean up your apartment, writing something that you know
303
+
304
+ other people will read forces you to think well. So it
305
+ does matter to have an audience. The things I've written
306
+ just for myself are no good. Indeed, they're bad in
307
+ a particular way:
308
+ they tend to peter out. When I run into
309
+ difficulties, I notice that I
310
+ tend to conclude with a few vague
311
+ questions and then drift off to get a cup of tea.This seems a common problem.
312
+ It's practically the standard
313
+ ending in blog entries--- with the addition of a "heh" or an
314
+ emoticon, prompted by the all too accurate sense that
315
+ something is missing.And indeed, a lot of
316
+ published essays peter out in this
317
+ same way.
318
+ Particularly the sort written by the staff writers of newsmagazines. Outside writers tend to supply
319
+ editorials of the defend-a-position variety, which
320
+ make a beeline toward a rousing (and
321
+ foreordained) conclusion. But the staff writers feel
322
+ obliged to write something more
323
+ balanced, which in
324
+ practice ends up meaning blurry.
325
+ Since they're
326
+ writing for a popular magazine, they start with the
327
+ most radioactively controversial questions, from which
328
+ (because they're writing for a popular magazine)
329
+ they then proceed to recoil from
330
+ in terror.
331
+ Gay marriage, for or
332
+ against? This group says one thing. That group says
333
+ another. One thing is certain: the question is a
334
+ complex one. (But don't get mad at us. We didn't
335
+ draw any conclusions.)Questions aren't enough. An essay has to come up with answers.
336
+ They don't always, of course. Sometimes you start with a
337
+ promising question and get nowhere. But those you don't
338
+ publish. Those are like experiments that get inconclusive
339
+ results. Something you publish ought to tell the reader
340
+ something he didn't already know.
341
+ But what you tell him doesn't matter, so long as
342
+ it's interesting. I'm sometimes accused of meandering.
343
+ In defend-a-position writing that would be a flaw.
344
+ There you're not concerned with truth. You already
345
+ know where you're going, and you want to go straight there,
346
+ blustering through obstacles, and hand-waving
347
+ your way across swampy ground. But that's not what
348
+ you're trying to do in an essay. An essay is supposed to
349
+ be a search for truth. It would be suspicious if it didn't
350
+ meander.The Meander is a river in Asia Minor (aka
351
+ Turkey).
352
+ As you might expect, it winds all over the place.
353
+ But does it
354
+ do this out of frivolity? Quite the opposite.
355
+ Like all rivers, it's rigorously following the laws of physics.
356
+ The path it has discovered,
357
+ winding as it is, represents
358
+ the most economical route to the sea.The river's algorithm is simple. At each step, flow down.
359
+ For the essayist this translates to: flow interesting.
360
+ Of all the places to go next, choose
361
+ whichever seems
362
+ most interesting.I'm pushing this metaphor a bit. An essayist
363
+ can't have
364
+ quite as little foresight as a river. In fact what you do
365
+ (or what I do) is somewhere between a river and a roman
366
+ road-builder. I have a general idea of the direction
367
+ I want to go in, and
368
+ I choose the next topic with that in mind. This essay is
369
+ about writing, so I do occasionally yank it back in that
370
+ direction, but it is not all the sort of essay I
371
+ thought I was going to write about writing.Note too that hill-climbing (which is what this algorithm is
372
+ called) can get you in trouble.
373
+ Sometimes, just
374
+ like a river,
375
+ you
376
+ run up against a blank wall. What
377
+ I do then is just
378
+ what the river does: backtrack.
379
+ At one point in this essay
380
+ I found that after following a certain thread I ran out
381
+ of ideas. I had to go back n
382
+ paragraphs and start over
383
+ in another direction. For illustrative purposes I've left
384
+ the abandoned branch as a footnote.
385
+ Err on the side of the river. An essay is not a reference
386
+ work. It's not something you read looking for a specific
387
+ answer, and feel cheated if you don't find it. I'd much
388
+ rather read an essay that went off in an unexpected but
389
+ interesting direction than one that plodded dutifully along
390
+ a prescribed course.So what's interesting? For me, interesting means surprise.
391
+ Design, as Matz
392
+ has said, should follow the principle of
393
+ least surprise.
394
+ A button that looks like it will make a
395
+ machine stop should make it stop, not speed up. Essays
396
+ should do the opposite. Essays should aim for maximum
397
+ surprise.I was afraid of flying for a long time and could only travel
398
+ vicariously. When friends came back from faraway places,
399
+ it wasn't just out of politeness that I asked them about
400
+ their trip.
401
+ I really wanted to know. And I found that
402
+ the best way to get information out of them was to ask
403
+ what surprised them. How was the place different from what
404
+ they expected? This is an extremely useful question.
405
+ You can ask it of even
406
+ the most unobservant people, and it will
407
+ extract information they didn't even know they were
408
+ recording. Indeed, you can ask it in real time. Now when I go somewhere
409
+ new, I make a note of what surprises me about it. Sometimes I
410
+ even make a conscious effort to visualize the place beforehand,
411
+ so I'll have a detailed image to diff with reality.
412
+ Surprises are facts
413
+ you didn't already
414
+ know.
415
+ But they're
416
+ more than that. They're facts
417
+ that contradict things you
418
+ thought you knew. And so they're the most valuable sort of
419
+ fact you can get. They're like a food that's not merely
420
+ healthy, but counteracts the unhealthy effects of things
421
+ you've already eaten.
422
+ How do you find surprises? Well, therein lies half
423
+ the work of essay writing. (The other half is expressing
424
+ yourself well.) You can at least
425
+ use yourself as a
426
+ proxy for the reader. You should only write about things
427
+ you've thought about a lot. And anything you come across
428
+ that surprises you, who've thought about the topic a lot,
429
+ will probably surprise most readers.For example, in a recent essay I pointed out that because
430
+ you can only judge computer programmers by working with
431
+ them, no one knows in programming who the heroes should
432
+ be.
433
+ I
434
+ certainly
435
+ didn't realize this when I started writing
436
+ the
437
+ essay, and even now I find it kind of weird. That's
438
+ what you're looking for.So if you want to write essays, you need two ingredients:
439
+ you need
440
+ a few topics that you think about a lot, and you
441
+ need some ability to ferret out the unexpected.What should you think about? My guess is that it
442
+ doesn't matter. Almost everything is
443
+ interesting if you get deeply
444
+ enough into it. The one possible exception
445
+ are
446
+ things
447
+ like working in fast food, which
448
+ have deliberately had all
449
+ the variation sucked out of them.
450
+ In retrospect, was there
451
+ anything interesting about working in Baskin-Robbins?
452
+ Well, it was interesting to notice
453
+ how important color was
454
+ to the customers. Kids a certain age would point into
455
+ the case and say that they wanted yellow. Did they want
456
+ French Vanilla or Lemon? They would just look at you
457
+ blankly. They wanted yellow. And then there was the
458
+ mystery of why the perennial favorite Pralines n' Cream
459
+ was so appealing. I'm inclined now to
460
+ think it was the salt.
461
+ And the mystery of why Passion Fruit tasted so disgusting.
462
+ People would order it because of the name, and were always
463
+ disappointed. It should have been called In-sink-erator
464
+ Fruit.
465
+ And there was
466
+ the difference in the way fathers and
467
+ mothers bought ice cream for their kids.
468
+ Fathers tended to
469
+ adopt the attitude of
470
+ benevolent kings bestowing largesse,
471
+ and mothers that of
472
+ harried bureaucrats,
473
+ giving in to
474
+ pressure against their better judgement.
475
+ So, yes, there does seem to be material, even in
476
+ fast food.What about the other half, ferreting out the unexpected?
477
+ That may require some natural ability. I've noticed for
478
+ a long time that I'm pathologically observant. ....[That was as far as I'd gotten at the time.]Notes[sh] In Shakespeare's own time, serious writing meant theological
479
+ discourses, not the bawdy plays acted over on the other
480
+ side of the river among the bear gardens and whorehouses.The other extreme, the work that seems formidable from the moment
481
+ it's created (indeed, is deliberately intended to be)
482
+ is represented by Milton. Like the Aeneid, Paradise Lost is a
483
+ rock imitating a butterfly that happened to get fossilized.
484
+ Even Samuel Johnson seems to have balked at this, on the one
485
+ hand paying Milton the compliment of an extensive biography,
486
+ and on the other writing of Paradise Lost that "none who read it
487
+ ever wished it longer."
PaulGrahamEssays/love.txt ADDED
@@ -0,0 +1,376 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ January 2006To do something well you have to like it. That idea is not exactly
10
+ novel. We've got it down to four words: "Do what you love." But
11
+ it's not enough just to tell people that. Doing what you love is
12
+ complicated.The very idea is foreign to what most of us learn as kids. When I
13
+ was a kid, it seemed as if work and fun were opposites by definition.
14
+ Life had two states: some of the time adults were making you do
15
+ things, and that was called work; the rest of the time you could
16
+ do what you wanted, and that was called playing. Occasionally the
17
+ things adults made you do were fun, just as, occasionally, playing
18
+ wasn't—for example, if you fell and hurt yourself. But except
19
+ for these few anomalous cases, work was pretty much defined as
20
+ not-fun.And it did not seem to be an accident. School, it was implied, was
21
+ tedious because it was preparation for grownup work.The world then was divided into two groups, grownups and kids.
22
+ Grownups, like some kind of cursed race, had to work. Kids didn't,
23
+ but they did have to go to school, which was a dilute version of
24
+ work meant to prepare us for the real thing. Much as we disliked
25
+ school, the grownups all agreed that grownup work was worse, and
26
+ that we had it easy.Teachers in particular all seemed to believe implicitly that work
27
+ was not fun. Which is not surprising: work wasn't fun for most of
28
+ them. Why did we have to memorize state capitals instead of playing
29
+ dodgeball? For the same reason they had to watch over a bunch of
30
+ kids instead of lying on a beach. You couldn't just do what you
31
+ wanted.I'm not saying we should let little kids do whatever they want.
32
+ They may have to be made to work on certain things. But if we make
33
+ kids work on dull stuff, it might be wise to tell them that tediousness
34
+ is not the defining quality of work, and indeed that the reason
35
+ they have to work on dull stuff now is so they can work on more
36
+ interesting stuff later.
37
+ [1]Once, when I was about 9 or 10, my father told me I could be whatever
38
+ I wanted when I grew up, so long as I enjoyed it. I remember that
39
+ precisely because it seemed so anomalous. It was like being told
40
+ to use dry water. Whatever I thought he meant, I didn't think he
41
+ meant work could literally be fun—fun like playing. It
42
+ took me years to grasp that.JobsBy high school, the prospect of an actual job was on the horizon.
43
+ Adults would sometimes come to speak to us about their work, or we
44
+ would go to see them at work. It was always understood that they
45
+ enjoyed what they did. In retrospect I think one may have: the
46
+ private jet pilot. But I don't think the bank manager really did.The main reason they all acted as if they enjoyed their work was
47
+ presumably the upper-middle class convention that you're supposed
48
+ to. It would not merely be bad for your career to say that you
49
+ despised your job, but a social faux-pas.Why is it conventional to pretend to like what you do? The first
50
+ sentence of this essay explains that. If you have to like something
51
+ to do it well, then the most successful people will all like what
52
+ they do. That's where the upper-middle class tradition comes from.
53
+ Just as houses all over America are full of
54
+ chairs
55
+ that are, without
56
+ the owners even knowing it, nth-degree imitations of chairs designed
57
+ 250 years ago for French kings, conventional attitudes about work
58
+ are, without the owners even knowing it, nth-degree imitations of
59
+ the attitudes of people who've done great things.What a recipe for alienation. By the time they reach an age to
60
+ think about what they'd like to do, most kids have been thoroughly
61
+ misled about the idea of loving one's work. School has trained
62
+ them to regard work as an unpleasant duty. Having a job is said
63
+ to be even more onerous than schoolwork. And yet all the adults
64
+ claim to like what they do. You can't blame kids for thinking "I
65
+ am not like these people; I am not suited to this world."Actually they've been told three lies: the stuff they've been taught
66
+ to regard as work in school is not real work; grownup work is not
67
+ (necessarily) worse than schoolwork; and many of the adults around
68
+ them are lying when they say they like what they do.The most dangerous liars can be the kids' own parents. If you take
69
+ a boring job to give your family a high standard of living, as so
70
+ many people do, you risk infecting your kids with the idea that
71
+ work is boring.
72
+ [2]
73
+ Maybe it would be better for kids in this one
74
+ case if parents were not so unselfish. A parent who set an example
75
+ of loving their work might help their kids more than an expensive
76
+ house.
77
+ [3]It was not till I was in college that the idea of work finally broke
78
+ free from the idea of making a living. Then the important question
79
+ became not how to make money, but what to work on. Ideally these
80
+ coincided, but some spectacular boundary cases (like Einstein in
81
+ the patent office) proved they weren't identical.The definition of work was now to make some original contribution
82
+ to the world, and in the process not to starve. But after the habit
83
+ of so many years my idea of work still included a large component
84
+ of pain. Work still seemed to require discipline, because only
85
+ hard problems yielded grand results, and hard problems couldn't
86
+ literally be fun. Surely one had to force oneself to work on them.If you think something's supposed to hurt, you're less likely to
87
+ notice if you're doing it wrong. That about sums up my experience
88
+ of graduate school.BoundsHow much are you supposed to like what you do? Unless you
89
+ know that, you don't know when to stop searching. And if, like most
90
+ people, you underestimate it, you'll tend to stop searching too
91
+ early. You'll end up doing something chosen for you by your parents,
92
+ or the desire to make money, or prestige—or sheer inertia.Here's an upper bound: Do what you love doesn't mean, do what you
93
+ would like to do most this second. Even Einstein probably
94
+ had moments when he wanted to have a cup of coffee, but told himself
95
+ he ought to finish what he was working on first.It used to perplex me when I read about people who liked what they
96
+ did so much that there was nothing they'd rather do. There didn't
97
+ seem to be any sort of work I liked that much. If I had a
98
+ choice of (a) spending the next hour working on something or (b)
99
+ be teleported to Rome and spend the next hour wandering about, was
100
+ there any sort of work I'd prefer? Honestly, no.But the fact is, almost anyone would rather, at any given moment,
101
+ float about in the Carribbean, or have sex, or eat some delicious
102
+ food, than work on hard problems. The rule about doing what you
103
+ love assumes a certain length of time. It doesn't mean, do what
104
+ will make you happiest this second, but what will make you happiest
105
+ over some longer period, like a week or a month.Unproductive pleasures pall eventually. After a while you get tired
106
+ of lying on the beach. If you want to stay happy, you have to do
107
+ something.As a lower bound, you have to like your work more than any unproductive
108
+ pleasure. You have to like what you do enough that the concept of
109
+ "spare time" seems mistaken. Which is not to say you have to spend
110
+ all your time working. You can only work so much before you get
111
+ tired and start to screw up. Then you want to do something else—even something mindless. But you don't regard this time as the
112
+ prize and the time you spend working as the pain you endure to earn
113
+ it.I put the lower bound there for practical reasons. If your work
114
+ is not your favorite thing to do, you'll have terrible problems
115
+ with procrastination. You'll have to force yourself to work, and
116
+ when you resort to that the results are distinctly inferior.To be happy I think you have to be doing something you not only
117
+ enjoy, but admire. You have to be able to say, at the end, wow,
118
+ that's pretty cool. This doesn't mean you have to make something.
119
+ If you learn how to hang glide, or to speak a foreign language
120
+ fluently, that will be enough to make you say, for a while at least,
121
+ wow, that's pretty cool. What there has to be is a test.So one thing that falls just short of the standard, I think, is
122
+ reading books. Except for some books in math and the hard sciences,
123
+ there's no test of how well you've read a book, and that's why
124
+ merely reading books doesn't quite feel like work. You have to do
125
+ something with what you've read to feel productive.I think the best test is one Gino Lee taught me: to try to do things
126
+ that would make your friends say wow. But it probably wouldn't
127
+ start to work properly till about age 22, because most people haven't
128
+ had a big enough sample to pick friends from before then.SirensWhat you should not do, I think, is worry about the opinion of
129
+ anyone beyond your friends. You shouldn't worry about prestige.
130
+ Prestige is the opinion of the rest of the world. When you can ask
131
+ the opinions of people whose judgement you respect, what does it
132
+ add to consider the opinions of people you don't even know?
133
+ [4]This is easy advice to give. It's hard to follow, especially when
134
+ you're young.
135
+ [5]
136
+ Prestige is like a powerful magnet that warps
137
+ even your beliefs about what you enjoy. It causes you to work not
138
+ on what you like, but what you'd like to like.That's what leads people to try to write novels, for example. They
139
+ like reading novels. They notice that people who write them win
140
+ Nobel prizes. What could be more wonderful, they think, than to
141
+ be a novelist? But liking the idea of being a novelist is not
142
+ enough; you have to like the actual work of novel-writing if you're
143
+ going to be good at it; you have to like making up elaborate lies.Prestige is just fossilized inspiration. If you do anything well
144
+ enough, you'll make it prestigious. Plenty of things we now
145
+ consider prestigious were anything but at first. Jazz comes to
146
+ mind—though almost any established art form would do. So just
147
+ do what you like, and let prestige take care of itself.Prestige is especially dangerous to the ambitious. If you want to
148
+ make ambitious people waste their time on errands, the way to do
149
+ it is to bait the hook with prestige. That's the recipe for getting
150
+ people to give talks, write forewords, serve on committees, be
151
+ department heads, and so on. It might be a good rule simply to
152
+ avoid any prestigious task. If it didn't suck, they wouldn't have
153
+ had to make it prestigious.Similarly, if you admire two kinds of work equally, but one is more
154
+ prestigious, you should probably choose the other. Your opinions
155
+ about what's admirable are always going to be slightly influenced
156
+ by prestige, so if the two seem equal to you, you probably have
157
+ more genuine admiration for the less prestigious one.The other big force leading people astray is money. Money by itself
158
+ is not that dangerous. When something pays well but is regarded
159
+ with contempt, like telemarketing, or prostitution, or personal
160
+ injury litigation, ambitious people aren't tempted by it. That
161
+ kind of work ends up being done by people who are "just trying to
162
+ make a living." (Tip: avoid any field whose practitioners say
163
+ this.) The danger is when money is combined with prestige, as in,
164
+ say, corporate law, or medicine. A comparatively safe and prosperous
165
+ career with some automatic baseline prestige is dangerously tempting
166
+ to someone young, who hasn't thought much about what they really
167
+ like.The test of whether people love what they do is whether they'd do
168
+ it even if they weren't paid for it—even if they had to work at
169
+ another job to make a living. How many corporate lawyers would do
170
+ their current work if they had to do it for free, in their spare
171
+ time, and take day jobs as waiters to support themselves?This test is especially helpful in deciding between different kinds
172
+ of academic work, because fields vary greatly in this respect. Most
173
+ good mathematicians would work on math even if there were no jobs
174
+ as math professors, whereas in the departments at the other end of
175
+ the spectrum, the availability of teaching jobs is the driver:
176
+ people would rather be English professors than work in ad agencies,
177
+ and publishing papers is the way you compete for such jobs. Math
178
+ would happen without math departments, but it is the existence of
179
+ English majors, and therefore jobs teaching them, that calls into
180
+ being all those thousands of dreary papers about gender and identity
181
+ in the novels of Conrad. No one does
182
+ that
183
+ kind of thing for fun.The advice of parents will tend to err on the side of money. It
184
+ seems safe to say there are more undergrads who want to be novelists
185
+ and whose parents want them to be doctors than who want to be doctors
186
+ and whose parents want them to be novelists. The kids think their
187
+ parents are "materialistic." Not necessarily. All parents tend to
188
+ be more conservative for their kids than they would for themselves,
189
+ simply because, as parents, they share risks more than rewards. If
190
+ your eight year old son decides to climb a tall tree, or your teenage
191
+ daughter decides to date the local bad boy, you won't get a share
192
+ in the excitement, but if your son falls, or your daughter gets
193
+ pregnant, you'll have to deal with the consequences.DisciplineWith such powerful forces leading us astray, it's not surprising
194
+ we find it so hard to discover what we like to work on. Most people
195
+ are doomed in childhood by accepting the axiom that work = pain.
196
+ Those who escape this are nearly all lured onto the rocks by prestige
197
+ or money. How many even discover something they love to work on?
198
+ A few hundred thousand, perhaps, out of billions.It's hard to find work you love; it must be, if so few do. So don't
199
+ underestimate this task. And don't feel bad if you haven't succeeded
200
+ yet. In fact, if you admit to yourself that you're discontented,
201
+ you're a step ahead of most people, who are still in denial. If
202
+ you're surrounded by colleagues who claim to enjoy work that you
203
+ find contemptible, odds are they're lying to themselves. Not
204
+ necessarily, but probably.Although doing great work takes less discipline than people think—because the way to do great work is to find something you like so
205
+ much that you don't have to force yourself to do it—finding
206
+ work you love does usually require discipline. Some people are
207
+ lucky enough to know what they want to do when they're 12, and just
208
+ glide along as if they were on railroad tracks. But this seems the
209
+ exception. More often people who do great things have careers with
210
+ the trajectory of a ping-pong ball. They go to school to study A,
211
+ drop out and get a job doing B, and then become famous for C after
212
+ taking it up on the side.Sometimes jumping from one sort of work to another is a sign of
213
+ energy, and sometimes it's a sign of laziness. Are you dropping
214
+ out, or boldly carving a new path? You often can't tell yourself.
215
+ Plenty of people who will later do great things seem to be disappointments
216
+ early on, when they're trying to find their niche.Is there some test you can use to keep yourself honest? One is to
217
+ try to do a good job at whatever you're doing, even if you don't
218
+ like it. Then at least you'll know you're not using dissatisfaction
219
+ as an excuse for being lazy. Perhaps more importantly, you'll get
220
+ into the habit of doing things well.Another test you can use is: always produce. For example, if you
221
+ have a day job you don't take seriously because you plan to be a
222
+ novelist, are you producing? Are you writing pages of fiction,
223
+ however bad? As long as you're producing, you'll know you're not
224
+ merely using the hazy vision of the grand novel you plan to write
225
+ one day as an opiate. The view of it will be obstructed by the all
226
+ too palpably flawed one you're actually writing."Always produce" is also a heuristic for finding the work you love.
227
+ If you subject yourself to that constraint, it will automatically
228
+ push you away from things you think you're supposed to work on,
229
+ toward things you actually like. "Always produce" will discover
230
+ your life's work the way water, with the aid of gravity, finds the
231
+ hole in your roof.Of course, figuring out what you like to work on doesn't mean you
232
+ get to work on it. That's a separate question. And if you're
233
+ ambitious you have to keep them separate: you have to make a conscious
234
+ effort to keep your ideas about what you want from being contaminated
235
+ by what seems possible.
236
+ [6]It's painful to keep them apart, because it's painful to observe
237
+ the gap between them. So most people pre-emptively lower their
238
+ expectations. For example, if you asked random people on the street
239
+ if they'd like to be able to draw like Leonardo, you'd find most
240
+ would say something like "Oh, I can't draw." This is more a statement
241
+ of intention than fact; it means, I'm not going to try. Because
242
+ the fact is, if you took a random person off the street and somehow
243
+ got them to work as hard as they possibly could at drawing for the
244
+ next twenty years, they'd get surprisingly far. But it would require
245
+ a great moral effort; it would mean staring failure in the eye every
246
+ day for years. And so to protect themselves people say "I can't."Another related line you often hear is that not everyone can do
247
+ work they love—that someone has to do the unpleasant jobs. Really?
248
+ How do you make them? In the US the only mechanism for forcing
249
+ people to do unpleasant jobs is the draft, and that hasn't been
250
+ invoked for over 30 years. All we can do is encourage people to
251
+ do unpleasant work, with money and prestige.If there's something people still won't do, it seems as if society
252
+ just has to make do without. That's what happened with domestic
253
+ servants. For millennia that was the canonical example of a job
254
+ "someone had to do." And yet in the mid twentieth century servants
255
+ practically disappeared in rich countries, and the rich have just
256
+ had to do without.So while there may be some things someone has to do, there's a good
257
+ chance anyone saying that about any particular job is mistaken.
258
+ Most unpleasant jobs would either get automated or go undone if no
259
+ one were willing to do them.Two RoutesThere's another sense of "not everyone can do work they love"
260
+ that's all too true, however. One has to make a living, and it's
261
+ hard to get paid for doing work you love. There are two routes to
262
+ that destination:
263
+
264
+ The organic route: as you become more eminent, gradually to
265
+ increase the parts of your job that you like at the expense of
266
+ those you don't.The two-job route: to work at things you don't like to get money
267
+ to work on things you do.
268
+
269
+ The organic route is more common. It happens naturally to anyone
270
+ who does good work. A young architect has to take whatever work
271
+ he can get, but if he does well he'll gradually be in a position
272
+ to pick and choose among projects. The disadvantage of this route
273
+ is that it's slow and uncertain. Even tenure is not real freedom.The two-job route has several variants depending on how long you
274
+ work for money at a time. At one extreme is the "day job," where
275
+ you work regular hours at one job to make money, and work on what
276
+ you love in your spare time. At the other extreme you work at
277
+ something till you make enough not to
278
+ have to work for money again.The two-job route is less common than the organic route, because
279
+ it requires a deliberate choice. It's also more dangerous. Life
280
+ tends to get more expensive as you get older, so it's easy to get
281
+ sucked into working longer than you expected at the money job.
282
+ Worse still, anything you work on changes you. If you work too
283
+ long on tedious stuff, it will rot your brain. And the best paying
284
+ jobs are most dangerous, because they require your full attention.The advantage of the two-job route is that it lets you jump over
285
+ obstacles. The landscape of possible jobs isn't flat; there are
286
+ walls of varying heights between different kinds of work.
287
+ [7]
288
+ The trick of maximizing the parts of your job that you like can get you
289
+ from architecture to product design, but not, probably, to music.
290
+ If you make money doing one thing and then work on another, you
291
+ have more freedom of choice.Which route should you take? That depends on how sure you are of
292
+ what you want to do, how good you are at taking orders, how much
293
+ risk you can stand, and the odds that anyone will pay (in your
294
+ lifetime) for what you want to do. If you're sure of the general
295
+ area you want to work in and it's something people are likely to
296
+ pay you for, then you should probably take the organic route. But
297
+ if you don't know what you want to work on, or don't like to take
298
+ orders, you may want to take the two-job route, if you can stand
299
+ the risk.Don't decide too soon. Kids who know early what they want to do
300
+ seem impressive, as if they got the answer to some math question
301
+ before the other kids. They have an answer, certainly, but odds
302
+ are it's wrong.A friend of mine who is a quite successful doctor complains constantly
303
+ about her job. When people applying to medical school ask her for
304
+ advice, she wants to shake them and yell "Don't do it!" (But she
305
+ never does.) How did she get into this fix? In high school she
306
+ already wanted to be a doctor. And she is so ambitious and determined
307
+ that she overcame every obstacle along the way—including,
308
+ unfortunately, not liking it.Now she has a life chosen for her by a high-school kid.When you're young, you're given the impression that you'll get
309
+ enough information to make each choice before you need to make it.
310
+ But this is certainly not so with work. When you're deciding what
311
+ to do, you have to operate on ridiculously incomplete information.
312
+ Even in college you get little idea what various types of work are
313
+ like. At best you may have a couple internships, but not all jobs
314
+ offer internships, and those that do don't teach you much more about
315
+ the work than being a batboy teaches you about playing baseball.In the design of lives, as in the design of most other things, you
316
+ get better results if you use flexible media. So unless you're
317
+ fairly sure what you want to do, your best bet may be to choose a
318
+ type of work that could turn into either an organic or two-job
319
+ career. That was probably part of the reason I chose computers.
320
+ You can be a professor, or make a lot of money, or morph it into
321
+ any number of other kinds of work.It's also wise, early on, to seek jobs that let you do many different
322
+ things, so you can learn faster what various kinds of work are like.
323
+ Conversely, the extreme version of the two-job route is dangerous
324
+ because it teaches you so little about what you like. If you work
325
+ hard at being a bond trader for ten years, thinking that you'll
326
+ quit and write novels when you have enough money, what happens when
327
+ you quit and then discover that you don't actually like writing
328
+ novels?Most people would say, I'd take that problem. Give me a million
329
+ dollars and I'll figure out what to do. But it's harder than it
330
+ looks. Constraints give your life shape. Remove them and most
331
+ people have no idea what to do: look at what happens to those who
332
+ win lotteries or inherit money. Much as everyone thinks they want
333
+ financial security, the happiest people are not those who have it,
334
+ but those who like what they do. So a plan that promises freedom
335
+ at the expense of knowing what to do with it may not be as good as
336
+ it seems.Whichever route you take, expect a struggle. Finding work you love
337
+ is very difficult. Most people fail. Even if you succeed, it's
338
+ rare to be free to work on what you want till your thirties or
339
+ forties. But if you have the destination in sight you'll be more
340
+ likely to arrive at it. If you know you can love work, you're in
341
+ the home stretch, and if you know what work you love, you're
342
+ practically there.Notes[1]
343
+ Currently we do the opposite: when we make kids do boring work,
344
+ like arithmetic drills, instead of admitting frankly that it's
345
+ boring, we try to disguise it with superficial decorations.[2]
346
+ One father told me about a related phenomenon: he found himself
347
+ concealing from his family how much he liked his work. When he
348
+ wanted to go to work on a saturday, he found it easier to say that
349
+ it was because he "had to" for some reason, rather than admitting
350
+ he preferred to work than stay home with them.[3]
351
+ Something similar happens with suburbs. Parents move to suburbs
352
+ to raise their kids in a safe environment, but suburbs are so dull
353
+ and artificial that by the time they're fifteen the kids are convinced
354
+ the whole world is boring.[4]
355
+ I'm not saying friends should be the only audience for your
356
+ work. The more people you can help, the better. But friends should
357
+ be your compass.[5]
358
+ Donald Hall said young would-be poets were mistaken to be so
359
+ obsessed with being published. But you can imagine what it would
360
+ do for a 24 year old to get a poem published in The New Yorker.
361
+ Now to people he meets at parties he's a real poet. Actually he's
362
+ no better or worse than he was before, but to a clueless audience
363
+ like that, the approval of an official authority makes all the
364
+ difference. So it's a harder problem than Hall realizes. The
365
+ reason the young care so much about prestige is that the people
366
+ they want to impress are not very discerning.[6]
367
+ This is isomorphic to the principle that you should prevent
368
+ your beliefs about how things are from being contaminated by how
369
+ you wish they were. Most people let them mix pretty promiscuously.
370
+ The continuing popularity of religion is the most visible index of
371
+ that.[7]
372
+ A more accurate metaphor would be to say that the graph of jobs
373
+ is not very well connected.Thanks to Trevor Blackwell, Dan Friedman, Sarah Harlin,
374
+ Jessica Livingston, Jackie McDonough, Robert Morris, Peter Norvig,
375
+ David Sloo, and Aaron Swartz
376
+ for reading drafts of this.
PaulGrahamEssays/mod.txt ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ December 2019There are two distinct ways to be politically moderate: on purpose
2
+ and by accident. Intentional moderates are trimmers, deliberately
3
+ choosing a position mid-way between the extremes of right and left.
4
+ Accidental moderates end up in the middle, on average, because they
5
+ make up their own minds about each question, and the far right and
6
+ far left are roughly equally wrong.You can distinguish intentional from accidental moderates by the
7
+ distribution of their opinions. If the far left opinion on some
8
+ matter is 0 and the far right opinion 100, an intentional moderate's
9
+ opinion on every question will be near 50. Whereas an accidental
10
+ moderate's opinions will be scattered over a broad range, but will,
11
+ like those of the intentional moderate, average to about 50.Intentional moderates are similar to those on the far left and the
12
+ far right in that their opinions are, in a sense, not their own.
13
+ The defining quality of an ideologue, whether on the left or the
14
+ right, is to acquire one's opinions in bulk. You don't get to pick
15
+ and choose. Your opinions about taxation can be predicted from your
16
+ opinions about sex. And although intentional moderates
17
+ might seem to be the opposite of ideologues, their beliefs (though
18
+ in their case the word "positions" might be more accurate) are also
19
+ acquired in bulk. If the median opinion shifts to the right or left,
20
+ the intentional moderate must shift with it. Otherwise they stop
21
+ being moderate.Accidental moderates, on the other hand, not only choose their own
22
+ answers, but choose their own questions. They may not care at all
23
+ about questions that the left and right both think are terribly
24
+ important. So you can only even measure the politics of an accidental
25
+ moderate from the intersection of the questions they care about and
26
+ those the left and right care about, and this can
27
+ sometimes be vanishingly small.It is not merely a manipulative rhetorical trick to say "if you're
28
+ not with us, you're against us," but often simply false.Moderates are sometimes derided as cowards, particularly by
29
+ the extreme left. But while it may be accurate to call intentional
30
+ moderates cowards, openly being an accidental moderate requires the
31
+ most courage of all, because you get attacked from both right and
32
+ left, and you don't have the comfort of being an orthodox member
33
+ of a large group to sustain you.Nearly all the most impressive people I know are accidental moderates.
34
+ If I knew a lot of professional athletes, or people in the entertainment
35
+ business, that might be different. Being on the far left or far
36
+ right doesn't affect how fast you run or how well you sing. But
37
+ someone who works with ideas has to be independent-minded to do it
38
+ well.Or more precisely, you have to be independent-minded about the ideas
39
+ you work with. You could be mindlessly doctrinaire in your politics
40
+ and still be a good mathematician. In the 20th century, a lot of
41
+ very smart people were Marxists — just no one who was smart about
42
+ the subjects Marxism involves. But if the ideas you use in your
43
+ work intersect with the politics of your time, you have two choices:
44
+ be an accidental moderate, or be mediocre.Notes[1] It's possible in theory for one side to be entirely right and
45
+ the other to be entirely wrong. Indeed, ideologues must always
46
+ believe this is the case. But historically it rarely has been.[2] For some reason the far right tend to ignore moderates rather
47
+ than despise them as backsliders. I'm not sure why. Perhaps it
48
+ means that the far right is less ideological than the far left. Or
49
+ perhaps that they are more confident, or more resigned, or simply
50
+ more disorganized. I just don't know.[3] Having heretical opinions doesn't mean you have to express
51
+ them openly. It may be
52
+ easier to have them if you don't.
53
+ Thanks to Austen Allred, Trevor Blackwell, Patrick Collison, Jessica Livingston,
54
+ Amjad Masad, Ryan Petersen, and Harj Taggar for reading drafts of this.
PaulGrahamEssays/newideas.txt ADDED
@@ -0,0 +1,114 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2021There's one kind of opinion I'd be very afraid to express publicly.
2
+ If someone I knew to be both a domain expert and a reasonable person
3
+ proposed an idea that sounded preposterous, I'd be very reluctant
4
+ to say "That will never work."Anyone who has studied the history of ideas, and especially the
5
+ history of science, knows that's how big things start. Someone
6
+ proposes an idea that sounds crazy, most people dismiss it, then
7
+ it gradually takes over the world.Most implausible-sounding ideas are in fact bad and could be safely
8
+ dismissed. But not when they're proposed by reasonable domain
9
+ experts. If the person proposing the idea is reasonable, then they
10
+ know how implausible it sounds. And yet they're proposing it anyway.
11
+ That suggests they know something you don't. And if they have deep
12
+ domain expertise, that's probably the source of it.
13
+ [1]Such ideas are not merely unsafe to dismiss, but disproportionately
14
+ likely to be interesting. When the average person proposes an
15
+ implausible-sounding idea, its implausibility is evidence of their
16
+ incompetence. But when a reasonable domain expert does it, the
17
+ situation is reversed. There's something like an efficient market
18
+ here: on average the ideas that seem craziest will, if correct,
19
+ have the biggest effect. So if you can eliminate the theory that
20
+ the person proposing an implausible-sounding idea is incompetent,
21
+ its implausibility switches from evidence that it's boring to
22
+ evidence that it's exciting.
23
+ [2]Such ideas are not guaranteed to work. But they don't have to be.
24
+ They just have to be sufficiently good bets — to have sufficiently
25
+ high expected value. And I think on average they do. I think if you
26
+ bet on the entire set of implausible-sounding ideas proposed by
27
+ reasonable domain experts, you'd end up net ahead.The reason is that everyone is too conservative. The word "paradigm"
28
+ is overused, but this is a case where it's warranted. Everyone is
29
+ too much in the grip of the current paradigm. Even the people who
30
+ have the new ideas undervalue them initially. Which means that
31
+ before they reach the stage of proposing them publicly, they've
32
+ already subjected them to an excessively strict filter.
33
+ [3]The wise response to such an idea is not to make statements, but
34
+ to ask questions, because there's a real mystery here. Why has this
35
+ smart and reasonable person proposed an idea that seems so wrong?
36
+ Are they mistaken, or are you? One of you has to be. If you're the
37
+ one who's mistaken, that would be good to know, because it means
38
+ there's a hole in your model of the world. But even if they're
39
+ mistaken, it should be interesting to learn why. A trap that an
40
+ expert falls into is one you have to worry about too.This all seems pretty obvious. And yet there are clearly a lot of
41
+ people who don't share my fear of dismissing new ideas. Why do they
42
+ do it? Why risk looking like a jerk now and a fool later, instead
43
+ of just reserving judgement?One reason they do it is envy. If you propose a radical new idea
44
+ and it succeeds, your reputation (and perhaps also your wealth)
45
+ will increase proportionally. Some people would be envious if that
46
+ happened, and this potential envy propagates back into a conviction
47
+ that you must be wrong.Another reason people dismiss new ideas is that it's an easy way
48
+ to seem sophisticated. When a new idea first emerges, it usually
49
+ seems pretty feeble. It's a mere hatchling. Received wisdom is a
50
+ full-grown eagle by comparison. So it's easy to launch a devastating
51
+ attack on a new idea, and anyone who does will seem clever to those
52
+ who don't understand this asymmetry.This phenomenon is exacerbated by the difference between how those
53
+ working on new ideas and those attacking them are rewarded. The
54
+ rewards for working on new ideas are weighted by the value of the
55
+ outcome. So it's worth working on something that only has a 10%
56
+ chance of succeeding if it would make things more than 10x better.
57
+ Whereas the rewards for attacking new ideas are roughly constant;
58
+ such attacks seem roughly equally clever regardless of the target.People will also attack new ideas when they have a vested interest
59
+ in the old ones. It's not surprising, for example, that some of
60
+ Darwin's harshest critics were churchmen. People build whole careers
61
+ on some ideas. When someone claims they're false or obsolete, they
62
+ feel threatened.The lowest form of dismissal is mere factionalism: to automatically
63
+ dismiss any idea associated with the opposing faction. The lowest
64
+ form of all is to dismiss an idea because of who proposed it.But the main thing that leads reasonable people to dismiss new ideas
65
+ is the same thing that holds people back from proposing them: the
66
+ sheer pervasiveness of the current paradigm. It doesn't just affect
67
+ the way we think; it is the Lego blocks we build thoughts out of.
68
+ Popping out of the current paradigm is something only a few people
69
+ can do. And even they usually have to suppress their intuitions at
70
+ first, like a pilot flying through cloud who has to trust his
71
+ instruments over his sense of balance.
72
+ [4]Paradigms don't just define our present thinking. They also vacuum
73
+ up the trail of crumbs that led to them, making our standards for
74
+ new ideas impossibly high. The current paradigm seems so perfect
75
+ to us, its offspring, that we imagine it must have been accepted
76
+ completely as soon as it was discovered — that whatever the church thought
77
+ of the heliocentric model, astronomers must have been convinced as
78
+ soon as Copernicus proposed it. Far, in fact, from it. Copernicus
79
+ published the heliocentric model in 1532, but it wasn't till the
80
+ mid seventeenth century that the balance of scientific opinion
81
+ shifted in its favor.
82
+ [5]Few understand how feeble new ideas look when they first appear.
83
+ So if you want to have new ideas yourself, one of the most valuable
84
+ things you can do is to learn what they look like when they're born.
85
+ Read about how new ideas happened, and try to get yourself into the
86
+ heads of people at the time. How did things look to them, when the
87
+ new idea was only half-finished, and even the person who had it was
88
+ only half-convinced it was right?But you don't have to stop at history. You can observe big new ideas
89
+ being born all around you right now. Just look for a reasonable
90
+ domain expert proposing something that sounds wrong.If you're nice, as well as wise, you won't merely resist attacking
91
+ such people, but encourage them. Having new ideas is a lonely
92
+ business. Only those who've tried it know how lonely. These people
93
+ need your help. And if you help them, you'll probably learn something
94
+ in the process.Notes[1]
95
+ This domain expertise could be in another field. Indeed,
96
+ such crossovers tend to be particularly promising.[2]
97
+ I'm not claiming this principle extends much beyond math,
98
+ engineering, and the hard sciences. In politics, for example,
99
+ crazy-sounding ideas generally are as bad as they sound. Though
100
+ arguably this is not an exception, because the people who propose
101
+ them are not in fact domain experts; politicians are domain experts
102
+ in political tactics, like how to get elected and how to get
103
+ legislation passed, but not in the world that policy acts upon.
104
+ Perhaps no one could be.[3]
105
+ This sense of "paradigm" was defined by Thomas Kuhn in his
106
+ Structure of Scientific Revolutions, but I also recommend his
107
+ Copernican Revolution, where you can see him at work developing the
108
+ idea.[4]
109
+ This is one reason people with a touch of Asperger's may have
110
+ an advantage in discovering new ideas. They're always flying on
111
+ instruments.[5]
112
+ Hall, Rupert. From Galileo to Newton. Collins, 1963. This
113
+ book is particularly good at getting into contemporaries' heads.Thanks to Trevor Blackwell, Patrick Collison, Suhail Doshi, Daniel
114
+ Gackle, Jessica Livingston, and Robert Morris for reading drafts of this.
PaulGrahamEssays/nft.txt ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2021Noora Health, a nonprofit I've
2
+ supported for years, just launched
3
+ a new NFT. It has a dramatic name, Save Thousands of Lives,
4
+ because that's what the proceeds will do.Noora has been saving lives for 7 years. They run programs in
5
+ hospitals in South Asia to teach new mothers how to take care of
6
+ their babies once they get home. They're in 165 hospitals now. And
7
+ because they know the numbers before and after they start at a new
8
+ hospital, they can measure the impact they have. It is massive.
9
+ For every 1000 live births, they save 9 babies.This number comes from a study
10
+ of 133,733 families at 28 different
11
+ hospitals that Noora conducted in collaboration with the Better
12
+ Birth team at Ariadne Labs, a joint center for health systems
13
+ innovation at Brigham and Women’s Hospital and Harvard T.H. Chan
14
+ School of Public Health.Noora is so effective that even if you measure their costs in the
15
+ most conservative way, by dividing their entire budget by the number
16
+ of lives saved, the cost of saving a life is the lowest I've seen.
17
+ $1,235.For this NFT, they're going to issue a public report tracking how
18
+ this specific tranche of money is spent, and estimating the number
19
+ of lives saved as a result.NFTs are a new territory, and this way of using them is especially
20
+ new, but I'm excited about its potential. And I'm excited to see
21
+ what happens with this particular auction, because unlike an NFT
22
+ representing something that has already happened,
23
+ this NFT gets better as the price gets higher.The reserve price was about $2.5 million, because that's what it
24
+ takes for the name to be accurate: that's what it costs to save
25
+ 2000 lives. But the higher the price of this NFT goes, the more
26
+ lives will be saved. What a sentence to be able to write.
PaulGrahamEssays/philosophy.txt ADDED
@@ -0,0 +1,429 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ September 2007In high school I decided I was going to study philosophy in college.
2
+ I had several motives, some more honorable than others. One of the
3
+ less honorable was to shock people. College was regarded as job
4
+ training where I grew up, so studying philosophy seemed an impressively
5
+ impractical thing to do. Sort of like slashing holes in your clothes
6
+ or putting a safety pin through your ear, which were other forms
7
+ of impressive impracticality then just coming into fashion.But I had some more honest motives as well. I thought studying
8
+ philosophy would be a shortcut straight to wisdom. All the people
9
+ majoring in other things would just end up with a bunch of domain
10
+ knowledge. I would be learning what was really what.I'd tried to read a few philosophy books. Not recent ones; you
11
+ wouldn't find those in our high school library. But I tried to
12
+ read Plato and Aristotle. I doubt I believed I understood them,
13
+ but they sounded like they were talking about something important.
14
+ I assumed I'd learn what in college.The summer before senior year I took some college classes. I learned
15
+ a lot in the calculus class, but I didn't learn much in Philosophy
16
+ 101. And yet my plan to study philosophy remained intact. It was
17
+ my fault I hadn't learned anything. I hadn't read the books we
18
+ were assigned carefully enough. I'd give Berkeley's Principles
19
+ of Human Knowledge another shot in college. Anything so admired
20
+ and so difficult to read must have something in it, if one could
21
+ only figure out what.Twenty-six years later, I still don't understand Berkeley. I have
22
+ a nice edition of his collected works. Will I ever read it? Seems
23
+ unlikely.The difference between then and now is that now I understand why
24
+ Berkeley is probably not worth trying to understand. I think I see
25
+ now what went wrong with philosophy, and how we might fix it.WordsI did end up being a philosophy major for most of college. It
26
+ didn't work out as I'd hoped. I didn't learn any magical truths
27
+ compared to which everything else was mere domain knowledge. But
28
+ I do at least know now why I didn't. Philosophy doesn't really
29
+ have a subject matter in the way math or history or most other
30
+ university subjects do. There is no core of knowledge one must
31
+ master. The closest you come to that is a knowledge of what various
32
+ individual philosophers have said about different topics over the
33
+ years. Few were sufficiently correct that people have forgotten
34
+ who discovered what they discovered.Formal logic has some subject matter. I took several classes in
35
+ logic. I don't know if I learned anything from them.
36
+ [1]
37
+ It does seem to me very important to be able to flip ideas around in
38
+ one's head: to see when two ideas don't fully cover the space of
39
+ possibilities, or when one idea is the same as another but with a
40
+ couple things changed. But did studying logic teach me the importance
41
+ of thinking this way, or make me any better at it? I don't know.There are things I know I learned from studying philosophy. The
42
+ most dramatic I learned immediately, in the first semester of
43
+ freshman year, in a class taught by Sydney Shoemaker. I learned
44
+ that I don't exist. I am (and you are) a collection of cells that
45
+ lurches around driven by various forces, and calls itself I. But
46
+ there's no central, indivisible thing that your identity goes with.
47
+ You could conceivably lose half your brain and live. Which means
48
+ your brain could conceivably be split into two halves and each
49
+ transplanted into different bodies. Imagine waking up after such
50
+ an operation. You have to imagine being two people.The real lesson here is that the concepts we use in everyday life
51
+ are fuzzy, and break down if pushed too hard. Even a concept as
52
+ dear to us as I. It took me a while to grasp this, but when I
53
+ did it was fairly sudden, like someone in the nineteenth century
54
+ grasping evolution and realizing the story of creation they'd been
55
+ told as a child was all wrong.
56
+ [2]
57
+ Outside of math there's a limit
58
+ to how far you can push words; in fact, it would not be a bad
59
+ definition of math to call it the study of terms that have precise
60
+ meanings. Everyday words are inherently imprecise. They work well
61
+ enough in everyday life that you don't notice. Words seem to work,
62
+ just as Newtonian physics seems to. But you can always make them
63
+ break if you push them far enough.I would say that this has been, unfortunately for philosophy, the
64
+ central fact of philosophy. Most philosophical debates are not
65
+ merely afflicted by but driven by confusions over words. Do we
66
+ have free will? Depends what you mean by "free." Do abstract ideas
67
+ exist? Depends what you mean by "exist."Wittgenstein is popularly credited with the idea that most philosophical
68
+ controversies are due to confusions over language. I'm not sure
69
+ how much credit to give him. I suspect a lot of people realized
70
+ this, but reacted simply by not studying philosophy, rather than
71
+ becoming philosophy professors.How did things get this way? Can something people have spent
72
+ thousands of years studying really be a waste of time? Those are
73
+ interesting questions. In fact, some of the most interesting
74
+ questions you can ask about philosophy. The most valuable way to
75
+ approach the current philosophical tradition may be neither to get
76
+ lost in pointless speculations like Berkeley, nor to shut them down
77
+ like Wittgenstein, but to study it as an example of reason gone
78
+ wrong.HistoryWestern philosophy really begins with Socrates, Plato, and Aristotle.
79
+ What we know of their predecessors comes from fragments and references
80
+ in later works; their doctrines could be described as speculative
81
+ cosmology that occasionally strays into analysis. Presumably they
82
+ were driven by whatever makes people in every other society invent
83
+ cosmologies.
84
+ [3]With Socrates, Plato, and particularly Aristotle, this tradition
85
+ turned a corner. There started to be a lot more analysis. I suspect
86
+ Plato and Aristotle were encouraged in this by progress in math.
87
+ Mathematicians had by then shown that you could figure things out
88
+ in a much more conclusive way than by making up fine sounding stories
89
+ about them.
90
+ [4]People talk so much about abstractions now that we don't realize
91
+ what a leap it must have been when they first started to. It was
92
+ presumably many thousands of years between when people first started
93
+ describing things as hot or cold and when someone asked "what is
94
+ heat?" No doubt it was a very gradual process. We don't know if
95
+ Plato or Aristotle were the first to ask any of the questions they
96
+ did. But their works are the oldest we have that do this on a large
97
+ scale, and there is a freshness (not to say naivete) about them
98
+ that suggests some of the questions they asked were new to them,
99
+ at least.Aristotle in particular reminds me of the phenomenon that happens
100
+ when people discover something new, and are so excited by it that
101
+ they race through a huge percentage of the newly discovered territory
102
+ in one lifetime. If so, that's evidence of how new this kind of
103
+ thinking was.
104
+ [5]This is all to explain how Plato and Aristotle can be very impressive
105
+ and yet naive and mistaken. It was impressive even to ask the
106
+ questions they did. That doesn't mean they always came up with
107
+ good answers. It's not considered insulting to say that ancient
108
+ Greek mathematicians were naive in some respects, or at least lacked
109
+ some concepts that would have made their lives easier. So I hope
110
+ people will not be too offended if I propose that ancient philosophers
111
+ were similarly naive. In particular, they don't seem to have fully
112
+ grasped what I earlier called the central fact of philosophy: that
113
+ words break if you push them too far."Much to the surprise of the builders of the first digital computers,"
114
+ Rod Brooks wrote, "programs written for them usually did not work."
115
+ [6]
116
+ Something similar happened when people first started trying
117
+ to talk about abstractions. Much to their surprise, they didn't
118
+ arrive at answers they agreed upon. In fact, they rarely seemed
119
+ to arrive at answers at all.They were in effect arguing about artifacts induced by sampling at
120
+ too low a resolution.The proof of how useless some of their answers turned out to be is
121
+ how little effect they have. No one after reading Aristotle's
122
+ Metaphysics does anything differently as a result.
123
+ [7]Surely I'm not claiming that ideas have to have practical applications
124
+ to be interesting? No, they may not have to. Hardy's boast that
125
+ number theory had no use whatsoever wouldn't disqualify it. But
126
+ he turned out to be mistaken. In fact, it's suspiciously hard to
127
+ find a field of math that truly has no practical use. And Aristotle's
128
+ explanation of the ultimate goal of philosophy in Book A of the
129
+ Metaphysics implies that philosophy should be useful too.Theoretical KnowledgeAristotle's goal was to find the most general of general principles.
130
+ The examples he gives are convincing: an ordinary worker builds
131
+ things a certain way out of habit; a master craftsman can do more
132
+ because he grasps the underlying principles. The trend is clear:
133
+ the more general the knowledge, the more admirable it is. But then
134
+ he makes a mistake—possibly the most important mistake in the
135
+ history of philosophy. He has noticed that theoretical knowledge
136
+ is often acquired for its own sake, out of curiosity, rather than
137
+ for any practical need. So he proposes there are two kinds of
138
+ theoretical knowledge: some that's useful in practical matters and
139
+ some that isn't. Since people interested in the latter are interested
140
+ in it for its own sake, it must be more noble. So he sets as his
141
+ goal in the Metaphysics the exploration of knowledge that has no
142
+ practical use. Which means no alarms go off when he takes on grand
143
+ but vaguely understood questions and ends up getting lost in a sea
144
+ of words.His mistake was to confuse motive and result. Certainly, people
145
+ who want a deep understanding of something are often driven by
146
+ curiosity rather than any practical need. But that doesn't mean
147
+ what they end up learning is useless. It's very valuable in practice
148
+ to have a deep understanding of what you're doing; even if you're
149
+ never called on to solve advanced problems, you can see shortcuts
150
+ in the solution of simple ones, and your knowledge won't break down
151
+ in edge cases, as it would if you were relying on formulas you
152
+ didn't understand. Knowledge is power. That's what makes theoretical
153
+ knowledge prestigious. It's also what causes smart people to be
154
+ curious about certain things and not others; our DNA is not so
155
+ disinterested as we might think.So while ideas don't have to have immediate practical applications
156
+ to be interesting, the kinds of things we find interesting will
157
+ surprisingly often turn out to have practical applications.The reason Aristotle didn't get anywhere in the Metaphysics was
158
+ partly that he set off with contradictory aims: to explore the most
159
+ abstract ideas, guided by the assumption that they were useless.
160
+ He was like an explorer looking for a territory to the north of
161
+ him, starting with the assumption that it was located to the south.And since his work became the map used by generations of future
162
+ explorers, he sent them off in the wrong direction as well.
163
+ [8]
164
+ Perhaps worst of all, he protected them from both the criticism of
165
+ outsiders and the promptings of their own inner compass by establishing
166
+ the principle that the most noble sort of theoretical knowledge had
167
+ to be useless.The Metaphysics is mostly a failed experiment. A few ideas from
168
+ it turned out to be worth keeping; the bulk of it has had no effect
169
+ at all. The Metaphysics is among the least read of all famous
170
+ books. It's not hard to understand the way Newton's Principia
171
+ is, but the way a garbled message is.Arguably it's an interesting failed experiment. But unfortunately
172
+ that was not the conclusion Aristotle's successors derived from
173
+ works like the Metaphysics.
174
+ [9]
175
+ Soon after, the western world
176
+ fell on intellectual hard times. Instead of version 1s to be
177
+ superseded, the works of Plato and Aristotle became revered texts
178
+ to be mastered and discussed. And so things remained for a shockingly
179
+ long time. It was not till around 1600 (in Europe, where the center
180
+ of gravity had shifted by then) that one found people confident
181
+ enough to treat Aristotle's work as a catalog of mistakes. And
182
+ even then they rarely said so outright.If it seems surprising that the gap was so long, consider how little
183
+ progress there was in math between Hellenistic times and the
184
+ Renaissance.In the intervening years an unfortunate idea took hold: that it
185
+ was not only acceptable to produce works like the Metaphysics,
186
+ but that it was a particularly prestigious line of work, done by a
187
+ class of people called philosophers. No one thought to go back and
188
+ debug Aristotle's motivating argument. And so instead of correcting
189
+ the problem Aristotle discovered by falling into it—that you can
190
+ easily get lost if you talk too loosely about very abstract ideas—they
191
+ continued to fall into it.The SingularityCuriously, however, the works they produced continued to attract
192
+ new readers. Traditional philosophy occupies a kind of singularity
193
+ in this respect. If you write in an unclear way about big ideas,
194
+ you produce something that seems tantalizingly attractive to
195
+ inexperienced but intellectually ambitious students. Till one knows
196
+ better, it's hard to distinguish something that's hard to understand
197
+ because the writer was unclear in his own mind from something like
198
+ a mathematical proof that's hard to understand because the ideas
199
+ it represents are hard to understand. To someone who hasn't learned
200
+ the difference, traditional philosophy seems extremely attractive:
201
+ as hard (and therefore impressive) as math, yet broader in scope.
202
+ That was what lured me in as a high school student.This singularity is even more singular in having its own defense
203
+ built in. When things are hard to understand, people who suspect
204
+ they're nonsense generally keep quiet. There's no way to prove a
205
+ text is meaningless. The closest you can get is to show that the
206
+ official judges of some class of texts can't distinguish them from
207
+ placebos.
208
+ [10]And so instead of denouncing philosophy, most people who suspected
209
+ it was a waste of time just studied other things. That alone is
210
+ fairly damning evidence, considering philosophy's claims. It's
211
+ supposed to be about the ultimate truths. Surely all smart people
212
+ would be interested in it, if it delivered on that promise.Because philosophy's flaws turned away the sort of people who might
213
+ have corrected them, they tended to be self-perpetuating. Bertrand
214
+ Russell wrote in a letter in 1912:
215
+
216
+ Hitherto the people attracted to philosophy have been mostly those
217
+ who loved the big generalizations, which were all wrong, so that
218
+ few people with exact minds have taken up the subject.
219
+ [11]
220
+
221
+ His response was to launch Wittgenstein at it, with dramatic results.I think Wittgenstein deserves to be famous not for the discovery
222
+ that most previous philosophy was a waste of time, which judging
223
+ from the circumstantial evidence must have been made by every smart
224
+ person who studied a little philosophy and declined to pursue it
225
+ further, but for how he acted in response.
226
+ [12]
227
+ Instead of quietly
228
+ switching to another field, he made a fuss, from inside. He was
229
+ Gorbachev.The field of philosophy is still shaken from the fright Wittgenstein
230
+ gave it.
231
+ [13]
232
+ Later in life he spent a lot of time talking about
233
+ how words worked. Since that seems to be allowed, that's what a
234
+ lot of philosophers do now. Meanwhile, sensing a vacuum in the
235
+ metaphysical speculation department, the people who used to do
236
+ literary criticism have been edging Kantward, under new names like
237
+ "literary theory," "critical theory," and when they're feeling
238
+ ambitious, plain "theory." The writing is the familiar word salad:
239
+
240
+ Gender is not like some of the other grammatical modes which
241
+ express precisely a mode of conception without any reality that
242
+ corresponds to the conceptual mode, and consequently do not express
243
+ precisely something in reality by which the intellect could be
244
+ moved to conceive a thing the way it does, even where that motive
245
+ is not something in the thing as such.
246
+ [14]
247
+
248
+ The singularity I've described is not going away. There's a market
249
+ for writing that sounds impressive and can't be disproven. There
250
+ will always be both supply and demand. So if one group abandons
251
+ this territory, there will always be others ready to occupy it.A ProposalWe may be able to do better. Here's an intriguing possibility.
252
+ Perhaps we should do what Aristotle meant to do, instead of what
253
+ he did. The goal he announces in the Metaphysics seems one worth
254
+ pursuing: to discover the most general truths. That sounds good.
255
+ But instead of trying to discover them because they're useless,
256
+ let's try to discover them because they're useful.I propose we try again, but that we use that heretofore despised
257
+ criterion, applicability, as a guide to keep us from wondering
258
+ off into a swamp of abstractions. Instead of trying to answer the
259
+ question:
260
+
261
+ What are the most general truths?
262
+
263
+ let's try to answer the question
264
+
265
+ Of all the useful things we can say, which are the most general?
266
+
267
+ The test of utility I propose is whether we cause people who read
268
+ what we've written to do anything differently afterward. Knowing
269
+ we have to give definite (if implicit) advice will keep us from
270
+ straying beyond the resolution of the words we're using.The goal is the same as Aristotle's; we just approach it from a
271
+ different direction.As an example of a useful, general idea, consider that of the
272
+ controlled experiment. There's an idea that has turned out to be
273
+ widely applicable. Some might say it's part of science, but it's
274
+ not part of any specific science; it's literally meta-physics (in
275
+ our sense of "meta"). The idea of evolution is another. It turns
276
+ out to have quite broad applications—for example, in genetic
277
+ algorithms and even product design. Frankfurt's distinction between
278
+ lying and bullshitting seems a promising recent example.
279
+ [15]These seem to me what philosophy should look like: quite general
280
+ observations that would cause someone who understood them to do
281
+ something differently.Such observations will necessarily be about things that are imprecisely
282
+ defined. Once you start using words with precise meanings, you're
283
+ doing math. So starting from utility won't entirely solve the
284
+ problem I described above—it won't flush out the metaphysical
285
+ singularity. But it should help. It gives people with good
286
+ intentions a new roadmap into abstraction. And they may thereby
287
+ produce things that make the writing of the people with bad intentions
288
+ look bad by comparison.One drawback of this approach is that it won't produce the sort of
289
+ writing that gets you tenure. And not just because it's not currently
290
+ the fashion. In order to get tenure in any field you must not
291
+ arrive at conclusions that members of tenure committees can disagree
292
+ with. In practice there are two kinds of solutions to this problem.
293
+ In math and the sciences, you can prove what you're saying, or at
294
+ any rate adjust your conclusions so you're not claiming anything
295
+ false ("6 of 8 subjects had lower blood pressure after the treatment").
296
+ In the humanities you can either avoid drawing any definite conclusions
297
+ (e.g. conclude that an issue is a complex one), or draw conclusions
298
+ so narrow that no one cares enough to disagree with you.The kind of philosophy I'm advocating won't be able to take either
299
+ of these routes. At best you'll be able to achieve the essayist's
300
+ standard of proof, not the mathematician's or the experimentalist's.
301
+ And yet you won't be able to meet the usefulness test without
302
+ implying definite and fairly broadly applicable conclusions. Worse
303
+ still, the usefulness test will tend to produce results that annoy
304
+ people: there's no use in telling people things they already believe,
305
+ and people are often upset to be told things they don't.Here's the exciting thing, though. Anyone can do this. Getting
306
+ to general plus useful by starting with useful and cranking up the
307
+ generality may be unsuitable for junior professors trying to get
308
+ tenure, but it's better for everyone else, including professors who
309
+ already have it. This side of the mountain is a nice gradual slope.
310
+ You can start by writing things that are useful but very specific,
311
+ and then gradually make them more general. Joe's has good burritos.
312
+ What makes a good burrito? What makes good food? What makes
313
+ anything good? You can take as long as you want. You don't have
314
+ to get all the way to the top of the mountain. You don't have to
315
+ tell anyone you're doing philosophy.If it seems like a daunting task to do philosophy, here's an
316
+ encouraging thought. The field is a lot younger than it seems.
317
+ Though the first philosophers in the western tradition lived about
318
+ 2500 years ago, it would be misleading to say the field is 2500
319
+ years old, because for most of that time the leading practitioners
320
+ weren't doing much more than writing commentaries on Plato or
321
+ Aristotle while watching over their shoulders for the next invading
322
+ army. In the times when they weren't, philosophy was hopelessly
323
+ intermingled with religion. It didn't shake itself free till a
324
+ couple hundred years ago, and even then was afflicted by the
325
+ structural problems I've described above. If I say this, some will
326
+ say it's a ridiculously overbroad and uncharitable generalization,
327
+ and others will say it's old news, but here goes: judging from their
328
+ works, most philosophers up to the present have been wasting their
329
+ time. So in a sense the field is still at the first step.
330
+ [16]That sounds a preposterous claim to make. It won't seem so
331
+ preposterous in 10,000 years. Civilization always seems old, because
332
+ it's always the oldest it's ever been. The only way to say whether
333
+ something is really old or not is by looking at structural evidence,
334
+ and structurally philosophy is young; it's still reeling from the
335
+ unexpected breakdown of words.Philosophy is as young now as math was in 1500. There is a lot
336
+ more to discover.Notes
337
+ [1]
338
+ In practice formal logic is not much use, because despite
339
+ some progress in the last 150 years we're still only able to formalize
340
+ a small percentage of statements. We may never do that much better,
341
+ for the same reason 1980s-style "knowledge representation" could
342
+ never have worked; many statements may have no representation more
343
+ concise than a huge, analog brain state.[2]
344
+ It was harder for Darwin's contemporaries to grasp this than
345
+ we can easily imagine. The story of creation in the Bible is not
346
+ just a Judeo-Christian concept; it's roughly what everyone must
347
+ have believed since before people were people. The hard part of
348
+ grasping evolution was to realize that species weren't, as they
349
+ seem to be, unchanging, but had instead evolved from different,
350
+ simpler organisms over unimaginably long periods of time.Now we don't have to make that leap. No one in an industrialized
351
+ country encounters the idea of evolution for the first time as an
352
+ adult. Everyone's taught about it as a child, either as truth or
353
+ heresy.[3]
354
+ Greek philosophers before Plato wrote in verse. This must
355
+ have affected what they said. If you try to write about the nature
356
+ of the world in verse, it inevitably turns into incantation. Prose
357
+ lets you be more precise, and more tentative.[4]
358
+ Philosophy is like math's
359
+ ne'er-do-well brother. It was born when Plato and Aristotle looked
360
+ at the works of their predecessors and said in effect "why can't
361
+ you be more like your brother?" Russell was still saying the same
362
+ thing 2300 years later.Math is the precise half of the most abstract ideas, and philosophy
363
+ the imprecise half. It's probably inevitable that philosophy will
364
+ suffer by comparison, because there's no lower bound to its precision.
365
+ Bad math is merely boring, whereas bad philosophy is nonsense. And
366
+ yet there are some good ideas in the imprecise half.[5]
367
+ Aristotle's best work was in logic and zoology, both of which
368
+ he can be said to have invented. But the most dramatic departure
369
+ from his predecessors was a new, much more analytical style of
370
+ thinking. He was arguably the first scientist.[6]
371
+ Brooks, Rodney, Programming in Common Lisp, Wiley, 1985, p.
372
+ 94.[7]
373
+ Some would say we depend on Aristotle more than we realize,
374
+ because his ideas were one of the ingredients in our common culture.
375
+ Certainly a lot of the words we use have a connection with Aristotle,
376
+ but it seems a bit much to suggest that we wouldn't have the concept
377
+ of the essence of something or the distinction between matter and
378
+ form if Aristotle hadn't written about them.One way to see how much we really depend on Aristotle would be to
379
+ diff European culture with Chinese: what ideas did European culture
380
+ have in 1800 that Chinese culture didn't, in virtue of Aristotle's
381
+ contribution?[8]
382
+ The meaning of the word "philosophy" has changed over time.
383
+ In ancient times it covered a broad range of topics, comparable in
384
+ scope to our "scholarship" (though without the methodological
385
+ implications). Even as late as Newton's time it included what we
386
+ now call "science." But core of the subject today is still what
387
+ seemed to Aristotle the core: the attempt to discover the most
388
+ general truths.Aristotle didn't call this "metaphysics." That name got assigned
389
+ to it because the books we now call the Metaphysics came after
390
+ (meta = after) the Physics in the standard edition of Aristotle's
391
+ works compiled by Andronicus of Rhodes three centuries later. What
392
+ we call "metaphysics" Aristotle called "first philosophy."[9]
393
+ Some of Aristotle's immediate successors may have realized
394
+ this, but it's hard to say because most of their works are lost.[10]
395
+ Sokal, Alan, "Transgressing the Boundaries: Toward a Transformative
396
+ Hermeneutics of Quantum Gravity," Social Text 46/47, pp. 217-252.Abstract-sounding nonsense seems to be most attractive when it's
397
+ aligned with some axe the audience already has to grind. If this
398
+ is so we should find it's most popular with groups that are (or
399
+ feel) weak. The powerful don't need its reassurance.[11]
400
+ Letter to Ottoline Morrell, December 1912. Quoted in:Monk, Ray, Ludwig Wittgenstein: The Duty of Genius, Penguin, 1991,
401
+ p. 75.[12]
402
+ A preliminary result, that all metaphysics between Aristotle
403
+ and 1783 had been a waste of time, is due to I. Kant.[13]
404
+ Wittgenstein asserted a sort of mastery to which the inhabitants
405
+ of early 20th century Cambridge seem to have been peculiarly
406
+ vulnerable—perhaps partly because so many had been raised religious
407
+ and then stopped believing, so had a vacant space in their heads
408
+ for someone to tell them what to do (others chose Marx or Cardinal
409
+ Newman), and partly because a quiet, earnest place like Cambridge
410
+ in that era had no natural immunity to messianic figures, just as
411
+ European politics then had no natural immunity to dictators.[14]
412
+ This is actually from the Ordinatio of Duns Scotus (ca.
413
+ 1300), with "number" replaced by "gender." Plus ca change.Wolter, Allan (trans), Duns Scotus: Philosophical Writings, Nelson,
414
+ 1963, p. 92.[15]
415
+ Frankfurt, Harry, On Bullshit, Princeton University Press,
416
+ 2005.[16]
417
+ Some introductions to philosophy now take the line that
418
+ philosophy is worth studying as a process rather than for any
419
+ particular truths you'll learn. The philosophers whose works they
420
+ cover would be rolling in their graves at that. They hoped they
421
+ were doing more than serving as examples of how to argue: they hoped
422
+ they were getting results. Most were wrong, but it doesn't seem
423
+ an impossible hope.This argument seems to me like someone in 1500 looking at the lack
424
+ of results achieved by alchemy and saying its value was as a process.
425
+ No, they were going about it wrong. It turns out it is possible
426
+ to transmute lead into gold (though not economically at current
427
+ energy prices), but the route to that knowledge was to
428
+ backtrack and try another approach.Thanks to Trevor Blackwell, Paul Buchheit, Jessica Livingston,
429
+ Robert Morris, Mark Nitzberg, and Peter Norvig for reading drafts of this.
PaulGrahamEssays/popular.txt ADDED
@@ -0,0 +1,602 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2001(This article was written as a kind of business plan for a
2
+ new language.
3
+ So it is missing (because it takes for granted) the most important
4
+ feature of a good programming language: very powerful abstractions.)A friend of mine once told an eminent operating systems
5
+ expert that he wanted to design a really good
6
+ programming language. The expert told him that it would be a
7
+ waste of time, that programming languages don't become popular
8
+ or unpopular based on their merits, and so no matter how
9
+ good his language was, no one would use it. At least, that
10
+ was what had happened to the language he had designed.What does make a language popular? Do popular
11
+ languages deserve their popularity? Is it worth trying to
12
+ define a good programming language? How would you do it?I think the answers to these questions can be found by looking
13
+ at hackers, and learning what they want. Programming
14
+ languages are for hackers, and a programming language
15
+ is good as a programming language (rather than, say, an
16
+ exercise in denotational semantics or compiler design)
17
+ if and only if hackers like it.1 The Mechanics of PopularityIt's true, certainly, that most people don't choose programming
18
+ languages simply based on their merits. Most programmers are told
19
+ what language to use by someone else. And yet I think the effect
20
+ of such external factors on the popularity of programming languages
21
+ is not as great as it's sometimes thought to be. I think a bigger
22
+ problem is that a hacker's idea of a good programming language is
23
+ not the same as most language designers'.Between the two, the hacker's opinion is the one that matters.
24
+ Programming languages are not theorems. They're tools, designed
25
+ for people, and they have to be designed to suit human strengths
26
+ and weaknesses as much as shoes have to be designed for human feet.
27
+ If a shoe pinches when you put it on, it's a bad shoe, however
28
+ elegant it may be as a piece of sculpture.It may be that the majority of programmers can't tell a good language
29
+ from a bad one. But that's no different with any other tool. It
30
+ doesn't mean that it's a waste of time to try designing a good
31
+ language. Expert hackers
32
+ can tell a good language when they see
33
+ one, and they'll use it. Expert hackers are a tiny minority,
34
+ admittedly, but that tiny minority write all the good software,
35
+ and their influence is such that the rest of the programmers will
36
+ tend to use whatever language they use. Often, indeed, it is not
37
+ merely influence but command: often the expert hackers are the very
38
+ people who, as their bosses or faculty advisors, tell the other
39
+ programmers what language to use.The opinion of expert hackers is not the only force that determines
40
+ the relative popularity of programming languages — legacy software
41
+ (Cobol) and hype (Ada, Java) also play a role — but I think it is
42
+ the most powerful force over the long term. Given an initial critical
43
+ mass and enough time, a programming language probably becomes about
44
+ as popular as it deserves to be. And popularity further separates
45
+ good languages from bad ones, because feedback from real live users
46
+ always leads to improvements. Look at how much any popular language
47
+ has changed during its life. Perl and Fortran are extreme cases,
48
+ but even Lisp has changed a lot. Lisp 1.5 didn't have macros, for
49
+ example; these evolved later, after hackers at MIT had spent a
50
+ couple years using Lisp to write real programs. [1]So whether or not a language has to be good to be popular, I think
51
+ a language has to be popular to be good. And it has to stay popular
52
+ to stay good. The state of the art in programming languages doesn't
53
+ stand still. And yet the Lisps we have today are still pretty much
54
+ what they had at MIT in the mid-1980s, because that's the last time
55
+ Lisp had a sufficiently large and demanding user base.Of course, hackers have to know about a language before they can
56
+ use it. How are they to hear? From other hackers. But there has to
57
+ be some initial group of hackers using the language for others even
58
+ to hear about it. I wonder how large this group has to be; how many
59
+ users make a critical mass? Off the top of my head, I'd say twenty.
60
+ If a language had twenty separate users, meaning twenty users who
61
+ decided on their own to use it, I'd consider it to be real.Getting there can't be easy. I would not be surprised if it is
62
+ harder to get from zero to twenty than from twenty to a thousand.
63
+ The best way to get those initial twenty users is probably to use
64
+ a trojan horse: to give people an application they want, which
65
+ happens to be written in the new language.2 External FactorsLet's start by acknowledging one external factor that does affect
66
+ the popularity of a programming language. To become popular, a
67
+ programming language has to be the scripting language of a popular
68
+ system. Fortran and Cobol were the scripting languages of early
69
+ IBM mainframes. C was the scripting language of Unix, and so, later,
70
+ was Perl. Tcl is the scripting language of Tk. Java and Javascript
71
+ are intended to be the scripting languages of web browsers.Lisp is not a massively popular language because it is not the
72
+ scripting language of a massively popular system. What popularity
73
+ it retains dates back to the 1960s and 1970s, when it was the
74
+ scripting language of MIT. A lot of the great programmers of the
75
+ day were associated with MIT at some point. And in the early 1970s,
76
+ before C, MIT's dialect of Lisp, called MacLisp, was one of the
77
+ only programming languages a serious hacker would want to use.Today Lisp is the scripting language of two moderately popular
78
+ systems, Emacs and Autocad, and for that reason I suspect that most
79
+ of the Lisp programming done today is done in Emacs Lisp or AutoLisp.Programming languages don't exist in isolation. To hack is a
80
+ transitive verb — hackers are usually hacking something — and in
81
+ practice languages are judged relative to whatever they're used to
82
+ hack. So if you want to design a popular language, you either have
83
+ to supply more than a language, or you have to design your language
84
+ to replace the scripting language of some existing system.Common Lisp is unpopular partly because it's an orphan. It did
85
+ originally come with a system to hack: the Lisp Machine. But Lisp
86
+ Machines (along with parallel computers) were steamrollered by the
87
+ increasing power of general purpose processors in the 1980s. Common
88
+ Lisp might have remained popular if it had been a good scripting
89
+ language for Unix. It is, alas, an atrociously bad one.One way to describe this situation is to say that a language isn't
90
+ judged on its own merits. Another view is that a programming language
91
+ really isn't a programming language unless it's also the scripting
92
+ language of something. This only seems unfair if it comes as a
93
+ surprise. I think it's no more unfair than expecting a programming
94
+ language to have, say, an implementation. It's just part of what
95
+ a programming language is.A programming language does need a good implementation, of course,
96
+ and this must be free. Companies will pay for software, but individual
97
+ hackers won't, and it's the hackers you need to attract.A language also needs to have a book about it. The book should be
98
+ thin, well-written, and full of good examples. K&R is the ideal
99
+ here. At the moment I'd almost say that a language has to have a
100
+ book published by O'Reilly. That's becoming the test of mattering
101
+ to hackers.There should be online documentation as well. In fact, the book
102
+ can start as online documentation. But I don't think that physical
103
+ books are outmoded yet. Their format is convenient, and the de
104
+ facto censorship imposed by publishers is a useful if imperfect
105
+ filter. Bookstores are one of the most important places for learning
106
+ about new languages.3 BrevityGiven that you can supply the three things any language needs — a
107
+ free implementation, a book, and something to hack — how do you
108
+ make a language that hackers will like?One thing hackers like is brevity. Hackers are lazy, in the same
109
+ way that mathematicians and modernist architects are lazy: they
110
+ hate anything extraneous. It would not be far from the truth to
111
+ say that a hacker about to write a program decides what language
112
+ to use, at least subconsciously, based on the total number of
113
+ characters he'll have to type. If this isn't precisely how hackers
114
+ think, a language designer would do well to act as if it were.It is a mistake to try to baby the user with long-winded expressions
115
+ that are meant to resemble English. Cobol is notorious for this
116
+ flaw. A hacker would consider being asked to writeadd x to y giving zinstead ofz = x+yas something between an insult to his intelligence and a sin against
117
+ God.It has sometimes been said that Lisp should use first and rest
118
+ instead of car and cdr, because it would make programs easier to
119
+ read. Maybe for the first couple hours. But a hacker can learn
120
+ quickly enough that car means the first element of a list and cdr
121
+ means the rest. Using first and rest means 50% more typing. And
122
+ they are also different lengths, meaning that the arguments won't
123
+ line up when they're called, as car and cdr often are, in successive
124
+ lines. I've found that it matters a lot how code lines up on the
125
+ page. I can barely read Lisp code when it is set in a variable-width
126
+ font, and friends say this is true for other languages too.Brevity is one place where strongly typed languages lose. All other
127
+ things being equal, no one wants to begin a program with a bunch
128
+ of declarations. Anything that can be implicit, should be.The individual tokens should be short as well. Perl and Common Lisp
129
+ occupy opposite poles on this question. Perl programs can be almost
130
+ cryptically dense, while the names of built-in Common Lisp operators
131
+ are comically long. The designers of Common Lisp probably expected
132
+ users to have text editors that would type these long names for
133
+ them. But the cost of a long name is not just the cost of typing
134
+ it. There is also the cost of reading it, and the cost of the space
135
+ it takes up on your screen.4 HackabilityThere is one thing more important than brevity to a hacker: being
136
+ able to do what you want. In the history of programming languages
137
+ a surprising amount of effort has gone into preventing programmers
138
+ from doing things considered to be improper. This is a dangerously
139
+ presumptuous plan. How can the language designer know what the
140
+ programmer is going to need to do? I think language designers would
141
+ do better to consider their target user to be a genius who will
142
+ need to do things they never anticipated, rather than a bumbler
143
+ who needs to be protected from himself. The bumbler will shoot
144
+ himself in the foot anyway. You may save him from referring to
145
+ variables in another package, but you can't save him from writing
146
+ a badly designed program to solve the wrong problem, and taking
147
+ forever to do it.Good programmers often want to do dangerous and unsavory things.
148
+ By unsavory I mean things that go behind whatever semantic facade
149
+ the language is trying to present: getting hold of the internal
150
+ representation of some high-level abstraction, for example. Hackers
151
+ like to hack, and hacking means getting inside things and second
152
+ guessing the original designer.Let yourself be second guessed. When you make any tool, people use
153
+ it in ways you didn't intend, and this is especially true of a
154
+ highly articulated tool like a programming language. Many a hacker
155
+ will want to tweak your semantic model in a way that you never
156
+ imagined. I say, let them; give the programmer access to as much
157
+ internal stuff as you can without endangering runtime systems like
158
+ the garbage collector.In Common Lisp I have often wanted to iterate through the fields
159
+ of a struct — to comb out references to a deleted object, for example,
160
+ or find fields that are uninitialized. I know the structs are just
161
+ vectors underneath. And yet I can't write a general purpose function
162
+ that I can call on any struct. I can only access the fields by
163
+ name, because that's what a struct is supposed to mean.A hacker may only want to subvert the intended model of things once
164
+ or twice in a big program. But what a difference it makes to be
165
+ able to. And it may be more than a question of just solving a
166
+ problem. There is a kind of pleasure here too. Hackers share the
167
+ surgeon's secret pleasure in poking about in gross innards, the
168
+ teenager's secret pleasure in popping zits. [2] For boys, at least,
169
+ certain kinds of horrors are fascinating. Maxim magazine publishes
170
+ an annual volume of photographs, containing a mix of pin-ups and
171
+ grisly accidents. They know their audience.Historically, Lisp has been good at letting hackers have their way.
172
+ The political correctness of Common Lisp is an aberration. Early
173
+ Lisps let you get your hands on everything. A good deal of that
174
+ spirit is, fortunately, preserved in macros. What a wonderful thing,
175
+ to be able to make arbitrary transformations on the source code.Classic macros are a real hacker's tool — simple, powerful, and
176
+ dangerous. It's so easy to understand what they do: you call a
177
+ function on the macro's arguments, and whatever it returns gets
178
+ inserted in place of the macro call. Hygienic macros embody the
179
+ opposite principle. They try to protect you from understanding what
180
+ they're doing. I have never heard hygienic macros explained in one
181
+ sentence. And they are a classic example of the dangers of deciding
182
+ what programmers are allowed to want. Hygienic macros are intended
183
+ to protect me from variable capture, among other things, but variable
184
+ capture is exactly what I want in some macros.A really good language should be both clean and dirty: cleanly
185
+ designed, with a small core of well understood and highly orthogonal
186
+ operators, but dirty in the sense that it lets hackers have their
187
+ way with it. C is like this. So were the early Lisps. A real hacker's
188
+ language will always have a slightly raffish character.A good programming language should have features that make the kind
189
+ of people who use the phrase "software engineering" shake their
190
+ heads disapprovingly. At the other end of the continuum are languages
191
+ like Ada and Pascal, models of propriety that are good for teaching
192
+ and not much else.5 Throwaway ProgramsTo be attractive to hackers, a language must be good for writing
193
+ the kinds of programs they want to write. And that means, perhaps
194
+ surprisingly, that it has to be good for writing throwaway programs.A throwaway program is a program you write quickly for some limited
195
+ task: a program to automate some system administration task, or
196
+ generate test data for a simulation, or convert data from one format
197
+ to another. The surprising thing about throwaway programs is that,
198
+ like the "temporary" buildings built at so many American universities
199
+ during World War II, they often don't get thrown away. Many evolve
200
+ into real programs, with real features and real users.I have a hunch that the best big programs begin life this way,
201
+ rather than being designed big from the start, like the Hoover Dam.
202
+ It's terrifying to build something big from scratch. When people
203
+ take on a project that's too big, they become overwhelmed. The
204
+ project either gets bogged down, or the result is sterile and
205
+ wooden: a shopping mall rather than a real downtown, Brasilia rather
206
+ than Rome, Ada rather than C.Another way to get a big program is to start with a throwaway
207
+ program and keep improving it. This approach is less daunting, and
208
+ the design of the program benefits from evolution. I think, if one
209
+ looked, that this would turn out to be the way most big programs
210
+ were developed. And those that did evolve this way are probably
211
+ still written in whatever language they were first written in,
212
+ because it's rare for a program to be ported, except for political
213
+ reasons. And so, paradoxically, if you want to make a language that
214
+ is used for big systems, you have to make it good for writing
215
+ throwaway programs, because that's where big systems come from.Perl is a striking example of this idea. It was not only designed
216
+ for writing throwaway programs, but was pretty much a throwaway
217
+ program itself. Perl began life as a collection of utilities for
218
+ generating reports, and only evolved into a programming language
219
+ as the throwaway programs people wrote in it grew larger. It was
220
+ not until Perl 5 (if then) that the language was suitable for
221
+ writing serious programs, and yet it was already massively popular.What makes a language good for throwaway programs? To start with,
222
+ it must be readily available. A throwaway program is something that
223
+ you expect to write in an hour. So the language probably must
224
+ already be installed on the computer you're using. It can't be
225
+ something you have to install before you use it. It has to be there.
226
+ C was there because it came with the operating system. Perl was
227
+ there because it was originally a tool for system administrators,
228
+ and yours had already installed it.Being available means more than being installed, though. An
229
+ interactive language, with a command-line interface, is more
230
+ available than one that you have to compile and run separately. A
231
+ popular programming language should be interactive, and start up
232
+ fast.Another thing you want in a throwaway program is brevity. Brevity
233
+ is always attractive to hackers, and never more so than in a program
234
+ they expect to turn out in an hour.6 LibrariesOf course the ultimate in brevity is to have the program already
235
+ written for you, and merely to call it. And this brings us to what
236
+ I think will be an increasingly important feature of programming
237
+ languages: library functions. Perl wins because it has large
238
+ libraries for manipulating strings. This class of library functions
239
+ are especially important for throwaway programs, which are often
240
+ originally written for converting or extracting data. Many Perl
241
+ programs probably begin as just a couple library calls stuck
242
+ together.I think a lot of the advances that happen in programming languages
243
+ in the next fifty years will have to do with library functions. I
244
+ think future programming languages will have libraries that are as
245
+ carefully designed as the core language. Programming language design
246
+ will not be about whether to make your language strongly or weakly
247
+ typed, or object oriented, or functional, or whatever, but about
248
+ how to design great libraries. The kind of language designers who
249
+ like to think about how to design type systems may shudder at this.
250
+ It's almost like writing applications! Too bad. Languages are for
251
+ programmers, and libraries are what programmers need.It's hard to design good libraries. It's not simply a matter of
252
+ writing a lot of code. Once the libraries get too big, it can
253
+ sometimes take longer to find the function you need than to write
254
+ the code yourself. Libraries need to be designed using a small set
255
+ of orthogonal operators, just like the core language. It ought to
256
+ be possible for the programmer to guess what library call will do
257
+ what he needs.Libraries are one place Common Lisp falls short. There are only
258
+ rudimentary libraries for manipulating strings, and almost none
259
+ for talking to the operating system. For historical reasons, Common
260
+ Lisp tries to pretend that the OS doesn't exist. And because you
261
+ can't talk to the OS, you're unlikely to be able to write a serious
262
+ program using only the built-in operators in Common Lisp. You have
263
+ to use some implementation-specific hacks as well, and in practice
264
+ these tend not to give you everything you want. Hackers would think
265
+ a lot more highly of Lisp if Common Lisp had powerful string
266
+ libraries and good OS support.7 SyntaxCould a language with Lisp's syntax, or more precisely, lack of
267
+ syntax, ever become popular? I don't know the answer to this
268
+ question. I do think that syntax is not the main reason Lisp isn't
269
+ currently popular. Common Lisp has worse problems than unfamiliar
270
+ syntax. I know several programmers who are comfortable with prefix
271
+ syntax and yet use Perl by default, because it has powerful string
272
+ libraries and can talk to the os.There are two possible problems with prefix notation: that it is
273
+ unfamiliar to programmers, and that it is not dense enough. The
274
+ conventional wisdom in the Lisp world is that the first problem is
275
+ the real one. I'm not so sure. Yes, prefix notation makes ordinary
276
+ programmers panic. But I don't think ordinary programmers' opinions
277
+ matter. Languages become popular or unpopular based on what expert
278
+ hackers think of them, and I think expert hackers might be able to
279
+ deal with prefix notation. Perl syntax can be pretty incomprehensible,
280
+ but that has not stood in the way of Perl's popularity. If anything
281
+ it may have helped foster a Perl cult.A more serious problem is the diffuseness of prefix notation. For
282
+ expert hackers, that really is a problem. No one wants to write
283
+ (aref a x y) when they could write a[x,y].In this particular case there is a way to finesse our way out of
284
+ the problem. If we treat data structures as if they were functions
285
+ on indexes, we could write (a x y) instead, which is even shorter
286
+ than the Perl form. Similar tricks may shorten other types of
287
+ expressions.We can get rid of (or make optional) a lot of parentheses by making
288
+ indentation significant. That's how programmers read code anyway:
289
+ when indentation says one thing and delimiters say another, we go
290
+ by the indentation. Treating indentation as significant would
291
+ eliminate this common source of bugs as well as making programs
292
+ shorter.Sometimes infix syntax is easier to read. This is especially true
293
+ for math expressions. I've used Lisp my whole programming life and
294
+ I still don't find prefix math expressions natural. And yet it is
295
+ convenient, especially when you're generating code, to have operators
296
+ that take any number of arguments. So if we do have infix syntax,
297
+ it should probably be implemented as some kind of read-macro.I don't think we should be religiously opposed to introducing syntax
298
+ into Lisp, as long as it translates in a well-understood way into
299
+ underlying s-expressions. There is already a good deal of syntax
300
+ in Lisp. It's not necessarily bad to introduce more, as long as no
301
+ one is forced to use it. In Common Lisp, some delimiters are reserved
302
+ for the language, suggesting that at least some of the designers
303
+ intended to have more syntax in the future.One of the most egregiously unlispy pieces of syntax in Common Lisp
304
+ occurs in format strings; format is a language in its own right,
305
+ and that language is not Lisp. If there were a plan for introducing
306
+ more syntax into Lisp, format specifiers might be able to be included
307
+ in it. It would be a good thing if macros could generate format
308
+ specifiers the way they generate any other kind of code.An eminent Lisp hacker told me that his copy of CLTL falls open to
309
+ the section format. Mine too. This probably indicates room for
310
+ improvement. It may also mean that programs do a lot of I/O.8 EfficiencyA good language, as everyone knows, should generate fast code. But
311
+ in practice I don't think fast code comes primarily from things
312
+ you do in the design of the language. As Knuth pointed out long
313
+ ago, speed only matters in certain critical bottlenecks. And as
314
+ many programmers have observed since, one is very often mistaken
315
+ about where these bottlenecks are.So, in practice, the way to get fast code is to have a very good
316
+ profiler, rather than by, say, making the language strongly typed.
317
+ You don't need to know the type of every argument in every call in
318
+ the program. You do need to be able to declare the types of arguments
319
+ in the bottlenecks. And even more, you need to be able to find out
320
+ where the bottlenecks are.One complaint people have had with Lisp is that it's hard to tell
321
+ what's expensive. This might be true. It might also be inevitable,
322
+ if you want to have a very abstract language. And in any case I
323
+ think good profiling would go a long way toward fixing the problem:
324
+ you'd soon learn what was expensive.Part of the problem here is social. Language designers like to
325
+ write fast compilers. That's how they measure their skill. They
326
+ think of the profiler as an add-on, at best. But in practice a good
327
+ profiler may do more to improve the speed of actual programs written
328
+ in the language than a compiler that generates fast code. Here,
329
+ again, language designers are somewhat out of touch with their
330
+ users. They do a really good job of solving slightly the wrong
331
+ problem.It might be a good idea to have an active profiler — to push
332
+ performance data to the programmer instead of waiting for him to
333
+ come asking for it. For example, the editor could display bottlenecks
334
+ in red when the programmer edits the source code. Another approach
335
+ would be to somehow represent what's happening in running programs.
336
+ This would be an especially big win in server-based applications,
337
+ where you have lots of running programs to look at. An active
338
+ profiler could show graphically what's happening in memory as a
339
+ program's running, or even make sounds that tell what's happening.Sound is a good cue to problems. In one place I worked, we had a
340
+ big board of dials showing what was happening to our web servers.
341
+ The hands were moved by little servomotors that made a slight noise
342
+ when they turned. I couldn't see the board from my desk, but I
343
+ found that I could tell immediately, by the sound, when there was
344
+ a problem with a server.It might even be possible to write a profiler that would automatically
345
+ detect inefficient algorithms. I would not be surprised if certain
346
+ patterns of memory access turned out to be sure signs of bad
347
+ algorithms. If there were a little guy running around inside the
348
+ computer executing our programs, he would probably have as long
349
+ and plaintive a tale to tell about his job as a federal government
350
+ employee. I often have a feeling that I'm sending the processor on
351
+ a lot of wild goose chases, but I've never had a good way to look
352
+ at what it's doing.A number of Lisps now compile into byte code, which is then executed
353
+ by an interpreter. This is usually done to make the implementation
354
+ easier to port, but it could be a useful language feature. It might
355
+ be a good idea to make the byte code an official part of the
356
+ language, and to allow programmers to use inline byte code in
357
+ bottlenecks. Then such optimizations would be portable too.The nature of speed, as perceived by the end-user, may be changing.
358
+ With the rise of server-based applications, more and more programs
359
+ may turn out to be i/o-bound. It will be worth making i/o fast.
360
+ The language can help with straightforward measures like simple,
361
+ fast, formatted output functions, and also with deep structural
362
+ changes like caching and persistent objects.Users are interested in response time. But another kind of efficiency
363
+ will be increasingly important: the number of simultaneous users
364
+ you can support per processor. Many of the interesting applications
365
+ written in the near future will be server-based, and the number of
366
+ users per server is the critical question for anyone hosting such
367
+ applications. In the capital cost of a business offering a server-based
368
+ application, this is the divisor.For years, efficiency hasn't mattered much in most end-user
369
+ applications. Developers have been able to assume that each user
370
+ would have an increasingly powerful processor sitting on their
371
+ desk. And by Parkinson's Law, software has expanded to use the
372
+ resources available. That will change with server-based applications.
373
+ In that world, the hardware and software will be supplied together.
374
+ For companies that offer server-based applications, it will make
375
+ a very big difference to the bottom line how many users they can
376
+ support per server.In some applications, the processor will be the limiting factor,
377
+ and execution speed will be the most important thing to optimize.
378
+ But often memory will be the limit; the number of simultaneous
379
+ users will be determined by the amount of memory you need for each
380
+ user's data. The language can help here too. Good support for
381
+ threads will enable all the users to share a single heap. It may
382
+ also help to have persistent objects and/or language level support
383
+ for lazy loading.9 TimeThe last ingredient a popular language needs is time. No one wants
384
+ to write programs in a language that might go away, as so many
385
+ programming languages do. So most hackers will tend to wait until
386
+ a language has been around for a couple years before even considering
387
+ using it.Inventors of wonderful new things are often surprised to discover
388
+ this, but you need time to get any message through to people. A
389
+ friend of mine rarely does anything the first time someone asks
390
+ him. He knows that people sometimes ask for things that they turn
391
+ out not to want. To avoid wasting his time, he waits till the third
392
+ or fourth time he's asked to do something; by then, whoever's asking
393
+ him may be fairly annoyed, but at least they probably really do
394
+ want whatever they're asking for.Most people have learned to do a similar sort of filtering on new
395
+ things they hear about. They don't even start paying attention
396
+ until they've heard about something ten times. They're perfectly
397
+ justified: the majority of hot new whatevers do turn out to be a
398
+ waste of time, and eventually go away. By delaying learning VRML,
399
+ I avoided having to learn it at all.So anyone who invents something new has to expect to keep repeating
400
+ their message for years before people will start to get it. We
401
+ wrote what was, as far as I know, the first web-server based
402
+ application, and it took us years to get it through to people that
403
+ it didn't have to be downloaded. It wasn't that they were stupid.
404
+ They just had us tuned out.The good news is, simple repetition solves the problem. All you
405
+ have to do is keep telling your story, and eventually people will
406
+ start to hear. It's not when people notice you're there that they
407
+ pay attention; it's when they notice you're still there.It's just as well that it usually takes a while to gain momentum.
408
+ Most technologies evolve a good deal even after they're first
409
+ launched — programming languages especially. Nothing could be better,
410
+ for a new techology, than a few years of being used only by a small
411
+ number of early adopters. Early adopters are sophisticated and
412
+ demanding, and quickly flush out whatever flaws remain in your
413
+ technology. When you only have a few users you can be in close
414
+ contact with all of them. And early adopters are forgiving when
415
+ you improve your system, even if this causes some breakage.There are two ways new technology gets introduced: the organic
416
+ growth method, and the big bang method. The organic growth method
417
+ is exemplified by the classic seat-of-the-pants underfunded garage
418
+ startup. A couple guys, working in obscurity, develop some new
419
+ technology. They launch it with no marketing and initially have
420
+ only a few (fanatically devoted) users. They continue to improve
421
+ the technology, and meanwhile their user base grows by word of
422
+ mouth. Before they know it, they're big.The other approach, the big bang method, is exemplified by the
423
+ VC-backed, heavily marketed startup. They rush to develop a product,
424
+ launch it with great publicity, and immediately (they hope) have
425
+ a large user base.Generally, the garage guys envy the big bang guys. The big bang
426
+ guys are smooth and confident and respected by the VCs. They can
427
+ afford the best of everything, and the PR campaign surrounding the
428
+ launch has the side effect of making them celebrities. The organic
429
+ growth guys, sitting in their garage, feel poor and unloved. And
430
+ yet I think they are often mistaken to feel sorry for themselves.
431
+ Organic growth seems to yield better technology and richer founders
432
+ than the big bang method. If you look at the dominant technologies
433
+ today, you'll find that most of them grew organically.This pattern doesn't only apply to companies. You see it in sponsored
434
+ research too. Multics and Common Lisp were big-bang projects, and
435
+ Unix and MacLisp were organic growth projects.10 Redesign"The best writing is rewriting," wrote E. B. White. Every good
436
+ writer knows this, and it's true for software too. The most important
437
+ part of design is redesign. Programming languages, especially,
438
+ don't get redesigned enough.To write good software you must simultaneously keep two opposing
439
+ ideas in your head. You need the young hacker's naive faith in
440
+ his abilities, and at the same time the veteran's skepticism. You
441
+ have to be able to think
442
+ how hard can it be? with one half of
443
+ your brain while thinking
444
+ it will never work with the other.The trick is to realize that there's no real contradiction here.
445
+ You want to be optimistic and skeptical about two different things.
446
+ You have to be optimistic about the possibility of solving the
447
+ problem, but skeptical about the value of whatever solution you've
448
+ got so far.People who do good work often think that whatever they're working
449
+ on is no good. Others see what they've done and are full of wonder,
450
+ but the creator is full of worry. This pattern is no coincidence:
451
+ it is the worry that made the work good.If you can keep hope and worry balanced, they will drive a project
452
+ forward the same way your two legs drive a bicycle forward. In the
453
+ first phase of the two-cycle innovation engine, you work furiously
454
+ on some problem, inspired by your confidence that you'll be able
455
+ to solve it. In the second phase, you look at what you've done in
456
+ the cold light of morning, and see all its flaws very clearly. But
457
+ as long as your critical spirit doesn't outweigh your hope, you'll
458
+ be able to look at your admittedly incomplete system, and think,
459
+ how hard can it be to get the rest of the way?, thereby continuing
460
+ the cycle.It's tricky to keep the two forces balanced. In young hackers,
461
+ optimism predominates. They produce something, are convinced it's
462
+ great, and never improve it. In old hackers, skepticism predominates,
463
+ and they won't even dare to take on ambitious projects.Anything you can do to keep the redesign cycle going is good. Prose
464
+ can be rewritten over and over until you're happy with it. But
465
+ software, as a rule, doesn't get redesigned enough. Prose has
466
+ readers, but software has users. If a writer rewrites an essay,
467
+ people who read the old version are unlikely to complain that their
468
+ thoughts have been broken by some newly introduced incompatibility.Users are a double-edged sword. They can help you improve your
469
+ language, but they can also deter you from improving it. So choose
470
+ your users carefully, and be slow to grow their number. Having
471
+ users is like optimization: the wise course is to delay it. Also,
472
+ as a general rule, you can at any given time get away with changing
473
+ more than you think. Introducing change is like pulling off a
474
+ bandage: the pain is a memory almost as soon as you feel it.Everyone knows that it's not a good idea to have a language designed
475
+ by a committee. Committees yield bad design. But I think the worst
476
+ danger of committees is that they interfere with redesign. It is
477
+ so much work to introduce changes that no one wants to bother.
478
+ Whatever a committee decides tends to stay that way, even if most
479
+ of the members don't like it.Even a committee of two gets in the way of redesign. This happens
480
+ particularly in the interfaces between pieces of software written
481
+ by two different people. To change the interface both have to agree
482
+ to change it at once. And so interfaces tend not to change at all,
483
+ which is a problem because they tend to be one of the most ad hoc
484
+ parts of any system.One solution here might be to design systems so that interfaces
485
+ are horizontal instead of vertical — so that modules are always
486
+ vertically stacked strata of abstraction. Then the interface will
487
+ tend to be owned by one of them. The lower of two levels will either
488
+ be a language in which the upper is written, in which case the
489
+ lower level will own the interface, or it will be a slave, in which
490
+ case the interface can be dictated by the upper level.11 LispWhat all this implies is that there is hope for a new Lisp. There
491
+ is hope for any language that gives hackers what they want, including
492
+ Lisp. I think we may have made a mistake in thinking that hackers
493
+ are turned off by Lisp's strangeness. This comforting illusion may
494
+ have prevented us from seeing the real problem with Lisp, or at
495
+ least Common Lisp, which is that it sucks for doing what hackers
496
+ want to do. A hacker's language needs powerful libraries and
497
+ something to hack. Common Lisp has neither. A hacker's language is
498
+ terse and hackable. Common Lisp is not.The good news is, it's not Lisp that sucks, but Common Lisp. If we
499
+ can develop a new Lisp that is a real hacker's language, I think
500
+ hackers will use it. They will use whatever language does the job.
501
+ All we have to do is make sure this new Lisp does some important
502
+ job better than other languages.History offers some encouragement. Over time, successive new
503
+ programming languages have taken more and more features from Lisp.
504
+ There is no longer much left to copy before the language you've
505
+ made is Lisp. The latest hot language, Python, is a watered-down
506
+ Lisp with infix syntax and no macros. A new Lisp would be a natural
507
+ step in this progression.I sometimes think that it would be a good marketing trick to call
508
+ it an improved version of Python. That sounds hipper than Lisp. To
509
+ many people, Lisp is a slow AI language with a lot of parentheses.
510
+ Fritz Kunze's official biography carefully avoids mentioning the
511
+ L-word. But my guess is that we shouldn't be afraid to call the
512
+ new Lisp Lisp. Lisp still has a lot of latent respect among the
513
+ very best hackers — the ones who took 6.001 and understood it, for
514
+ example. And those are the users you need to win.In "How to Become a Hacker," Eric Raymond describes Lisp as something
515
+ like Latin or Greek — a language you should learn as an intellectual
516
+ exercise, even though you won't actually use it:
517
+
518
+ Lisp is worth learning for the profound enlightenment experience
519
+ you will have when you finally get it; that experience will make
520
+ you a better programmer for the rest of your days, even if you
521
+ never actually use Lisp itself a lot.
522
+
523
+ If I didn't know Lisp, reading this would set me asking questions.
524
+ A language that would make me a better programmer, if it means
525
+ anything at all, means a language that would be better for programming.
526
+ And that is in fact the implication of what Eric is saying.As long as that idea is still floating around, I think hackers will
527
+ be receptive enough to a new Lisp, even if it is called Lisp. But
528
+ this Lisp must be a hacker's language, like the classic Lisps of
529
+ the 1970s. It must be terse, simple, and hackable. And it must have
530
+ powerful libraries for doing what hackers want to do now.In the matter of libraries I think there is room to beat languages
531
+ like Perl and Python at their own game. A lot of the new applications
532
+ that will need to be written in the coming years will be
533
+ server-based
534
+ applications. There's no reason a new Lisp shouldn't have string
535
+ libraries as good as Perl, and if this new Lisp also had powerful
536
+ libraries for server-based applications, it could be very popular.
537
+ Real hackers won't turn up their noses at a new tool that will let
538
+ them solve hard problems with a few library calls. Remember, hackers
539
+ are lazy.It could be an even bigger win to have core language support for
540
+ server-based applications. For example, explicit support for programs
541
+ with multiple users, or data ownership at the level of type tags.Server-based applications also give us the answer to the question
542
+ of what this new Lisp will be used to hack. It would not hurt to
543
+ make Lisp better as a scripting language for Unix. (It would be
544
+ hard to make it worse.) But I think there are areas where existing
545
+ languages would be easier to beat. I think it might be better to
546
+ follow the model of Tcl, and supply the Lisp together with a complete
547
+ system for supporting server-based applications. Lisp is a natural
548
+ fit for server-based applications. Lexical closures provide a way
549
+ to get the effect of subroutines when the ui is just a series of
550
+ web pages. S-expressions map nicely onto html, and macros are good
551
+ at generating it. There need to be better tools for writing
552
+ server-based applications, and there needs to be a new Lisp, and
553
+ the two would work very well together.12 The Dream LanguageBy way of summary, let's try describing the hacker's dream language.
554
+ The dream language is
555
+ beautiful, clean, and terse. It has an
556
+ interactive toplevel that starts up fast. You can write programs
557
+ to solve common problems with very little code. Nearly all the
558
+ code in any program you write is code that's specific to your
559
+ application. Everything else has been done for you.The syntax of the language is brief to a fault. You never have to
560
+ type an unnecessary character, or even to use the shift key much.Using big abstractions you can write the first version of a program
561
+ very quickly. Later, when you want to optimize, there's a really
562
+ good profiler that tells you where to focus your attention. You
563
+ can make inner loops blindingly fast, even writing inline byte code
564
+ if you need to.There are lots of good examples to learn from, and the language is
565
+ intuitive enough that you can learn how to use it from examples in
566
+ a couple minutes. You don't need to look in the manual much. The
567
+ manual is thin, and has few warnings and qualifications.The language has a small core, and powerful, highly orthogonal
568
+ libraries that are as carefully designed as the core language. The
569
+ libraries all work well together; everything in the language fits
570
+ together like the parts in a fine camera. Nothing is deprecated,
571
+ or retained for compatibility. The source code of all the libraries
572
+ is readily available. It's easy to talk to the operating system
573
+ and to applications written in other languages.The language is built in layers. The higher-level abstractions are
574
+ built in a very transparent way out of lower-level abstractions,
575
+ which you can get hold of if you want.Nothing is hidden from you that doesn't absolutely have to be. The
576
+ language offers abstractions only as a way of saving you work,
577
+ rather than as a way of telling you what to do. In fact, the language
578
+ encourages you to be an equal participant in its design. You can
579
+ change everything about it, including even its syntax, and anything
580
+ you write has, as much as possible, the same status as what comes
581
+ predefined.Notes[1] Macros very close to the modern idea were proposed by Timothy
582
+ Hart in 1964, two years after Lisp 1.5 was released. What was
583
+ missing, initially, were ways to avoid variable capture and multiple
584
+ evaluation; Hart's examples are subject to both.[2] In When the Air Hits Your Brain, neurosurgeon Frank Vertosick
585
+ recounts a conversation in which his chief resident, Gary, talks
586
+ about the difference between surgeons and internists ("fleas"):
587
+
588
+ Gary and I ordered a large pizza and found an open booth. The
589
+ chief lit a cigarette. "Look at those goddamn fleas, jabbering
590
+ about some disease they'll see once in their lifetimes. That's
591
+ the trouble with fleas, they only like the bizarre stuff. They
592
+ hate their bread and butter cases. That's the difference between
593
+ us and the fucking fleas. See, we love big juicy lumbar disc
594
+ herniations, but they hate hypertension...."
595
+
596
+ It's hard to think of a lumbar disc herniation as juicy (except
597
+ literally). And yet I think I know what they mean. I've often had
598
+ a juicy bug to track down. Someone who's not a programmer would
599
+ find it hard to imagine that there could be pleasure in a bug.
600
+ Surely it's better if everything just works. In one way, it is.
601
+ And yet there is undeniably a grim satisfaction in hunting down
602
+ certain sorts of bugs.
PaulGrahamEssays/pow.txt ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
1
+ January 2017People who are powerful but uncharismatic will tend to be disliked.
2
+ Their power makes them a target for criticism that they don't have
3
+ the charisma to disarm. That was Hillary Clinton's problem. It also
4
+ tends to be a problem for any CEO who is more of a builder than a
5
+ schmoozer. And yet the builder-type CEO is (like Hillary) probably
6
+ the best person for the job.I don't think there is any solution to this problem. It's human
7
+ nature. The best we can do is to recognize that it's happening, and
8
+ to understand that being a magnet for criticism is sometimes a sign
9
+ not that someone is the wrong person for a job, but that they're
10
+ the right one.
PaulGrahamEssays/rootsoflisp.txt ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2001
2
+
3
+ (I wrote this article to help myself understand exactly
4
+ what McCarthy discovered. You don't need to know this stuff
5
+ to program in Lisp, but it should be helpful to
6
+ anyone who wants to
7
+ understand the essence of Lisp — both in the sense of its
8
+ origins and its semantic core. The fact that it has such a core
9
+ is one of Lisp's distinguishing features, and the reason why,
10
+ unlike other languages, Lisp has dialects.)In 1960, John
11
+ McCarthy published a remarkable paper in
12
+ which he did for programming something like what Euclid did for
13
+ geometry. He showed how, given a handful of simple
14
+ operators and a notation for functions, you can
15
+ build a whole programming language.
16
+ He called this language Lisp, for "List Processing,"
17
+ because one of his key ideas was to use a simple
18
+ data structure called a list for both
19
+ code and data.It's worth understanding what McCarthy discovered, not
20
+ just as a landmark in the history of computers, but as
21
+ a model for what programming is tending to become in
22
+ our own time. It seems to me that there have been
23
+ two really clean, consistent models of programming so
24
+ far: the C model and the Lisp model.
25
+ These two seem points of high ground, with swampy lowlands
26
+ between them. As computers have grown more powerful,
27
+ the new languages being developed have been moving
28
+ steadily toward the Lisp model. A popular recipe
29
+ for new programming languages in the past 20 years
30
+ has been to take the C model of computing and add to
31
+ it, piecemeal, parts taken from the Lisp model,
32
+ like runtime typing and garbage collection.In this article I'm going to try to explain in the
33
+ simplest possible terms what McCarthy discovered.
34
+ The point is not just to learn about an interesting
35
+ theoretical result someone figured out forty years ago,
36
+ but to show where languages are heading.
37
+ The unusual thing about Lisp — in fact, the defining
38
+ quality of Lisp — is that it can be written in
39
+ itself. To understand what McCarthy meant by this,
40
+ we're going to retrace his steps, with his mathematical
41
+ notation translated into running Common Lisp code.
PaulGrahamEssays/rss.txt ADDED
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1
+ Aaron Swartz created a scraped
2
+ feed
3
+ of the essays page.
PaulGrahamEssays/siliconvalley.txt ADDED
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1
+ May 2006(This essay is derived from a keynote at Xtech.)Could you reproduce Silicon Valley elsewhere, or is there something
2
+ unique about it?It wouldn't be surprising if it were hard to reproduce in other
3
+ countries, because you couldn't reproduce it in most of the US
4
+ either. What does it take to make a silicon valley even here?What it takes is the right people. If you could get the right ten
5
+ thousand people to move from Silicon Valley to Buffalo, Buffalo
6
+ would become Silicon Valley.
7
+ [1]That's a striking departure from the past. Up till a couple decades
8
+ ago, geography was destiny for cities. All great cities were located
9
+ on waterways, because cities made money by trade, and water was the
10
+ only economical way to ship.Now you could make a great city anywhere, if you could get the right
11
+ people to move there. So the question of how to make a silicon
12
+ valley becomes: who are the right people, and how do you get them
13
+ to move?Two TypesI think you only need two kinds of people to create a technology
14
+ hub: rich people and nerds. They're the limiting reagents in the
15
+ reaction that produces startups, because they're the only ones
16
+ present when startups get started. Everyone else will move.Observation bears this out: within the US, towns have become startup
17
+ hubs if and only if they have both rich people and nerds. Few
18
+ startups happen in Miami, for example, because although it's full
19
+ of rich people, it has few nerds. It's not the kind of place nerds
20
+ like.Whereas Pittsburgh has the opposite problem: plenty of nerds, but
21
+ no rich people. The top US Computer Science departments are said
22
+ to be MIT, Stanford, Berkeley, and Carnegie-Mellon. MIT yielded
23
+ Route 128. Stanford and Berkeley yielded Silicon Valley. But
24
+ Carnegie-Mellon? The record skips at that point. Lower down the
25
+ list, the University of Washington yielded a high-tech community
26
+ in Seattle, and the University of Texas at Austin yielded one in
27
+ Austin. But what happened in Pittsburgh? And in Ithaca, home of
28
+ Cornell, which is also high on the list?I grew up in Pittsburgh and went to college at Cornell, so I can
29
+ answer for both. The weather is terrible, particularly in winter,
30
+ and there's no interesting old city to make up for it, as there is
31
+ in Boston. Rich people don't want to live in Pittsburgh or Ithaca.
32
+ So while there are plenty of hackers who could start startups,
33
+ there's no one to invest in them.Not BureaucratsDo you really need the rich people? Wouldn't it work to have the
34
+ government invest in the nerds? No, it would not. Startup investors
35
+ are a distinct type of rich people. They tend to have a lot of
36
+ experience themselves in the technology business. This (a) helps
37
+ them pick the right startups, and (b) means they can supply advice
38
+ and connections as well as money. And the fact that they have a
39
+ personal stake in the outcome makes them really pay attention.Bureaucrats by their nature are the exact opposite sort of people
40
+ from startup investors. The idea of them making startup investments
41
+ is comic. It would be like mathematicians running Vogue-- or
42
+ perhaps more accurately, Vogue editors running a math journal.
43
+ [2]Though indeed, most things bureaucrats do, they do badly. We just
44
+ don't notice usually, because they only have to compete against
45
+ other bureaucrats. But as startup investors they'd have to compete
46
+ against pros with a great deal more experience and motivation.Even corporations that have in-house VC groups generally forbid
47
+ them to make their own investment decisions. Most are only allowed
48
+ to invest in deals where some reputable private VC firm is willing
49
+ to act as lead investor.Not BuildingsIf you go to see Silicon Valley, what you'll see are buildings.
50
+ But it's the people that make it Silicon Valley, not the buildings.
51
+ I read occasionally about attempts to set up "technology
52
+ parks" in other places, as if the active ingredient of Silicon
53
+ Valley were the office space. An article about Sophia Antipolis
54
+ bragged that companies there included Cisco, Compaq, IBM, NCR, and
55
+ Nortel. Don't the French realize these aren't startups?Building office buildings for technology companies won't get you a
56
+ silicon valley, because the key stage in the life of a startup
57
+ happens before they want that kind of space. The key stage is when
58
+ they're three guys operating out of an apartment. Wherever the
59
+ startup is when it gets funded, it will stay. The defining quality
60
+ of Silicon Valley is not that Intel or Apple or Google have offices
61
+ there, but that they were started there.So if you want to reproduce Silicon Valley, what you need to reproduce
62
+ is those two or three founders sitting around a kitchen table
63
+ deciding to start a company. And to reproduce that you need those
64
+ people.UniversitiesThe exciting thing is, all you need are the people. If you could
65
+ attract a critical mass of nerds and investors to live somewhere,
66
+ you could reproduce Silicon Valley. And both groups are highly
67
+ mobile. They'll go where life is good. So what makes a place good
68
+ to them?What nerds like is other nerds. Smart people will go wherever other
69
+ smart people are. And in particular, to great universities. In
70
+ theory there could be other ways to attract them, but so far
71
+ universities seem to be indispensable. Within the US, there are
72
+ no technology hubs without first-rate universities-- or at least,
73
+ first-rate computer science departments.So if you want to make a silicon valley, you not only need a
74
+ university, but one of the top handful in the world. It has to be
75
+ good enough to act as a magnet, drawing the best people from thousands
76
+ of miles away. And that means it has to stand up to existing magnets
77
+ like MIT and Stanford.This sounds hard. Actually it might be easy. My professor friends,
78
+ when they're deciding where they'd like to work, consider one thing
79
+ above all: the quality of the other faculty. What attracts professors
80
+ is good colleagues. So if you managed to recruit, en masse, a
81
+ significant number of the best young researchers, you could create
82
+ a first-rate university from nothing overnight. And you could do
83
+ that for surprisingly little. If you paid 200 people hiring bonuses
84
+ of $3 million apiece, you could put together a faculty that would
85
+ bear comparison with any in the world. And from that point the
86
+ chain reaction would be self-sustaining. So whatever it costs to
87
+ establish a mediocre university, for an additional half billion or
88
+ so you could have a great one.
89
+ [3]PersonalityHowever, merely creating a new university would not be enough to
90
+ start a silicon valley. The university is just the seed. It has
91
+ to be planted in the right soil, or it won't germinate. Plant it
92
+ in the wrong place, and you just create Carnegie-Mellon.To spawn startups, your university has to be in a town that has
93
+ attractions other than the university. It has to be a place where
94
+ investors want to live, and students want to stay after they graduate.The two like much the same things, because most startup investors
95
+ are nerds themselves. So what do nerds look for in a town? Their
96
+ tastes aren't completely different from other people's, because a
97
+ lot of the towns they like most in the US are also big tourist
98
+ destinations: San Francisco, Boston, Seattle. But their tastes
99
+ can't be quite mainstream either, because they dislike other big
100
+ tourist destinations, like New York, Los Angeles, and Las Vegas.There has been a lot written lately about the "creative class." The
101
+ thesis seems to be that as wealth derives increasingly from ideas,
102
+ cities will prosper only if they attract those who have them. That
103
+ is certainly true; in fact it was the basis of Amsterdam's prosperity
104
+ 400 years ago.A lot of nerd tastes they share with the creative class in general.
105
+ For example, they like well-preserved old neighborhoods instead of
106
+ cookie-cutter suburbs, and locally-owned shops and restaurants
107
+ instead of national chains. Like the rest of the creative class,
108
+ they want to live somewhere with personality.What exactly is personality? I think it's the feeling that each
109
+ building is the work of a distinct group of people. A town with
110
+ personality is one that doesn't feel mass-produced. So if you want
111
+ to make a startup hub-- or any town to attract the "creative class"--
112
+ you probably have to ban large development projects.
113
+ When a large tract has been developed by a single organization, you
114
+ can always tell.
115
+ [4]Most towns with personality are old, but they don't have to be.
116
+ Old towns have two advantages: they're denser, because they were
117
+ laid out before cars, and they're more varied, because they were
118
+ built one building at a time. You could have both now. Just have
119
+ building codes that ensure density, and ban large scale developments.A corollary is that you have to keep out the biggest developer of
120
+ all: the government. A government that asks "How can we build a
121
+ silicon valley?" has probably ensured failure by the way they framed
122
+ the question. You don't build a silicon valley; you let one grow.NerdsIf you want to attract nerds, you need more than a town with
123
+ personality. You need a town with the right personality. Nerds
124
+ are a distinct subset of the creative class, with different tastes
125
+ from the rest. You can see this most clearly in New York, which
126
+ attracts a lot of creative people, but few nerds.
127
+ [5]What nerds like is the kind of town where people walk around smiling.
128
+ This excludes LA, where no one walks at all, and also New York,
129
+ where people walk, but not smiling. When I was in grad school in
130
+ Boston, a friend came to visit from New York. On the subway back
131
+ from the airport she asked "Why is everyone smiling?" I looked and
132
+ they weren't smiling. They just looked like they were compared to
133
+ the facial expressions she was used to.If you've lived in New York, you know where these facial expressions
134
+ come from. It's the kind of place where your mind may be excited,
135
+ but your body knows it's having a bad time. People don't so much
136
+ enjoy living there as endure it for the sake of the excitement.
137
+ And if you like certain kinds of excitement, New York is incomparable.
138
+ It's a hub of glamour, a magnet for all the shorter half-life
139
+ isotopes of style and fame.Nerds don't care about glamour, so to them the appeal of New York
140
+ is a mystery. People who like New York will pay a fortune for a
141
+ small, dark, noisy apartment in order to live in a town where the
142
+ cool people are really cool. A nerd looks at that deal and sees
143
+ only: pay a fortune for a small, dark, noisy apartment.Nerds will pay a premium to live in a town where the smart people
144
+ are really smart, but you don't have to pay as much for that. It's
145
+ supply and demand: glamour is popular, so you have to pay a lot for
146
+ it.Most nerds like quieter pleasures. They like cafes instead of
147
+ clubs; used bookshops instead of fashionable clothing shops; hiking
148
+ instead of dancing; sunlight instead of tall buildings. A nerd's
149
+ idea of paradise is Berkeley or Boulder.YouthIt's the young nerds who start startups, so it's those specifically
150
+ the city has to appeal to. The startup hubs in the US are all
151
+ young-feeling towns. This doesn't mean they have to be new.
152
+ Cambridge has the oldest town plan in America, but it feels young
153
+ because it's full of students.What you can't have, if you want to create a silicon valley, is a
154
+ large, existing population of stodgy people. It would be a waste
155
+ of time to try to reverse the fortunes of a declining industrial town
156
+ like Detroit or Philadelphia by trying to encourage startups. Those
157
+ places have too much momentum in the wrong direction. You're better
158
+ off starting with a blank slate in the form of a small town. Or
159
+ better still, if there's a town young people already flock to, that
160
+ one.The Bay Area was a magnet for the young and optimistic for decades
161
+ before it was associated with technology. It was a place people
162
+ went in search of something new. And so it became synonymous with
163
+ California nuttiness. There's still a lot of that there. If you
164
+ wanted to start a new fad-- a new way to focus one's "energy," for
165
+ example, or a new category of things not to eat-- the Bay Area would
166
+ be the place to do it. But a place that tolerates oddness in the
167
+ search for the new is exactly what you want in a startup hub, because
168
+ economically that's what startups are. Most good startup ideas
169
+ seem a little crazy; if they were obviously good ideas, someone
170
+ would have done them already.(How many people are going to want computers in their houses?
171
+ What, another search engine?)That's the connection between technology and liberalism. Without
172
+ exception the high-tech cities in the US are also the most liberal.
173
+ But it's not because liberals are smarter that this is so. It's
174
+ because liberal cities tolerate odd ideas, and smart people by
175
+ definition have odd ideas.Conversely, a town that gets praised for being "solid" or representing
176
+ "traditional values" may be a fine place to live, but it's never
177
+ going to succeed as a startup hub. The 2004 presidential election,
178
+ though a disaster in other respects, conveniently supplied us with
179
+ a county-by-county
180
+ map of such places.
181
+ [6]To attract the young, a town must have an intact center. In most
182
+ American cities the center has been abandoned, and the growth, if
183
+ any, is in the suburbs. Most American cities have been turned
184
+ inside out. But none of the startup hubs has: not San Francisco,
185
+ or Boston, or Seattle. They all have intact centers.
186
+ [7]
187
+ My guess is that no city with a dead center could be turned into a
188
+ startup hub. Young people don't want to live in the suburbs.Within the US, the two cities I think could most easily be turned
189
+ into new silicon valleys are Boulder and Portland. Both have the
190
+ kind of effervescent feel that attracts the young. They're each
191
+ only a great university short of becoming a silicon valley, if they
192
+ wanted to.TimeA great university near an attractive town. Is that all it takes?
193
+ That was all it took to make the original Silicon Valley. Silicon
194
+ Valley traces its origins to William Shockley, one of the inventors
195
+ of the transistor. He did the research that won him the Nobel Prize
196
+ at Bell Labs, but when he started his own company in 1956 he moved
197
+ to Palo Alto to do it. At the time that was an odd thing to do.
198
+ Why did he? Because he had grown up there and remembered how nice
199
+ it was. Now Palo Alto is suburbia, but then it was a charming
200
+ college town-- a charming college town with perfect weather and San
201
+ Francisco only an hour away.The companies that rule Silicon Valley now are all descended in
202
+ various ways from Shockley Semiconductor. Shockley was a difficult
203
+ man, and in 1957 his top people-- "the traitorous eight"-- left to
204
+ start a new company, Fairchild Semiconductor. Among them were
205
+ Gordon Moore and Robert Noyce, who went on to found Intel, and
206
+ Eugene Kleiner, who founded the VC firm Kleiner Perkins. Forty-two
207
+ years later, Kleiner Perkins funded Google, and the partner responsible
208
+ for the deal was John Doerr, who came to Silicon Valley in 1974 to
209
+ work for Intel.So although a lot of the newest companies in Silicon Valley don't
210
+ make anything out of silicon, there always seem to be multiple links
211
+ back to Shockley. There's a lesson here: startups beget startups.
212
+ People who work for startups start their own. People who get rich
213
+ from startups fund new ones. I suspect this kind of organic growth
214
+ is the only way to produce a startup hub, because it's the only way
215
+ to grow the expertise you need.That has two important implications. The first is that you need
216
+ time to grow a silicon valley. The university you could create in
217
+ a couple years, but the startup community around it has to grow
218
+ organically. The cycle time is limited by the time it takes a
219
+ company to succeed, which probably averages about five years.The other implication of the organic growth hypothesis is that you
220
+ can't be somewhat of a startup hub. You either have a self-sustaining
221
+ chain reaction, or not. Observation confirms this too: cities
222
+ either have a startup scene, or they don't. There is no middle
223
+ ground. Chicago has the third largest metropolitan area in America.
224
+ As source of startups it's negligible compared to Seattle, number 15.The good news is that the initial seed can be quite small. Shockley
225
+ Semiconductor, though itself not very successful, was big enough.
226
+ It brought a critical mass of experts in an important new technology
227
+ together in a place they liked enough to stay.CompetingOf course, a would-be silicon valley faces an obstacle the original
228
+ one didn't: it has to compete with Silicon Valley. Can that be
229
+ done? Probably.One of Silicon Valley's biggest advantages is its venture capital
230
+ firms. This was not a factor in Shockley's day, because VC funds
231
+ didn't exist. In fact, Shockley Semiconductor and Fairchild
232
+ Semiconductor were not startups at all in our sense. They were
233
+ subsidiaries-- of Beckman Instruments and Fairchild Camera and
234
+ Instrument respectively. Those companies were apparently willing
235
+ to establish subsidiaries wherever the experts wanted to live.Venture investors, however, prefer to fund startups within an hour's
236
+ drive. For one, they're more likely to notice startups nearby.
237
+ But when they do notice startups in other towns they prefer them
238
+ to move. They don't want to have to travel to attend board meetings,
239
+ and in any case the odds of succeeding are higher in a startup hub.The centralizing effect of venture firms is a double one: they cause
240
+ startups to form around them, and those draw in more startups through
241
+ acquisitions. And although the first may be weakening because it's
242
+ now so cheap to start some startups, the second seems as strong as ever.
243
+ Three of the most admired
244
+ "Web 2.0" companies were started outside the usual startup hubs,
245
+ but two of them have already been reeled in through acquisitions.Such centralizing forces make it harder for new silicon valleys to
246
+ get started. But by no means impossible. Ultimately power rests
247
+ with the founders. A startup with the best people will beat one
248
+ with funding from famous VCs, and a startup that was sufficiently
249
+ successful would never have to move. So a town that
250
+ could exert enough pull over the right people could resist and
251
+ perhaps even surpass Silicon Valley.For all its power, Silicon Valley has a great weakness: the paradise
252
+ Shockley found in 1956 is now one giant parking lot. San Francisco
253
+ and Berkeley are great, but they're forty miles away. Silicon
254
+ Valley proper is soul-crushing suburban sprawl. It
255
+ has fabulous weather, which makes it significantly better than the
256
+ soul-crushing sprawl of most other American cities. But a competitor
257
+ that managed to avoid sprawl would have real leverage. All a city
258
+ needs is to be the kind of place the next traitorous eight look at
259
+ and say "I want to stay here," and that would be enough to get the
260
+ chain reaction started.Notes[1]
261
+ It's interesting to consider how low this number could be
262
+ made. I suspect five hundred would be enough, even if they could
263
+ bring no assets with them. Probably just thirty, if I could pick them,
264
+ would be enough to turn Buffalo into a significant startup hub.[2]
265
+ Bureaucrats manage to allocate research funding moderately
266
+ well, but only because (like an in-house VC fund) they outsource
267
+ most of the work of selection. A professor at a famous university
268
+ who is highly regarded by his peers will get funding, pretty much
269
+ regardless of the proposal. That wouldn't work for startups, whose
270
+ founders aren't sponsored by organizations, and are often unknowns.[3]
271
+ You'd have to do it all at once, or at least a whole department
272
+ at a time, because people would be more likely to come if they
273
+ knew their friends were. And you should probably start from scratch,
274
+ rather than trying to upgrade an existing university, or much energy
275
+ would be lost in friction.[4]
276
+ Hypothesis: Any plan in which multiple independent buildings
277
+ are gutted or demolished to be "redeveloped" as a single project
278
+ is a net loss of personality for the city, with the exception of
279
+ the conversion of buildings not previously public, like warehouses.[5]
280
+ A few startups get started in New York, but less
281
+ than a tenth as many per capita as in Boston, and mostly
282
+ in less nerdy fields like finance and media.[6]
283
+ Some blue counties are false positives (reflecting the
284
+ remaining power of Democractic party machines), but there are no
285
+ false negatives. You can safely write off all the red counties.[7]
286
+ Some "urban renewal" experts took a shot at destroying Boston's
287
+ in the 1960s, leaving the area around city hall a bleak wasteland,
288
+ but most neighborhoods successfully resisted them.Thanks to Chris Anderson, Trevor Blackwell, Marc Hedlund,
289
+ Jessica Livingston, Robert Morris, Greg Mcadoo, Fred Wilson,
290
+ and Stephen Wolfram for
291
+ reading drafts of this, and to Ed Dumbill for inviting me to speak.(The second part of this talk became Why Startups
292
+ Condense in America.)
PaulGrahamEssays/startuplessons.txt ADDED
@@ -0,0 +1,395 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ April 2006(This essay is derived from a talk at the 2006
2
+ Startup School.)The startups we've funded so far are pretty quick, but they seem
3
+ quicker to learn some lessons than others. I think it's because
4
+ some things about startups are kind of counterintuitive.We've now
5
+ invested
6
+ in enough companies that I've learned a trick
7
+ for determining which points are the counterintuitive ones:
8
+ they're the ones I have to keep repeating.So I'm going to number these points, and maybe with future startups
9
+ I'll be able to pull off a form of Huffman coding. I'll make them
10
+ all read this, and then instead of nagging them in detail, I'll
11
+ just be able to say: number four!
12
+ 1. Release Early.The thing I probably repeat most is this recipe for a startup: get
13
+ a version 1 out fast, then improve it based on users' reactions.By "release early" I don't mean you should release something full
14
+ of bugs, but that you should release something minimal. Users hate
15
+ bugs, but they don't seem to mind a minimal version 1, if there's
16
+ more coming soon.There are several reasons it pays to get version 1 done fast. One
17
+ is that this is simply the right way to write software, whether for
18
+ a startup or not. I've been repeating that since 1993, and I haven't seen much since to
19
+ contradict it. I've seen a lot of startups die because they were
20
+ too slow to release stuff, and none because they were too quick.
21
+ [1]One of the things that will surprise you if you build something
22
+ popular is that you won't know your users. Reddit now has almost half a million
23
+ unique visitors a month. Who are all those people? They have no
24
+ idea. No web startup does. And since you don't know your users,
25
+ it's dangerous to guess what they'll like. Better to release
26
+ something and let them tell you.Wufoo took this to heart and released
27
+ their form-builder before the underlying database. You can't even
28
+ drive the thing yet, but 83,000 people came to sit in the driver's
29
+ seat and hold the steering wheel. And Wufoo got valuable feedback
30
+ from it: Linux users complained they used too much Flash, so they
31
+ rewrote their software not to. If they'd waited to release everything
32
+ at once, they wouldn't have discovered this problem till it was
33
+ more deeply wired in.Even if you had no users, it would still be important to release
34
+ quickly, because for a startup the initial release acts as a shakedown
35
+ cruise. If anything major is broken-- if the idea's no good,
36
+ for example, or the founders hate one another-- the stress of getting
37
+ that first version out will expose it. And if you have such problems
38
+ you want to find them early.Perhaps the most important reason to release early, though, is that
39
+ it makes you work harder. When you're working on something that
40
+ isn't released, problems are intriguing. In something that's out
41
+ there, problems are alarming. There is a lot more urgency once you
42
+ release. And I think that's precisely why people put it off. They
43
+ know they'll have to work a lot harder once they do.
44
+ [2]
45
+ 2. Keep Pumping Out Features.Of course, "release early" has a second component, without which
46
+ it would be bad advice. If you're going to start with something
47
+ that doesn't do much, you better improve it fast.What I find myself repeating is "pump out features." And this rule
48
+ isn't just for the initial stages. This is something all startups
49
+ should do for as long as they want to be considered startups.I don't mean, of course, that you should make your application ever
50
+ more complex. By "feature" I mean one unit of hacking-- one quantum
51
+ of making users' lives better.As with exercise, improvements beget improvements. If you run every
52
+ day, you'll probably feel like running tomorrow. But if you skip
53
+ running for a couple weeks, it will be an effort to drag yourself
54
+ out. So it is with hacking: the more ideas you implement, the more
55
+ ideas you'll have. You should make your system better at least in
56
+ some small way every day or two.This is not just a good way to get development done; it is also a
57
+ form of marketing. Users love a site that's constantly improving.
58
+ In fact, users expect a site to improve. Imagine if you visited a
59
+ site that seemed very good, and then returned two months later and
60
+ not one thing had changed. Wouldn't it start to seem lame?
61
+ [3]They'll like you even better when you improve in response to their
62
+ comments, because customers are used to companies ignoring them.
63
+ If you're the rare exception-- a company that actually listens--
64
+ you'll generate fanatical loyalty. You won't need to advertise,
65
+ because your users will do it for you.This seems obvious too, so why do I have to keep repeating it? I
66
+ think the problem here is that people get used to how things are.
67
+ Once a product gets past the stage where it has glaring flaws, you
68
+ start to get used to it, and gradually whatever features it happens
69
+ to have become its identity. For example, I doubt many people at
70
+ Yahoo (or Google for that matter) realized how much better web mail
71
+ could be till Paul Buchheit showed them.I think the solution is to assume that anything you've made is far
72
+ short of what it could be. Force yourself, as a sort of intellectual
73
+ exercise, to keep thinking of improvements. Ok, sure, what you
74
+ have is perfect. But if you had to change something, what would
75
+ it be?If your product seems finished, there are two possible explanations:
76
+ (a) it is finished, or (b) you lack imagination. Experience suggests
77
+ (b) is a thousand times more likely.
78
+ 3. Make Users Happy.Improving constantly is an instance of a more general rule: make
79
+ users happy. One thing all startups have in common is that they
80
+ can't force anyone to do anything. They can't force anyone to use
81
+ their software, and they can't force anyone to do deals with them.
82
+ A startup has to sing for its supper. That's why the successful
83
+ ones make great things. They have to, or die.When you're running a startup you feel like a little bit of debris
84
+ blown about by powerful winds. The most powerful wind is users.
85
+ They can either catch you and loft you up into the sky, as they did
86
+ with Google, or leave you flat on the pavement, as they do with
87
+ most startups. Users are a fickle wind, but more powerful than any
88
+ other. If they take you up, no competitor can keep you down.As a little piece of debris, the rational thing for you to do is
89
+ not to lie flat, but to curl yourself into a shape the wind will
90
+ catch.I like the wind metaphor because it reminds you how impersonal the
91
+ stream of traffic is. The vast majority of people who visit your
92
+ site will be casual visitors. It's them you have to design your
93
+ site for. The people who really care will find what they want by
94
+ themselves.The median visitor will arrive with their finger poised on the Back
95
+ button. Think about your own experience: most links you
96
+ follow lead to something lame. Anyone who has used the web for
97
+ more than a couple weeks has been trained to click on Back after
98
+ following a link. So your site has to say "Wait! Don't click on
99
+ Back. This site isn't lame. Look at this, for example."There are two things you have to do to make people pause. The most
100
+ important is to explain, as concisely as possible, what the hell
101
+ your site is about. How often have you visited a site that seemed
102
+ to assume you already knew what they did? For example, the corporate
103
+ site that says the
104
+ company makes
105
+
106
+ enterprise content management solutions for business that enable
107
+ organizations to unify people, content and processes to minimize
108
+ business risk, accelerate time-to-value and sustain lower total
109
+ cost of ownership.
110
+
111
+ An established company may get away with such an opaque description,
112
+ but no startup can. A startup
113
+ should be able to explain in one or two sentences exactly what it
114
+ does.
115
+ [4]
116
+ And not just to users. You need this for everyone:
117
+ investors, acquirers, partners, reporters, potential employees, and
118
+ even current employees. You probably shouldn't even start a company
119
+ to do something that can't be described compellingly in one or two
120
+ sentences.The other thing I repeat is to give people everything you've got,
121
+ right away. If you have something impressive, try to put it on the
122
+ front page, because that's the only one most visitors will see.
123
+ Though indeed there's a paradox here: the more you push the good
124
+ stuff toward the front, the more likely visitors are to explore
125
+ further.
126
+ [5]In the best case these two suggestions get combined: you tell
127
+ visitors what your site is about by showing them. One of the
128
+ standard pieces of advice in fiction writing is "show, don't tell."
129
+ Don't say that a character's angry; have him grind his teeth, or
130
+ break his pencil in half. Nothing will explain what your site does
131
+ so well as using it.The industry term here is "conversion." The job of your site is
132
+ to convert casual visitors into users-- whatever your definition
133
+ of a user is. You can measure this in your growth rate. Either
134
+ your site is catching on, or it isn't, and you must know which. If
135
+ you have decent growth, you'll win in the end, no matter how obscure
136
+ you are now. And if you don't, you need to fix something.
137
+ 4. Fear the Right Things.Another thing I find myself saying a lot is "don't worry." Actually,
138
+ it's more often "don't worry about this; worry about that instead."
139
+ Startups are right to be paranoid, but they sometimes fear the wrong
140
+ things.Most visible disasters are not so alarming as they seem. Disasters
141
+ are normal in a startup: a founder quits, you discover a patent
142
+ that covers what you're doing, your servers keep crashing, you run
143
+ into an insoluble technical problem, you have to change your name,
144
+ a deal falls through-- these are all par for the course. They won't
145
+ kill you unless you let them.Nor will most competitors. A lot of startups worry "what if Google
146
+ builds something like us?" Actually big companies are not the ones
147
+ you have to worry about-- not even Google. The people at Google
148
+ are smart, but no smarter than you; they're not as motivated, because
149
+ Google is not going to go out of business if this one product fails;
150
+ and even at Google they have a lot of bureaucracy to slow them down.What you should fear, as a startup, is not the established players,
151
+ but other startups you don't know exist yet. They're way more
152
+ dangerous than Google because, like you, they're cornered animals.Looking just at existing competitors can give you a false sense of
153
+ security. You should compete against what someone else could be
154
+ doing, not just what you can see people doing. A corollary is that
155
+ you shouldn't relax just because you have no visible competitors
156
+ yet. No matter what your idea, there's someone else out there
157
+ working on the same thing.That's the downside of it being easier to start a startup: more people
158
+ are doing it. But I disagree with Caterina Fake when she says that
159
+ makes this a bad time to start a startup. More people are starting
160
+ startups, but not as many more as could. Most college graduates
161
+ still think they have to get a job. The average person can't ignore
162
+ something that's been beaten into their head since they were three
163
+ just because serving web pages recently got a lot cheaper.And in any case, competitors are not the biggest threat. Way more
164
+ startups hose themselves than get crushed by competitors. There
165
+ are a lot of ways to do it, but the three main ones are internal
166
+ disputes, inertia, and ignoring users. Each is, by itself, enough
167
+ to kill you. But if I had to pick the worst, it would be ignoring
168
+ users. If you want a recipe for a startup that's going to die,
169
+ here it is: a couple of founders who have some great idea they know
170
+ everyone is going to love, and that's what they're going to build,
171
+ no matter what.Almost everyone's initial plan is broken. If companies stuck to
172
+ their initial plans, Microsoft would be selling programming languages,
173
+ and Apple would be selling printed circuit boards. In both cases
174
+ their customers told them what their business should be-- and they
175
+ were smart enough to listen.As Richard Feynman said, the imagination of nature is greater than
176
+ the imagination of man. You'll find more interesting things by
177
+ looking at the world than you could ever produce just by thinking.
178
+ This principle is very powerful. It's why the best abstract painting
179
+ still falls short of Leonardo, for example. And it applies to
180
+ startups too. No idea for a product could ever be so clever as the
181
+ ones you can discover by smashing a beam of prototypes into a beam
182
+ of users.
183
+ 5. Commitment Is a Self-Fulfilling Prophecy.I now have enough experience with startups to be able to say what
184
+ the most important quality is in a startup founder, and it's not
185
+ what you might think. The most important quality in a startup
186
+ founder is determination. Not intelligence-- determination.This is a little depressing. I'd like to believe Viaweb succeeded
187
+ because we were smart, not merely determined. A lot of people in
188
+ the startup world want to believe that. Not just founders, but
189
+ investors too. They like the idea of inhabiting a world ruled by
190
+ intelligence. And you can tell they really believe this, because
191
+ it affects their investment decisions.Time after time VCs invest in startups founded by eminent professors.
192
+ This may work in biotech, where a lot of startups simply commercialize
193
+ existing research, but in software you want to invest in students,
194
+ not professors. Microsoft, Yahoo, and Google were all founded by
195
+ people who dropped out of school to do it. What students lack in
196
+ experience they more than make up in dedication.Of course, if you want to get rich, it's not enough merely to be
197
+ determined. You have to be smart too, right? I'd like to think
198
+ so, but I've had an experience that convinced me otherwise: I spent
199
+ several years living in New York.You can lose quite a lot in the brains department and it won't kill
200
+ you. But lose even a little bit in the commitment department, and
201
+ that will kill you very rapidly.Running a startup is like walking on your hands: it's possible, but
202
+ it requires extraordinary effort. If an ordinary employee were
203
+ asked to do the things a startup founder has to, he'd be very
204
+ indignant. Imagine if you were hired at some big company, and in
205
+ addition to writing software ten times faster than you'd ever had
206
+ to before, they expected you to answer support calls, administer
207
+ the servers, design the web site, cold-call customers, find the
208
+ company office space, and go out and get everyone lunch.And to do all this not in the calm, womb-like atmosphere of a big
209
+ company, but against a backdrop of constant disasters. That's the
210
+ part that really demands determination. In a startup, there's
211
+ always some disaster happening. So if you're the least bit inclined
212
+ to find an excuse to quit, there's always one right there.But if you lack commitment, chances are it will have been hurting
213
+ you long before you actually quit. Everyone who deals with startups
214
+ knows how important commitment is, so if they sense you're ambivalent,
215
+ they won't give you much attention. If you lack commitment, you'll
216
+ just find that for some mysterious reason good things happen to
217
+ your competitors but not to you. If you lack commitment, it will
218
+ seem to you that you're unlucky.Whereas if you're determined to stick around, people will pay
219
+ attention to you, because odds are they'll have to deal with you
220
+ later. You're a local, not just a tourist, so everyone has to come
221
+ to terms with you.At Y Combinator we sometimes mistakenly fund teams who have the
222
+ attitude that they're going to give this startup thing a shot for
223
+ three months, and if something great happens, they'll stick with
224
+ it-- "something great" meaning either that someone wants to buy
225
+ them or invest millions of dollars in them. But if this is your
226
+ attitude, "something great" is very unlikely to happen to you,
227
+ because both acquirers and investors judge you by your level of
228
+ commitment.If an acquirer thinks you're going to stick around no matter what,
229
+ they'll be more likely to buy you, because if they don't and you
230
+ stick around, you'll probably grow, your price will go up, and
231
+ they'll be left wishing they'd bought you earlier. Ditto for
232
+ investors. What really motivates investors, even big VCs, is not
233
+ the hope of good returns, but the fear of missing out.
234
+ [6]
235
+ So if
236
+ you make it clear you're going to succeed no matter what, and the only
237
+ reason you need them is to make it happen a little faster, you're
238
+ much more likely to get money.You can't fake this. The only way to convince everyone that you're
239
+ ready to fight to the death is actually to be ready to.You have to be the right kind of determined, though. I carefully
240
+ chose the word determined rather than stubborn, because stubbornness
241
+ is a disastrous quality in a startup. You have to be determined,
242
+ but flexible, like a running back. A successful running back doesn't
243
+ just put his head down and try to run through people. He improvises:
244
+ if someone appears in front of him, he runs around them; if someone
245
+ tries to grab him, he spins out of their grip; he'll even run in
246
+ the wrong direction briefly if that will help. The one thing he'll
247
+ never do is stand still.
248
+ [7]
249
+ 6. There Is Always Room.I was talking recently to a startup founder about whether it might
250
+ be good to add a social component to their software. He said he
251
+ didn't think so, because the whole social thing was tapped out.
252
+ Really? So in a hundred years the only social networking sites
253
+ will be the Facebook, MySpace, Flickr, and Del.icio.us? Not likely.There is always room for new stuff. At every point in history,
254
+ even the darkest bits of the dark ages, people were discovering
255
+ things that made everyone say "why didn't anyone think of that
256
+ before?" We know this continued to be true up till 2004, when the
257
+ Facebook was founded-- though strictly speaking someone else did
258
+ think of that.The reason we don't see the opportunities all around us is that we
259
+ adjust to however things are, and assume that's how things have to
260
+ be. For example, it would seem crazy to most people to try to make
261
+ a better search engine than Google. Surely that field, at least,
262
+ is tapped out. Really? In a hundred years-- or even twenty-- are
263
+ people still going to search for information using something like
264
+ the current Google? Even Google probably doesn't think that.In particular, I don't think there's any limit to the number of
265
+ startups. Sometimes you hear people saying "All these guys starting
266
+ startups now are going to be disappointed. How many little startups
267
+ are Google and Yahoo going to buy, after all?" That sounds cleverly
268
+ skeptical, but I can prove it's mistaken. No one proposes that
269
+ there's some limit to the number of people who can be employed in
270
+ an economy consisting of big, slow-moving companies with a couple
271
+ thousand people each. Why should there be any limit to the number
272
+ who could be employed by small, fast-moving companies with ten each?
273
+ It seems to me the only limit would be the number of people who
274
+ want to work that hard.The limit on the number of startups is not the number that can get
275
+ acquired by Google and Yahoo-- though it seems even that should
276
+ be unlimited, if the startups were actually worth buying-- but the
277
+ amount of wealth that can be created. And I don't think there's
278
+ any limit on that, except cosmological ones.So for all practical purposes, there is no limit to the number of
279
+ startups. Startups make wealth, which means they make things people
280
+ want, and if there's a limit on the number of things people want,
281
+ we are nowhere near it. I still don't even have a flying car.
282
+ 7. Don't Get Your Hopes Up.This is another one I've been repeating since long before Y Combinator.
283
+ It was practically the corporate motto at Viaweb.Startup founders are naturally optimistic. They wouldn't do it
284
+ otherwise. But you should treat your optimism the way you'd treat
285
+ the core of a nuclear reactor: as a source of power that's also
286
+ very dangerous. You have to build a shield around it, or it will
287
+ fry you.The shielding of a reactor is not uniform; the reactor would be
288
+ useless if it were. It's pierced in a few places to let pipes in.
289
+ An optimism shield has to be pierced too. I think the place to
290
+ draw the line is between what you expect of yourself, and what you
291
+ expect of other people. It's ok to be optimistic about what you
292
+ can do, but assume the worst about machines and other people.This is particularly necessary in a startup, because you tend to
293
+ be pushing the limits of whatever you're doing. So things don't
294
+ happen in the smooth, predictable way they do in the rest of the
295
+ world. Things change suddenly, and usually for the worse.Shielding your optimism is nowhere more important than with deals.
296
+ If your startup is doing a deal, just assume it's not going to
297
+ happen. The VCs who say they're going to invest in you aren't.
298
+ The company that says they're going to buy you isn't. The big
299
+ customer who wants to use your system in their whole company won't.
300
+ Then if things work out you can be pleasantly surprised.The reason I warn startups not to get their hopes up is not to save
301
+ them from being disappointed when things fall through. It's
302
+ for a more practical reason: to prevent them from leaning their
303
+ company against something that's going to fall over, taking them
304
+ with it.For example, if someone says they want to invest in you, there's a
305
+ natural tendency to stop looking for other investors. That's why
306
+ people proposing deals seem so positive: they want you to
307
+ stop looking. And you want to stop too, because doing deals is a
308
+ pain. Raising money, in particular, is a huge time sink. So you
309
+ have to consciously force yourself to keep looking.Even if you ultimately do the first deal, it will be to your advantage
310
+ to have kept looking, because you'll get better terms. Deals are
311
+ dynamic; unless you're negotiating with someone unusually honest,
312
+ there's not a single point where you shake hands and the deal's
313
+ done. There are usually a lot of subsidiary questions to be cleared
314
+ up after the handshake, and if the other side senses weakness-- if
315
+ they sense you need this deal-- they will be very tempted to screw
316
+ you in the details.VCs and corp dev guys are professional negotiators. They're trained
317
+ to take advantage of weakness.
318
+ [8]
319
+ So while they're often nice
320
+ guys, they just can't help it. And as pros they do this more than
321
+ you. So don't even try to bluff them. The only way a startup can
322
+ have any leverage in a deal is genuinely not to need it. And if
323
+ you don't believe in a deal, you'll be less likely to depend on it.So I want to plant a hypnotic suggestion in your heads: when you
324
+ hear someone say the words "we want to invest in you" or "we want
325
+ to acquire you," I want the following phrase to appear automatically
326
+ in your head: don't get your hopes up. Just continue running
327
+ your company as if this deal didn't exist. Nothing is more likely
328
+ to make it close.The way to succeed in a startup is to focus on the goal of getting
329
+ lots of users, and keep walking swiftly toward it while investors
330
+ and acquirers scurry alongside trying to wave money in your face.
331
+ Speed, not MoneyThe way I've described it, starting a startup sounds pretty stressful.
332
+ It is. When I talk to the founders of the companies we've funded,
333
+ they all say the same thing: I knew it would be hard, but I didn't
334
+ realize it would be this hard.So why do it? It would be worth enduring a lot of pain and stress
335
+ to do something grand or heroic, but just to make money? Is making
336
+ money really that important?No, not really. It seems ridiculous to me when people take business
337
+ too seriously. I regard making money as a boring errand to be got
338
+ out of the way as soon as possible. There is nothing grand or
339
+ heroic about starting a startup per se.So why do I spend so much time thinking about startups? I'll tell
340
+ you why. Economically, a startup is best seen not as a way to get
341
+ rich, but as a way to work faster. You have to make a living, and
342
+ a startup is a way to get that done quickly, instead of letting it
343
+ drag on through your whole life.
344
+ [9]We take it for granted most of the time, but human life is fairly
345
+ miraculous. It is also palpably short. You're given this marvellous
346
+ thing, and then poof, it's taken away. You can see why people
347
+ invent gods to explain it. But even to people who don't believe
348
+ in gods, life commands respect. There are times in most of our
349
+ lives when the days go by in a blur, and almost everyone has a
350
+ sense, when this happens, of wasting something precious. As Ben
351
+ Franklin said, if you love life, don't waste time, because time is
352
+ what life is made of.So no, there's nothing particularly grand about making money. That's
353
+ not what makes startups worth the trouble. What's important about
354
+ startups is the speed. By compressing the dull but necessary task
355
+ of making a living into the smallest possible time, you show respect
356
+ for life, and there is something grand about that.Notes[1]
357
+ Startups can die from releasing something full of bugs, and not
358
+ fixing them fast enough, but I don't know of any that died from
359
+ releasing something stable but minimal very early, then promptly
360
+ improving it.[2]
361
+ I know this is why I haven't released Arc. The moment I do,
362
+ I'll have people nagging me for features.[3]
363
+ A web site is different from a book or movie or desktop application
364
+ in this respect. Users judge a site not as a single snapshot, but
365
+ as an animation with multiple frames. Of the two, I'd say the rate of
366
+ improvement is more important to users than where you currently
367
+ are.[4]
368
+ It should not always tell this to users, however. For example,
369
+ MySpace is basically a replacement mall for mallrats. But it was
370
+ wiser for them, initially, to pretend that the site was about bands.[5]
371
+ Similarly, don't make users register to try your site. Maybe
372
+ what you have is so valuable that visitors should gladly register
373
+ to get at it. But they've been trained to expect the opposite.
374
+ Most of the things they've tried on the web have sucked-- and
375
+ probably especially those that made them register.[6]
376
+ VCs have rational reasons for behaving this way. They don't
377
+ make their money (if they make money) off their median investments.
378
+ In a typical fund, half the companies fail, most of the rest generate
379
+ mediocre returns, and one or two "make the fund" by succeeding
380
+ spectacularly. So if they miss just a few of the most promising
381
+ opportunities, it could hose the whole fund.[7]
382
+ The attitude of a running back doesn't translate to soccer.
383
+ Though it looks great when a forward dribbles past multiple defenders,
384
+ a player who persists in trying such things will do worse in the
385
+ long term than one who passes.[8]
386
+ The reason Y Combinator never negotiates valuations
387
+ is that we're not professional negotiators, and don't want to turn
388
+ into them.[9]
389
+ There are two ways to do
390
+ work you love: (a) to make money, then work
391
+ on what you love, or (b) to get a job where you get paid to work on
392
+ stuff you love. In practice the first phases of both
393
+ consist mostly of unedifying schleps, and in (b) the second phase is less
394
+ secure.Thanks to Sam Altman, Trevor Blackwell, Beau Hartshorne, Jessica
395
+ Livingston, and Robert Morris for reading drafts of this.
PaulGrahamEssays/submarine.txt ADDED
@@ -0,0 +1,217 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ April 2005"Suits make a corporate comeback," says the New
2
+ York Times. Why does this sound familiar? Maybe because
3
+ the suit was also back in February,
4
+
5
+ September
6
+ 2004, June
7
+ 2004, March
8
+ 2004, September
9
+ 2003,
10
+
11
+ November
12
+ 2002,
13
+ April 2002,
14
+ and February
15
+ 2002.
16
+
17
+ Why do the media keep running stories saying suits are back? Because
18
+ PR firms tell
19
+ them to. One of the most surprising things I discovered
20
+ during my brief business career was the existence of the PR industry,
21
+ lurking like a huge, quiet submarine beneath the news. Of the
22
+ stories you read in traditional media that aren't about politics,
23
+ crimes, or disasters, more than half probably come from PR firms.I know because I spent years hunting such "press hits." Our startup spent
24
+ its entire marketing budget on PR: at a time when we were assembling
25
+ our own computers to save money, we were paying a PR firm $16,000
26
+ a month. And they were worth it. PR is the news equivalent of
27
+ search engine optimization; instead of buying ads, which readers
28
+ ignore, you get yourself inserted directly into the stories. [1]Our PR firm
29
+ was one of the best in the business. In 18 months, they got press
30
+ hits in over 60 different publications.
31
+ And we weren't the only ones they did great things for.
32
+ In 1997 I got a call from another
33
+ startup founder considering hiring them to promote his company. I
34
+ told him they were PR gods, worth every penny of their outrageous
35
+ fees. But I remember thinking his company's name was odd.
36
+ Why call an auction site "eBay"?
37
+ SymbiosisPR is not dishonest. Not quite. In fact, the reason the best PR
38
+ firms are so effective is precisely that they aren't dishonest.
39
+ They give reporters genuinely valuable information. A good PR firm
40
+ won't bug reporters just because the client tells them to; they've
41
+ worked hard to build their credibility with reporters, and they
42
+ don't want to destroy it by feeding them mere propaganda.If anyone is dishonest, it's the reporters. The main reason PR
43
+ firms exist is that reporters are lazy. Or, to put it more nicely,
44
+ overworked. Really they ought to be out there digging up stories
45
+ for themselves. But it's so tempting to sit in their offices and
46
+ let PR firms bring the stories to them. After all, they know good
47
+ PR firms won't lie to them.A good flatterer doesn't lie, but tells his victim selective truths
48
+ (what a nice color your eyes are). Good PR firms use the same
49
+ strategy: they give reporters stories that are true, but whose truth
50
+ favors their clients.For example, our PR firm often pitched stories about how the Web
51
+ let small merchants compete with big ones. This was perfectly true.
52
+ But the reason reporters ended up writing stories about this
53
+ particular truth, rather than some other one, was that small merchants
54
+ were our target market, and we were paying the piper.Different publications vary greatly in their reliance on PR firms.
55
+ At the bottom of the heap are the trade press, who make most of
56
+ their money from advertising and would give the magazines away for
57
+ free if advertisers would let them. [2] The average
58
+ trade publication is a bunch of ads, glued together by just enough
59
+ articles to make it look like a magazine. They're so desperate for
60
+ "content" that some will print your press releases almost verbatim,
61
+ if you take the trouble to write them to read like articles.At the other extreme are publications like the New York Times
62
+ and the Wall Street Journal. Their reporters do go out and
63
+ find their own stories, at least some of the time. They'll listen
64
+ to PR firms, but briefly and skeptically. We managed to get press
65
+ hits in almost every publication we wanted, but we never managed
66
+ to crack the print edition of the Times. [3]The weak point of the top reporters is not laziness, but vanity.
67
+ You don't pitch stories to them. You have to approach them as if
68
+ you were a specimen under their all-seeing microscope, and make it
69
+ seem as if the story you want them to run is something they thought
70
+ of themselves.Our greatest PR coup was a two-part one. We estimated, based on
71
+ some fairly informal math, that there were about 5000 stores on the
72
+ Web. We got one paper to print this number, which seemed neutral
73
+ enough. But once this "fact" was out there in print, we could quote
74
+ it to other publications, and claim that with 1000 users we had 20%
75
+ of the online store market.This was roughly true. We really did have the biggest share of the
76
+ online store market, and 5000 was our best guess at its size. But
77
+ the way the story appeared in the press sounded a lot more definite.Reporters like definitive statements. For example, many of the
78
+ stories about Jeremy Jaynes's conviction say that he was one of the
79
+ 10 worst spammers. This "fact" originated in Spamhaus's ROKSO list,
80
+ which I think even Spamhaus would admit is a rough guess at the top
81
+ spammers. The first stories about Jaynes cited this source, but
82
+ now it's simply repeated as if it were part of the indictment.
83
+ [4]All you can say with certainty about Jaynes is that he was a fairly
84
+ big spammer. But reporters don't want to print vague stuff like
85
+ "fairly big." They want statements with punch, like "top ten." And
86
+ PR firms give them what they want.
87
+ Wearing suits, we're told, will make us
88
+ 3.6
89
+ percent more productive.BuzzWhere the work of PR firms really does get deliberately misleading is in
90
+ the generation of "buzz." They usually feed the same story to
91
+ several different publications at once. And when readers see similar
92
+ stories in multiple places, they think there is some important trend
93
+ afoot. Which is exactly what they're supposed to think.When Windows 95 was launched, people waited outside stores
94
+ at midnight to buy the first copies. None of them would have been
95
+ there without PR firms, who generated such a buzz in
96
+ the news media that it became self-reinforcing, like a nuclear chain
97
+ reaction.I doubt PR firms realize it yet, but the Web makes it possible to
98
+ track them at work. If you search for the obvious phrases, you
99
+ turn up several efforts over the years to place stories about the
100
+ return of the suit. For example, the Reuters article
101
+
102
+ that got picked up by USA
103
+ Today in September 2004. "The suit is back," it begins.Trend articles like this are almost always the work of
104
+ PR firms. Once you know how to read them, it's straightforward to
105
+ figure out who the client is. With trend stories, PR firms usually
106
+ line up one or more "experts" to talk about the industry generally.
107
+ In this case we get three: the NPD Group, the creative director of
108
+ GQ, and a research director at Smith Barney. [5] When
109
+ you get to the end of the experts, look for the client. And bingo,
110
+ there it is: The Men's Wearhouse.Not surprising, considering The Men's Wearhouse was at that moment
111
+ running ads saying "The Suit is Back." Talk about a successful
112
+ press hit-- a wire service article whose first sentence is your own
113
+ ad copy.The secret to finding other press hits from a given pitch
114
+ is to realize that they all started from the same document back at
115
+ the PR firm. Search for a few key phrases and the names of the
116
+ clients and the experts, and you'll turn up other variants of this
117
+ story.Casual
118
+ fridays are out and dress codes are in writes Diane E. Lewis
119
+ in The Boston Globe. In a remarkable coincidence, Ms. Lewis's
120
+ industry contacts also include the creative director of GQ.Ripped jeans and T-shirts are out, writes Mary Kathleen Flynn in
121
+ US News & World Report. And she too knows the
122
+ creative director of GQ.Men's suits
123
+ are back writes Nicole Ford in Sexbuzz.Com ("the ultimate men's
124
+ entertainment magazine").Dressing
125
+ down loses appeal as men suit up at the office writes Tenisha
126
+ Mercer of The Detroit News.
127
+ Now that so many news articles are online, I suspect you could find
128
+ a similar pattern for most trend stories placed by PR firms. I
129
+ propose we call this new sport "PR diving," and I'm sure there are
130
+ far more striking examples out there than this clump of five stories.OnlineAfter spending years chasing them, it's now second nature
131
+ to me to recognize press hits for what they are. But before we
132
+ hired a PR firm I had no idea where articles in the mainstream media
133
+ came from. I could tell a lot of them were crap, but I didn't
134
+ realize why.Remember the exercises in critical reading you did in school, where
135
+ you had to look at a piece of writing and step back and ask whether
136
+ the author was telling the whole truth? If you really want to be
137
+ a critical reader, it turns out you have to step back one step
138
+ further, and ask not just whether the author is telling the truth,
139
+ but why he's writing about this subject at all.Online, the answer tends to be a lot simpler. Most people who
140
+ publish online write what they write for the simple reason that
141
+ they want to. You
142
+ can't see the fingerprints of PR firms all over the articles, as
143
+ you can in so many print publications-- which is one of the reasons,
144
+ though they may not consciously realize it, that readers trust
145
+ bloggers more than Business Week.I was talking recently to a friend who works for a
146
+ big newspaper. He thought the print media were in serious trouble,
147
+ and that they were still mostly in denial about it. "They think
148
+ the decline is cyclic," he said. "Actually it's structural."In other words, the readers are leaving, and they're not coming
149
+ back.
150
+ Why? I think the main reason is that the writing online is more honest.
151
+ Imagine how incongruous the New York Times article about
152
+ suits would sound if you read it in a blog:
153
+ The urge to look corporate-- sleek, commanding,
154
+ prudent, yet with just a touch of hubris on your well-cut sleeve--
155
+ is an unexpected development in a time of business disgrace.
156
+
157
+ The problem
158
+ with this article is not just that it originated in a PR firm.
159
+ The whole tone is bogus. This is the tone of someone writing down
160
+ to their audience.Whatever its flaws, the writing you find online
161
+ is authentic. It's not mystery meat cooked up
162
+ out of scraps of pitch letters and press releases, and pressed into
163
+ molds of zippy
164
+ journalese. It's people writing what they think.I didn't realize, till there was an alternative, just how artificial
165
+ most of the writing in the mainstream media was. I'm not saying
166
+ I used to believe what I read in Time and Newsweek. Since high
167
+ school, at least, I've thought of magazines like that more as
168
+ guides to what ordinary people were being
169
+ told to think than as
170
+ sources of information. But I didn't realize till the last
171
+ few years that writing for publication didn't have to mean writing
172
+ that way. I didn't realize you could write as candidly and
173
+ informally as you would if you were writing to a friend.Readers aren't the only ones who've noticed the
174
+ change. The PR industry has too.
175
+ A hilarious article
176
+ on the site of the PR Society of America gets to the heart of the
177
+ matter:
178
+ Bloggers are sensitive about becoming mouthpieces
179
+ for other organizations and companies, which is the reason they
180
+ began blogging in the first place.
181
+ PR people fear bloggers for the same reason readers
182
+ like them. And that means there may be a struggle ahead. As
183
+ this new kind of writing draws readers away from traditional media, we
184
+ should be prepared for whatever PR mutates into to compensate.
185
+ When I think
186
+ how hard PR firms work to score press hits in the traditional
187
+ media, I can't imagine they'll work any less hard to feed stories
188
+ to bloggers, if they can figure out how.
189
+ Notes[1] PR has at least
190
+ one beneficial feature: it favors small companies. If PR didn't
191
+ work, the only alternative would be to advertise, and only big
192
+ companies can afford that.[2] Advertisers pay
193
+ less for ads in free publications, because they assume readers
194
+ ignore something they get for free. This is why so many trade
195
+ publications nominally have a cover price and yet give away free
196
+ subscriptions with such abandon.[3] Different sections
197
+ of the Times vary so much in their standards that they're
198
+ practically different papers. Whoever fed the style section reporter
199
+ this story about suits coming back would have been sent packing by
200
+ the regular news reporters.[4] The most striking
201
+ example I know of this type is the "fact" that the Internet worm
202
+ of 1988 infected 6000 computers. I was there when it was cooked up,
203
+ and this was the recipe: someone guessed that there were about
204
+ 60,000 computers attached to the Internet, and that the worm might
205
+ have infected ten percent of them.Actually no one knows how many computers the worm infected, because
206
+ the remedy was to reboot them, and this destroyed all traces. But
207
+ people like numbers. And so this one is now replicated
208
+ all over the Internet, like a little worm of its own.[5] Not all were
209
+ necessarily supplied by the PR firm. Reporters sometimes call a few
210
+ additional sources on their own, like someone adding a few fresh
211
+ vegetables to a can of soup.
212
+ Thanks to Ingrid Basset, Trevor Blackwell, Sarah Harlin, Jessica
213
+ Livingston, Jackie McDonough, Robert Morris, and Aaron Swartz (who
214
+ also found the PRSA article) for reading drafts of this.Correction: Earlier versions used a recent
215
+ Business Week article mentioning del.icio.us as an example
216
+ of a press hit, but Joshua Schachter tells me
217
+ it was spontaneous.
PaulGrahamEssays/sun.txt ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ September 2017The most valuable insights are both general and surprising.
2
+ F = ma for example. But general and surprising is a hard
3
+ combination to achieve. That territory tends to be picked
4
+ clean, precisely because those insights are so valuable.Ordinarily, the best that people can do is one without the
5
+ other: either surprising without being general (e.g.
6
+ gossip), or general without being surprising (e.g.
7
+ platitudes).Where things get interesting is the moderately valuable
8
+ insights. You get those from small additions of whichever
9
+ quality was missing. The more common case is a small
10
+ addition of generality: a piece of gossip that's more than
11
+ just gossip, because it teaches something interesting about
12
+ the world. But another less common approach is to focus on
13
+ the most general ideas and see if you can find something new
14
+ to say about them. Because these start out so general, you
15
+ only need a small delta of novelty to produce a useful
16
+ insight.A small delta of novelty is all you'll be able to get most
17
+ of the time. Which means if you take this route, your ideas
18
+ will seem a lot like ones that already exist. Sometimes
19
+ you'll find you've merely rediscovered an idea that did
20
+ already exist. But don't be discouraged. Remember the huge
21
+ multiplier that kicks in when you do manage to think of
22
+ something even a little new.Corollary: the more general the ideas you're talking about,
23
+ the less you should worry about repeating yourself. If you
24
+ write enough, it's inevitable you will. Your brain is much
25
+ the same from year to year and so are the stimuli that hit
26
+ it. I feel slightly bad when I find I've said something
27
+ close to what I've said before, as if I were plagiarizing
28
+ myself. But rationally one shouldn't. You won't say
29
+ something exactly the same way the second time, and that
30
+ variation increases the chance you'll get that tiny but
31
+ critical delta of novelty.And of course, ideas beget ideas. (That sounds
32
+ familiar.)
33
+ An idea with a small amount of novelty could lead to one
34
+ with more. But only if you keep going. So it's doubly
35
+ important not to let yourself be discouraged by people who
36
+ say there's not much new about something you've discovered.
37
+ "Not much new" is a real achievement when you're talking
38
+ about the most general ideas. It's not true that there's nothing new under the sun. There
39
+ are some domains where there's almost nothing new. But
40
+ there's a big difference between nothing and almost nothing,
41
+ when it's multiplied by the area under the sun.
42
+ Thanks to Sam Altman, Patrick Collison, and Jessica
43
+ Livingston for reading drafts of this.
PaulGrahamEssays/superangels.txt ADDED
@@ -0,0 +1,302 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ October 2010After barely changing at all for decades, the startup funding
10
+ business is now in what could, at least by comparison, be called
11
+ turmoil. At Y Combinator we've seen dramatic changes in the funding
12
+ environment for startups. Fortunately one of them is much higher
13
+ valuations.The trends we've been seeing are probably not YC-specific. I wish
14
+ I could say they were, but the main cause is probably just that we
15
+ see trends first—partly because the startups we fund are very
16
+ plugged into the Valley and are quick to take advantage of anything
17
+ new, and partly because we fund so many that we have enough data
18
+ points to see patterns clearly.What we're seeing now, everyone's probably going to be seeing in
19
+ the next couple years. So I'm going to explain what we're seeing,
20
+ and what that will mean for you if you try to raise money.Super-AngelsLet me start by describing what the world of startup funding used
21
+ to look like. There used to be two sharply differentiated types
22
+ of investors: angels and venture capitalists. Angels are individual
23
+ rich people who invest small amounts of their own money, while VCs
24
+ are employees of funds that invest large amounts of other people's.For decades there were just those two types of investors, but now
25
+ a third type has appeared halfway between them: the so-called
26
+ super-angels.
27
+ [1]
28
+ And VCs have been provoked by their arrival
29
+ into making a lot of angel-style investments themselves. So the
30
+ previously sharp line between angels and VCs has become hopelessly
31
+ blurred.There used to be a no man's land between angels and VCs. Angels
32
+ would invest $20k to $50k apiece, and VCs usually a million or more.
33
+ So an angel round meant a collection of angel investments that
34
+ combined to maybe $200k, and a VC round meant a series A round in
35
+ which a single VC fund (or occasionally two) invested $1-5 million.The no man's land between angels and VCs was a very inconvenient
36
+ one for startups, because it coincided with the amount many wanted
37
+ to raise. Most startups coming out of Demo Day wanted to raise
38
+ around $400k. But it was a pain to stitch together that much out
39
+ of angel investments, and most VCs weren't interested in investments
40
+ so small. That's the fundamental reason the super-angels have
41
+ appeared. They're responding to the market.The arrival of a new type of investor is big news for startups,
42
+ because there used to be only two and they rarely competed with one
43
+ another. Super-angels compete with both angels and VCs. That's
44
+ going to change the rules about how to raise money. I don't know
45
+ yet what the new rules will be, but it looks like most of the changes
46
+ will be for the better.A super-angel has some of the qualities of an angel, and some of
47
+ the qualities of a VC. They're usually individuals, like angels.
48
+ In fact many of the current super-angels were initially angels of
49
+ the classic type. But like VCs, they invest other people's money.
50
+ This allows them to invest larger amounts than angels: a typical
51
+ super-angel investment is currently about $100k. They make investment
52
+ decisions quickly, like angels. And they make a lot more investments
53
+ per partner than VCs—up to 10 times as many.The fact that super-angels invest other people's money makes them
54
+ doubly alarming to VCs. They don't just compete for startups; they
55
+ also compete for investors. What super-angels really are is a new
56
+ form of fast-moving, lightweight VC fund. And those of us in the
57
+ technology world know what usually happens when something comes
58
+ along that can be described in terms like that. Usually it's the
59
+ replacement.Will it be? As of now, few of the startups that take money from
60
+ super-angels are ruling out taking VC money. They're just postponing
61
+ it. But that's still a problem for VCs. Some of the startups that
62
+ postpone raising VC money may do so well on the angel money they
63
+ raise that they never bother to raise more. And those who do raise
64
+ VC rounds will be able to get higher valuations when they do. If
65
+ the best startups get 10x higher valuations when they raise series
66
+ A rounds, that would cut VCs' returns from winners at least tenfold.
67
+ [2]So I think VC funds are seriously threatened by the super-angels.
68
+ But one thing that may save them to some extent is the uneven
69
+ distribution of startup outcomes: practically all the returns are
70
+ concentrated in a few big successes. The expected value of a startup
71
+ is the percentage chance it's Google. So to the extent that winning
72
+ is a matter of absolute returns, the super-angels could win practically
73
+ all the battles for individual startups and yet lose the war, if
74
+ they merely failed to get those few big winners. And there's a
75
+ chance that could happen, because the top VC funds have better
76
+ brands, and can also do more for their portfolio companies.
77
+ [3]Because super-angels make more investments per partner, they have
78
+ less partner per investment. They can't pay as much attention to
79
+ you as a VC on your board could. How much is that extra attention
80
+ worth? It will vary enormously from one partner to another. There's
81
+ no consensus yet in the general case. So for now this is something
82
+ startups are deciding individually.Till now, VCs' claims about how much value they added were sort of
83
+ like the government's. Maybe they made you feel better, but you
84
+ had no choice in the matter, if you needed money on the scale only
85
+ VCs could supply. Now that VCs have competitors, that's going to
86
+ put a market price on the help they offer. The interesting thing
87
+ is, no one knows yet what it will be.Do startups that want to get really big need the sort of advice and
88
+ connections only the top VCs can supply? Or would super-angel money
89
+ do just as well? The VCs will say you need them, and the super-angels
90
+ will say you don't. But the truth is, no one knows yet, not even
91
+ the VCs and super-angels themselves. All the super-angels know
92
+ is that their new model seems promising enough to be worth trying,
93
+ and all the VCs know is that it seems promising enough to worry
94
+ about.RoundsWhatever the outcome, the conflict between VCs and super-angels is
95
+ good news for founders. And not just for the obvious reason that
96
+ more competition for deals means better terms. The whole shape of
97
+ deals is changing.One of the biggest differences between angels and VCs is the amount
98
+ of your company they want. VCs want a lot. In a series A round
99
+ they want a third of your company, if they can get it. They don't
100
+ care much how much they pay for it, but they want a lot because the
101
+ number of series A investments they can do is so small. In a
102
+ traditional series A investment, at least one partner from the VC
103
+ fund takes a seat on your board.
104
+ [4]
105
+ Since board seats last about
106
+ 5 years and each partner can't handle more than about 10 at once,
107
+ that means a VC fund can only do about 2 series A deals per partner
108
+ per year. And that means they need to get as much of the company
109
+ as they can in each one. You'd have to be a very promising startup
110
+ indeed to get a VC to use up one of his 10 board seats for only a
111
+ few percent of you.Since angels generally don't take board seats, they don't have this
112
+ constraint. They're happy to buy only a few percent of you. And
113
+ although the super-angels are in most respects mini VC funds, they've
114
+ retained this critical property of angels. They don't take board
115
+ seats, so they don't need a big percentage of your company.Though that means you'll get correspondingly less attention from
116
+ them, it's good news in other respects. Founders never really liked
117
+ giving up as much equity as VCs wanted. It was a lot of the company
118
+ to give up in one shot. Most founders doing series A deals would
119
+ prefer to take half as much money for half as much stock, and then
120
+ see what valuation they could get for the second half of the stock
121
+ after using the first half of the money to increase its value. But
122
+ VCs never offered that option.Now startups have another alternative. Now it's easy to raise angel
123
+ rounds about half the size of series A rounds. Many of the startups
124
+ we fund are taking this route, and I predict that will be true of
125
+ startups in general.A typical big angel round might be $600k on a convertible note with
126
+ a valuation cap of $4 million premoney. Meaning that when the note
127
+ converts into stock (in a later round, or upon acquisition), the
128
+ investors in that round will get .6 / 4.6, or 13% of the company.
129
+ That's a lot less than the 30 to 40% of the company you usually
130
+ give up in a series A round if you do it so early.
131
+ [5]But the advantage of these medium-sized rounds is not just that
132
+ they cause less dilution. You also lose less control. After an
133
+ angel round, the founders almost always still have control of the
134
+ company, whereas after a series A round they often don't. The
135
+ traditional board structure after a series A round is two founders,
136
+ two VCs, and a (supposedly) neutral fifth person. Plus series A
137
+ terms usually give the investors a veto over various kinds of
138
+ important decisions, including selling the company. Founders usually
139
+ have a lot of de facto control after a series A, as long as things
140
+ are going well. But that's not the same as just being able to do
141
+ what you want, like you could before.A third and quite significant advantage of angel rounds is that
142
+ they're less stressful to raise. Raising a traditional series A
143
+ round has in the past taken weeks, if not months. When a VC firm
144
+ can only do 2 deals per partner per year, they're careful about
145
+ which they do. To get a traditional series A round you have to go
146
+ through a series of meetings, culminating in a full partner meeting
147
+ where the firm as a whole says yes or no. That's the really scary
148
+ part for founders: not just that series A rounds take so long, but
149
+ at the end of this long process the VCs might still say no. The
150
+ chance of getting rejected after the full partner meeting averages
151
+ about 25%. At some firms it's over 50%.Fortunately for founders, VCs have been getting a lot faster.
152
+ Nowadays Valley VCs are more likely to take 2 weeks than 2 months.
153
+ But they're still not as fast as angels and super-angels, the most
154
+ decisive of whom sometimes decide in hours.Raising an angel round is not only quicker, but you get feedback
155
+ as it progresses. An angel round is not an all or nothing thing
156
+ like a series A. It's composed of multiple investors with varying
157
+ degrees of seriousness, ranging from the upstanding ones who commit
158
+ unequivocally to the jerks who give you lines like "come back to
159
+ me to fill out the round." You usually start collecting money from
160
+ the most committed investors and work your way out toward the
161
+ ambivalent ones, whose interest increases as the round fills up.But at each point you know how you're doing. If investors turn
162
+ cold you may have to raise less, but when investors in an angel
163
+ round turn cold the process at least degrades gracefully, instead
164
+ of blowing up in your face and leaving you with nothing, as happens
165
+ if you get rejected by a VC fund after a full partner meeting.
166
+ Whereas if investors seem hot, you can not only close the round
167
+ faster, but now that convertible notes are becoming the norm,
168
+ actually raise the price to reflect demand.ValuationHowever, the VCs have a weapon they can use against the super-angels,
169
+ and they have started to use it. VCs have started making angel-sized
170
+ investments too. The term "angel round" doesn't mean that all the
171
+ investors in it are angels; it just describes the structure of the
172
+ round. Increasingly the participants include VCs making investments
173
+ of a hundred thousand or two. And when VCs invest in angel rounds
174
+ they can do things that super-angels don't like. VCs are quite
175
+ valuation-insensitive in angel rounds—partly because they are
176
+ in general, and partly because they don't care that much about the
177
+ returns on angel rounds, which they still view mostly as a way to
178
+ recruit startups for series A rounds later. So VCs who invest in
179
+ angel rounds can blow up the valuations for angels and super-angels
180
+ who invest in them.
181
+ [6]Some super-angels seem to care about valuations. Several turned
182
+ down YC-funded startups after Demo Day because their valuations
183
+ were too high. This was not a problem for the startups; by definition
184
+ a high valuation means enough investors were willing to accept it.
185
+ But it was mysterious to me that the super-angels would quibble
186
+ about valuations. Did they not understand that the big returns
187
+ come from a few big successes, and that it therefore mattered far
188
+ more which startups you picked than how much you paid for them?After thinking about it for a while and observing certain other
189
+ signs, I have a theory that explains why the super-angels may be
190
+ smarter than they seem. It would make sense for super-angels to
191
+ want low valuations if they're hoping to invest in startups that
192
+ get bought early. If you're hoping to hit the next Google, you
193
+ shouldn't care if the valuation is 20 million. But if you're looking
194
+ for companies that are going to get bought for 30 million, you care.
195
+ If you invest at 20 and the company gets bought for 30, you only
196
+ get 1.5x. You might as well buy Apple.So if some of the super-angels were looking for companies that could
197
+ get acquired quickly, that would explain why they'd care about
198
+ valuations. But why would they be looking for those? Because
199
+ depending on the meaning of "quickly," it could actually be very
200
+ profitable. A company that gets acquired for 30 million is a failure
201
+ to a VC, but it could be a 10x return for an angel, and moreover,
202
+ a quick 10x return. Rate of return is what matters in
203
+ investing—not the multiple you get, but the multiple per year.
204
+ If a super-angel gets 10x in one year, that's a higher rate of
205
+ return than a VC could ever hope to get from a company that took 6
206
+ years to go public. To get the same rate of return, the VC would
207
+ have to get a multiple of 10^6—one million x. Even Google
208
+ didn't come close to that.So I think at least some super-angels are looking for companies
209
+ that will get bought. That's the only rational explanation for
210
+ focusing on getting the right valuations, instead of the right
211
+ companies. And if so they'll be different to deal with than VCs.
212
+ They'll be tougher on valuations, but more accommodating if you want
213
+ to sell early.PrognosisWho will win, the super-angels or the VCs? I think the answer to
214
+ that is, some of each. They'll each become more like one another.
215
+ The super-angels will start to invest larger amounts, and the VCs
216
+ will gradually figure out ways to make more, smaller investments
217
+ faster. A decade from now the players will be hard to tell apart,
218
+ and there will probably be survivors from each group.What does that mean for founders? One thing it means is that the
219
+ high valuations startups are presently getting may not last forever.
220
+ To the extent that valuations are being driven up by price-insensitive
221
+ VCs, they'll fall again if VCs become more like super-angels and
222
+ start to become more miserly about valuations. Fortunately if this
223
+ does happen it will take years.The short term forecast is more competition between investors, which
224
+ is good news for you. The super-angels will try to undermine the
225
+ VCs by acting faster, and the VCs will try to undermine the
226
+ super-angels by driving up valuations. Which for founders will
227
+ result in the perfect combination: funding rounds that close fast,
228
+ with high valuations.But remember that to get that combination, your startup will have
229
+ to appeal to both super-angels and VCs. If you don't seem like you
230
+ have the potential to go public, you won't be able to use VCs to
231
+ drive up the valuation of an angel round.There is a danger of having VCs in an angel round: the so-called
232
+ signalling risk. If VCs are only doing it in the hope of investing
233
+ more later, what happens if they don't? That's a signal to everyone
234
+ else that they think you're lame.How much should you worry about that? The seriousness of signalling
235
+ risk depends on how far along you are. If by the next time you
236
+ need to raise money, you have graphs showing rising revenue or
237
+ traffic month after month, you don't have to worry about any signals
238
+ your existing investors are sending. Your results will speak for
239
+ themselves.
240
+ [7]Whereas if the next time you need to raise money you won't yet have
241
+ concrete results, you may need to think more about the message your
242
+ investors might send if they don't invest more. I'm not sure yet
243
+ how much you have to worry, because this whole phenomenon of VCs
244
+ doing angel investments is so new. But my instincts tell me you
245
+ don't have to worry much. Signalling risk smells like one of those
246
+ things founders worry about that's not a real problem. As a rule,
247
+ the only thing that can kill a good startup is the startup itself.
248
+ Startups hurt themselves way more often than competitors hurt them,
249
+ for example. I suspect signalling risk is in this category too.One thing YC-funded startups have been doing to mitigate the risk
250
+ of taking money from VCs in angel rounds is not to take too much
251
+ from any one VC. Maybe that will help, if you have the luxury of
252
+ turning down money.Fortunately, more and more startups will. After decades of competition
253
+ that could best be described as intramural, the startup funding
254
+ business is finally getting some real competition. That should
255
+ last several years at least, and maybe a lot longer. Unless there's
256
+ some huge market crash, the next couple years are going to be a
257
+ good time for startups to raise money. And that's exciting because
258
+ it means lots more startups will happen.
259
+ Notes[1]
260
+ I've also heard them called "Mini-VCs" and "Micro-VCs." I
261
+ don't know which name will stick.There were a couple predecessors. Ron Conway had angel funds
262
+ starting in the 1990s, and in some ways First Round Capital is closer to a
263
+ super-angel than a VC fund.[2]
264
+ It wouldn't cut their overall returns tenfold, because investing
265
+ later would probably (a) cause them to lose less on investments
266
+ that failed, and (b) not allow them to get as large a percentage
267
+ of startups as they do now. So it's hard to predict precisely what
268
+ would happen to their returns.[3]
269
+ The brand of an investor derives mostly from the success of
270
+ their portfolio companies. The top VCs thus have a big brand
271
+ advantage over the super-angels. They could make it self-perpetuating
272
+ if they used it to get all the best new startups. But I don't think
273
+ they'll be able to. To get all the best startups, you have to do
274
+ more than make them want you. You also have to want them; you have
275
+ to recognize them when you see them, and that's much harder.
276
+ Super-angels will snap up stars that VCs miss. And that will cause
277
+ the brand gap between the top VCs and the super-angels gradually
278
+ to erode.[4]
279
+ Though in a traditional series A round VCs put two partners
280
+ on your board, there are signs now that VCs may begin to conserve
281
+ board seats by switching to what used to be considered an angel-round
282
+ board, consisting of two founders and one VC. Which is also to the
283
+ founders' advantage if it means they still control the company.[5]
284
+ In a series A round, you usually have to give up more than
285
+ the actual amount of stock the VCs buy, because they insist you
286
+ dilute yourselves to set aside an "option pool" as well. I predict
287
+ this practice will gradually disappear though.[6]
288
+ The best thing for founders, if they can get it, is a convertible
289
+ note with no valuation cap at all. In that case the money invested
290
+ in the angel round just converts into stock at the valuation of the
291
+ next round, no matter how large. Angels and super-angels tend not
292
+ to like uncapped notes. They have no idea how much of the company
293
+ they're buying. If the company does well and the valuation of the
294
+ next round is high, they may end up with only a sliver of it. So
295
+ by agreeing to uncapped notes, VCs who don't care about valuations
296
+ in angel rounds can make offers that super-angels hate to match.[7]
297
+ Obviously signalling risk is also not a problem if you'll
298
+ never need to raise more money. But startups are often mistaken
299
+ about that.Thanks to Sam Altman, John Bautista, Patrick Collison, James
300
+ Lindenbaum, Reid Hoffman, Jessica Livingston and Harj Taggar
301
+ for reading drafts
302
+ of this.
PaulGrahamEssays/todo.txt ADDED
@@ -0,0 +1,22 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ April 2012A palliative care nurse called Bronnie Ware made a list of the
2
+ biggest regrets
3
+ of the dying. Her list seems plausible. I could see
4
+ myself — can see myself — making at least 4 of these
5
+ 5 mistakes.If you had to compress them into a single piece of advice, it might
6
+ be: don't be a cog. The 5 regrets paint a portrait of post-industrial
7
+ man, who shrinks himself into a shape that fits his circumstances,
8
+ then turns dutifully till he stops.The alarming thing is, the mistakes that produce these regrets are
9
+ all errors of omission. You forget your dreams, ignore your family,
10
+ suppress your feelings, neglect your friends, and forget to be
11
+ happy. Errors of omission are a particularly dangerous type of
12
+ mistake, because you make them by default.I would like to avoid making these mistakes. But how do you avoid
13
+ mistakes you make by default? Ideally you transform your life so
14
+ it has other defaults. But it may not be possible to do that
15
+ completely. As long as these mistakes happen by default, you probably
16
+ have to be reminded not to make them. So I inverted the 5 regrets,
17
+ yielding a list of 5 commands
18
+
19
+ Don't ignore your dreams; don't work too much; say what you
20
+ think; cultivate friendships; be happy.
21
+
22
+ which I then put at the top of the file I use as a todo list.
PaulGrahamEssays/unions.txt ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ May 2007People who worry about the increasing gap between rich and poor
2
+ generally look back on the mid twentieth century as a golden age.
3
+ In those days we had a large number of high-paying union manufacturing
4
+ jobs that boosted the median income. I wouldn't quite call the
5
+ high-paying union job a myth, but I think people who dwell on it
6
+ are reading too much into it.Oddly enough, it was working with startups that made me realize
7
+ where the high-paying union job came from. In a rapidly growing
8
+ market, you don't worry too much about efficiency. It's more
9
+ important to grow fast. If there's some mundane problem getting
10
+ in your way, and there's a simple solution that's somewhat expensive,
11
+ just take it and get on with more important things. EBay didn't
12
+ win by paying less for servers than their competitors.Difficult though it may be to imagine now, manufacturing was a
13
+ growth industry in the mid twentieth century. This was an era when
14
+ small firms making everything from cars to candy were getting
15
+ consolidated into a new kind of corporation with national reach and
16
+ huge economies of scale. You had to grow fast or die. Workers
17
+ were for these companies what servers are for an Internet startup.
18
+ A reliable supply was more important than low cost.If you looked in the head of a 1950s auto executive, the attitude
19
+ must have been: sure, give 'em whatever they ask for, so long as
20
+ the new model isn't delayed.In other words, those workers were not paid what their work was
21
+ worth. Circumstances being what they were, companies would have
22
+ been stupid to insist on paying them so little.If you want a less controversial example of this phenomenon, ask
23
+ anyone who worked as a consultant building web sites during the
24
+ Internet Bubble. In the late nineties you could get paid huge sums
25
+ of money for building the most trivial things. And yet does anyone
26
+ who was there have any expectation those days will ever return? I
27
+ doubt it. Surely everyone realizes that was just a temporary
28
+ aberration.The era of labor unions seems to have been the same kind of aberration,
29
+ just spread
30
+ over a longer period, and mixed together with a lot of ideology
31
+ that prevents people from viewing it with as cold an eye as they
32
+ would something like consulting during the Bubble.Basically, unions were just Razorfish.People who think the labor movement was the creation of heroic union
33
+ organizers have a problem to explain: why are unions shrinking now?
34
+ The best they can do is fall back on the default explanation of
35
+ people living in fallen civilizations. Our ancestors were giants.
36
+ The workers of the early twentieth century must have had a moral
37
+ courage that's lacking today.In fact there's a simpler explanation. The early twentieth century
38
+ was just a fast-growing startup overpaying for infrastructure. And
39
+ we in the present are not a fallen people, who have abandoned
40
+ whatever mysterious high-minded principles produced the high-paying
41
+ union job. We simply live in a time when the fast-growing companies
42
+ overspend on different things.
PaulGrahamEssays/useful.txt ADDED
@@ -0,0 +1,225 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ February 2020What should an essay be? Many people would say persuasive. That's
2
+ what a lot of us were taught essays should be. But I think we can
3
+ aim for something more ambitious: that an essay should be useful.To start with, that means it should be correct. But it's not enough
4
+ merely to be correct. It's easy to make a statement correct by
5
+ making it vague. That's a common flaw in academic writing, for
6
+ example. If you know nothing at all about an issue, you can't go
7
+ wrong by saying that the issue is a complex one, that there are
8
+ many factors to be considered, that it's a mistake to take too
9
+ simplistic a view of it, and so on.Though no doubt correct, such statements tell the reader nothing.
10
+ Useful writing makes claims that are as strong as they can be made
11
+ without becoming false.For example, it's more useful to say that Pike's Peak is near the
12
+ middle of Colorado than merely somewhere in Colorado. But if I say
13
+ it's in the exact middle of Colorado, I've now gone too far, because
14
+ it's a bit east of the middle.Precision and correctness are like opposing forces. It's easy to
15
+ satisfy one if you ignore the other. The converse of vaporous
16
+ academic writing is the bold, but false, rhetoric of demagogues.
17
+ Useful writing is bold, but true.It's also two other things: it tells people something important,
18
+ and that at least some of them didn't already know.Telling people something they didn't know doesn't always mean
19
+ surprising them. Sometimes it means telling them something they
20
+ knew unconsciously but had never put into words. In fact those may
21
+ be the more valuable insights, because they tend to be more
22
+ fundamental.Let's put them all together. Useful writing tells people something
23
+ true and important that they didn't already know, and tells them
24
+ as unequivocally as possible.Notice these are all a matter of degree. For example, you can't
25
+ expect an idea to be novel to everyone. Any insight that you have
26
+ will probably have already been had by at least one of the world's
27
+ 7 billion people. But it's sufficient if an idea is novel to a lot
28
+ of readers.Ditto for correctness, importance, and strength. In effect the four
29
+ components are like numbers you can multiply together to get a score
30
+ for usefulness. Which I realize is almost awkwardly reductive, but
31
+ nonetheless true._____
32
+ How can you ensure that the things you say are true and novel and
33
+ important? Believe it or not, there is a trick for doing this. I
34
+ learned it from my friend Robert Morris, who has a horror of saying
35
+ anything dumb. His trick is not to say anything unless he's sure
36
+ it's worth hearing. This makes it hard to get opinions out of him,
37
+ but when you do, they're usually right.Translated into essay writing, what this means is that if you write
38
+ a bad sentence, you don't publish it. You delete it and try again.
39
+ Often you abandon whole branches of four or five paragraphs. Sometimes
40
+ a whole essay.You can't ensure that every idea you have is good, but you can
41
+ ensure that every one you publish is, by simply not publishing the
42
+ ones that aren't.In the sciences, this is called publication bias, and is considered
43
+ bad. When some hypothesis you're exploring gets inconclusive results,
44
+ you're supposed to tell people about that too. But with essay
45
+ writing, publication bias is the way to go.My strategy is loose, then tight. I write the first draft of an
46
+ essay fast, trying out all kinds of ideas. Then I spend days rewriting
47
+ it very carefully.I've never tried to count how many times I proofread essays, but
48
+ I'm sure there are sentences I've read 100 times before publishing
49
+ them. When I proofread an essay, there are usually passages that
50
+ stick out in an annoying way, sometimes because they're clumsily
51
+ written, and sometimes because I'm not sure they're true. The
52
+ annoyance starts out unconscious, but after the tenth reading or
53
+ so I'm saying "Ugh, that part" each time I hit it. They become like
54
+ briars that catch your sleeve as you walk past. Usually I won't
55
+ publish an essay till they're all gone — till I can read through
56
+ the whole thing without the feeling of anything catching.I'll sometimes let through a sentence that seems clumsy, if I can't
57
+ think of a way to rephrase it, but I will never knowingly let through
58
+ one that doesn't seem correct. You never have to. If a sentence
59
+ doesn't seem right, all you have to do is ask why it doesn't, and
60
+ you've usually got the replacement right there in your head.This is where essayists have an advantage over journalists. You
61
+ don't have a deadline. You can work for as long on an essay as you
62
+ need to get it right. You don't have to publish the essay at all,
63
+ if you can't get it right. Mistakes seem to lose courage in the
64
+ face of an enemy with unlimited resources. Or that's what it feels
65
+ like. What's really going on is that you have different expectations
66
+ for yourself. You're like a parent saying to a child "we can sit
67
+ here all night till you eat your vegetables." Except you're the
68
+ child too.I'm not saying no mistake gets through. For example, I added condition
69
+ (c) in "A Way to Detect Bias"
70
+ after readers pointed out that I'd
71
+ omitted it. But in practice you can catch nearly all of them.There's a trick for getting importance too. It's like the trick I
72
+ suggest to young founders for getting startup ideas: to make something
73
+ you yourself want. You can use yourself as a proxy for the reader.
74
+ The reader is not completely unlike you, so if you write about
75
+ topics that seem important to you, they'll probably seem important
76
+ to a significant number of readers as well.Importance has two factors. It's the number of people something
77
+ matters to, times how much it matters to them. Which means of course
78
+ that it's not a rectangle, but a sort of ragged comb, like a Riemann
79
+ sum.The way to get novelty is to write about topics you've thought about
80
+ a lot. Then you can use yourself as a proxy for the reader in this
81
+ department too. Anything you notice that surprises you, who've
82
+ thought about the topic a lot, will probably also surprise a
83
+ significant number of readers. And here, as with correctness and
84
+ importance, you can use the Morris technique to ensure that you
85
+ will. If you don't learn anything from writing an essay, don't
86
+ publish it.You need humility to measure novelty, because acknowledging the
87
+ novelty of an idea means acknowledging your previous ignorance of
88
+ it. Confidence and humility are often seen as opposites, but in
89
+ this case, as in many others, confidence helps you to be humble.
90
+ If you know you're an expert on some topic, you can freely admit
91
+ when you learn something you didn't know, because you can be confident
92
+ that most other people wouldn't know it either.The fourth component of useful writing, strength, comes from two
93
+ things: thinking well, and the skillful use of qualification. These
94
+ two counterbalance each other, like the accelerator and clutch in
95
+ a car with a manual transmission. As you try to refine the expression
96
+ of an idea, you adjust the qualification accordingly. Something
97
+ you're sure of, you can state baldly with no qualification at all,
98
+ as I did the four components of useful writing. Whereas points that
99
+ seem dubious have to be held at arm's length with perhapses.As you refine an idea, you're pushing in the direction of less
100
+ qualification. But you can rarely get it down to zero. Sometimes
101
+ you don't even want to, if it's a side point and a fully refined
102
+ version would be too long.Some say that qualifications weaken writing. For example, that you
103
+ should never begin a sentence in an essay with "I think," because
104
+ if you're saying it, then of course you think it. And it's true
105
+ that "I think x" is a weaker statement than simply "x." Which is
106
+ exactly why you need "I think." You need it to express your degree
107
+ of certainty.But qualifications are not scalars. They're not just experimental
108
+ error. There must be 50 things they can express: how broadly something
109
+ applies, how you know it, how happy you are it's so, even how it
110
+ could be falsified. I'm not going to try to explore the structure
111
+ of qualification here. It's probably more complex than the whole
112
+ topic of writing usefully. Instead I'll just give you a practical
113
+ tip: Don't underestimate qualification. It's an important skill in
114
+ its own right, not just a sort of tax you have to pay in order to
115
+ avoid saying things that are false. So learn and use its full range.
116
+ It may not be fully half of having good ideas, but it's part of
117
+ having them.There's one other quality I aim for in essays: to say things as
118
+ simply as possible. But I don't think this is a component of
119
+ usefulness. It's more a matter of consideration for the reader. And
120
+ it's a practical aid in getting things right; a mistake is more
121
+ obvious when expressed in simple language. But I'll admit that the
122
+ main reason I write simply is not for the reader's sake or because
123
+ it helps get things right, but because it bothers me to use more
124
+ or fancier words than I need to. It seems inelegant, like a program
125
+ that's too long.I realize florid writing works for some people. But unless you're
126
+ sure you're one of them, the best advice is to write as simply as
127
+ you can._____
128
+ I believe the formula I've given you, importance + novelty +
129
+ correctness + strength, is the recipe for a good essay. But I should
130
+ warn you that it's also a recipe for making people mad.The root of the problem is novelty. When you tell people something
131
+ they didn't know, they don't always thank you for it. Sometimes the
132
+ reason people don't know something is because they don't want to
133
+ know it. Usually because it contradicts some cherished belief. And
134
+ indeed, if you're looking for novel ideas, popular but mistaken
135
+ beliefs are a good place to find them. Every popular mistaken belief
136
+ creates a dead zone of ideas around
137
+ it that are relatively unexplored because they contradict it.The strength component just makes things worse. If there's anything
138
+ that annoys people more than having their cherished assumptions
139
+ contradicted, it's having them flatly contradicted.Plus if you've used the Morris technique, your writing will seem
140
+ quite confident. Perhaps offensively confident, to people who
141
+ disagree with you. The reason you'll seem confident is that you are
142
+ confident: you've cheated, by only publishing the things you're
143
+ sure of. It will seem to people who try to disagree with you that
144
+ you never admit you're wrong. In fact you constantly admit you're
145
+ wrong. You just do it before publishing instead of after.And if your writing is as simple as possible, that just makes things
146
+ worse. Brevity is the diction of command. If you watch someone
147
+ delivering unwelcome news from a position of inferiority, you'll
148
+ notice they tend to use lots of words, to soften the blow. Whereas
149
+ to be short with someone is more or less to be rude to them.It can sometimes work to deliberately phrase statements more weakly
150
+ than you mean. To put "perhaps" in front of something you're actually
151
+ quite sure of. But you'll notice that when writers do this, they
152
+ usually do it with a wink.I don't like to do this too much. It's cheesy to adopt an ironic
153
+ tone for a whole essay. I think we just have to face the fact that
154
+ elegance and curtness are two names for the same thing.You might think that if you work sufficiently hard to ensure that
155
+ an essay is correct, it will be invulnerable to attack. That's sort
156
+ of true. It will be invulnerable to valid attacks. But in practice
157
+ that's little consolation.In fact, the strength component of useful writing will make you
158
+ particularly vulnerable to misrepresentation. If you've stated an
159
+ idea as strongly as you could without making it false, all anyone
160
+ has to do is to exaggerate slightly what you said, and now it is
161
+ false.Much of the time they're not even doing it deliberately. One of the
162
+ most surprising things you'll discover, if you start writing essays,
163
+ is that people who disagree with you rarely disagree with what
164
+ you've actually written. Instead they make up something you said
165
+ and disagree with that.For what it's worth, the countermove is to ask someone who does
166
+ this to quote a specific sentence or passage you wrote that they
167
+ believe is false, and explain why. I say "for what it's worth"
168
+ because they never do. So although it might seem that this could
169
+ get a broken discussion back on track, the truth is that it was
170
+ never on track in the first place.Should you explicitly forestall likely misinterpretations? Yes, if
171
+ they're misinterpretations a reasonably smart and well-intentioned
172
+ person might make. In fact it's sometimes better to say something
173
+ slightly misleading and then add the correction than to try to get
174
+ an idea right in one shot. That can be more efficient, and can also
175
+ model the way such an idea would be discovered.But I don't think you should explicitly forestall intentional
176
+ misinterpretations in the body of an essay. An essay is a place to
177
+ meet honest readers. You don't want to spoil your house by putting
178
+ bars on the windows to protect against dishonest ones. The place
179
+ to protect against intentional misinterpretations is in end-notes.
180
+ But don't think you can predict them all. People are as ingenious
181
+ at misrepresenting you when you say something they don't want to
182
+ hear as they are at coming up with rationalizations for things they
183
+ want to do but know they shouldn't. I suspect it's the same skill._____
184
+ As with most other things, the way to get better at writing essays
185
+ is to practice. But how do you start? Now that we've examined the
186
+ structure of useful writing, we can rephrase that question more
187
+ precisely. Which constraint do you relax initially? The answer is,
188
+ the first component of importance: the number of people who care
189
+ about what you write.If you narrow the topic sufficiently, you can probably find something
190
+ you're an expert on. Write about that to start with. If you only
191
+ have ten readers who care, that's fine. You're helping them, and
192
+ you're writing. Later you can expand the breadth of topics you write
193
+ about.The other constraint you can relax is a little surprising: publication.
194
+ Writing essays doesn't have to mean publishing them. That may seem
195
+ strange now that the trend is to publish every random thought, but
196
+ it worked for me. I wrote what amounted to essays in notebooks for
197
+ about 15 years. I never published any of them and never expected
198
+ to. I wrote them as a way of figuring things out. But when the web
199
+ came along I'd had a lot of practice.Incidentally,
200
+ Steve
201
+ Wozniak did the same thing. In high school he
202
+ designed computers on paper for fun. He couldn't build them because
203
+ he couldn't afford the components. But when Intel launched 4K DRAMs
204
+ in 1975, he was ready._____
205
+ How many essays are there left to write though? The answer to that
206
+ question is probably the most exciting thing I've learned about
207
+ essay writing. Nearly all of them are left to write.Although the essay
208
+ is an old form, it hasn't been assiduously
209
+ cultivated. In the print era, publication was expensive, and there
210
+ wasn't enough demand for essays to publish that many. You could
211
+ publish essays if you were already well known for writing something
212
+ else, like novels. Or you could write book reviews that you took
213
+ over to express your own ideas. But there was not really a direct
214
+ path to becoming an essayist. Which meant few essays got written,
215
+ and those that did tended to be about a narrow range of subjects.Now, thanks to the internet, there's a path. Anyone can publish
216
+ essays online. You start in obscurity, perhaps, but at least you
217
+ can start. You don't need anyone's permission.It sometimes happens that an area of knowledge sits quietly for
218
+ years, till some change makes it explode. Cryptography did this to
219
+ number theory. The internet is doing it to the essay.The exciting thing is not that there's a lot left to write, but
220
+ that there's a lot left to discover. There's a certain kind of idea
221
+ that's best discovered by writing essays. If most essays are still
222
+ unwritten, most such ideas are still undiscovered.Notes[1] Put railings on the balconies, but don't put bars on the windows.[2] Even now I sometimes write essays that are not meant for
223
+ publication. I wrote several to figure out what Y Combinator should
224
+ do, and they were really helpful.Thanks to Trevor Blackwell, Daniel Gackle, Jessica Livingston, and
225
+ Robert Morris for reading drafts of this.
PaulGrahamEssays/vb.txt ADDED
@@ -0,0 +1,129 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ January 2016Life is short, as everyone knows. When I was a kid I used to wonder
2
+ about this. Is life actually short, or are we really complaining
3
+ about its finiteness? Would we be just as likely to feel life was
4
+ short if we lived 10 times as long?Since there didn't seem any way to answer this question, I stopped
5
+ wondering about it. Then I had kids. That gave me a way to answer
6
+ the question, and the answer is that life actually is short.Having kids showed me how to convert a continuous quantity, time,
7
+ into discrete quantities. You only get 52 weekends with your 2 year
8
+ old. If Christmas-as-magic lasts from say ages 3 to 10, you only
9
+ get to watch your child experience it 8 times. And while it's
10
+ impossible to say what is a lot or a little of a continuous quantity
11
+ like time, 8 is not a lot of something. If you had a handful of 8
12
+ peanuts, or a shelf of 8 books to choose from, the quantity would
13
+ definitely seem limited, no matter what your lifespan was.Ok, so life actually is short. Does it make any difference to know
14
+ that?It has for me. It means arguments of the form "Life is too short
15
+ for x" have great force. It's not just a figure of speech to say
16
+ that life is too short for something. It's not just a synonym for
17
+ annoying. If you find yourself thinking that life is too short for
18
+ something, you should try to eliminate it if you can.When I ask myself what I've found life is too short for, the word
19
+ that pops into my head is "bullshit." I realize that answer is
20
+ somewhat tautological. It's almost the definition of bullshit that
21
+ it's the stuff that life is too short for. And yet bullshit does
22
+ have a distinctive character. There's something fake about it.
23
+ It's the junk food of experience.
24
+ [1]If you ask yourself what you spend your time on that's bullshit,
25
+ you probably already know the answer. Unnecessary meetings, pointless
26
+ disputes, bureaucracy, posturing, dealing with other people's
27
+ mistakes, traffic jams, addictive but unrewarding pastimes.There are two ways this kind of thing gets into your life: it's
28
+ either forced on you, or it tricks you. To some extent you have to
29
+ put up with the bullshit forced on you by circumstances. You need
30
+ to make money, and making money consists mostly of errands. Indeed,
31
+ the law of supply and demand insures that: the more rewarding some
32
+ kind of work is, the cheaper people will do it. It may be that
33
+ less bullshit is forced on you than you think, though. There has
34
+ always been a stream of people who opt out of the default grind and
35
+ go live somewhere where opportunities are fewer in the conventional
36
+ sense, but life feels more authentic. This could become more common.You can do it on a smaller scale without moving. The amount of
37
+ time you have to spend on bullshit varies between employers. Most
38
+ large organizations (and many small ones) are steeped in it. But
39
+ if you consciously prioritize bullshit avoidance over other factors
40
+ like money and prestige, you can probably find employers that will
41
+ waste less of your time.If you're a freelancer or a small company, you can do this at the
42
+ level of individual customers. If you fire or avoid toxic customers,
43
+ you can decrease the amount of bullshit in your life by more than
44
+ you decrease your income.But while some amount of bullshit is inevitably forced on you, the
45
+ bullshit that sneaks into your life by tricking you is no one's
46
+ fault but your own. And yet the bullshit you choose may be harder
47
+ to eliminate than the bullshit that's forced on you. Things that
48
+ lure you into wasting your time have to be really good at
49
+ tricking you. An example that will be familiar to a lot of people
50
+ is arguing online. When someone
51
+ contradicts you, they're in a sense attacking you. Sometimes pretty
52
+ overtly. Your instinct when attacked is to defend yourself. But
53
+ like a lot of instincts, this one wasn't designed for the world we
54
+ now live in. Counterintuitive as it feels, it's better most of
55
+ the time not to defend yourself. Otherwise these people are literally
56
+ taking your life.
57
+ [2]Arguing online is only incidentally addictive. There are more
58
+ dangerous things than that. As I've written before, one byproduct
59
+ of technical progress is that things we like tend to become more
60
+ addictive. Which means we will increasingly have to make a conscious
61
+ effort to avoid addictions — to stand outside ourselves and ask "is
62
+ this how I want to be spending my time?"As well as avoiding bullshit, one should actively seek out things
63
+ that matter. But different things matter to different people, and
64
+ most have to learn what matters to them. A few are lucky and realize
65
+ early on that they love math or taking care of animals or writing,
66
+ and then figure out a way to spend a lot of time doing it. But
67
+ most people start out with a life that's a mix of things that
68
+ matter and things that don't, and only gradually learn to distinguish
69
+ between them.For the young especially, much of this confusion is induced by the
70
+ artificial situations they find themselves in. In middle school and
71
+ high school, what the other kids think of you seems the most important
72
+ thing in the world. But when you ask adults what they got wrong
73
+ at that age, nearly all say they cared too much what other kids
74
+ thought of them.One heuristic for distinguishing stuff that matters is to ask
75
+ yourself whether you'll care about it in the future. Fake stuff
76
+ that matters usually has a sharp peak of seeming to matter. That's
77
+ how it tricks you. The area under the curve is small, but its shape
78
+ jabs into your consciousness like a pin.The things that matter aren't necessarily the ones people would
79
+ call "important." Having coffee with a friend matters. You won't
80
+ feel later like that was a waste of time.One great thing about having small children is that they make you
81
+ spend time on things that matter: them. They grab your sleeve as
82
+ you're staring at your phone and say "will you play with me?" And
83
+ odds are that is in fact the bullshit-minimizing option.If life is short, we should expect its shortness to take us by
84
+ surprise. And that is just what tends to happen. You take things
85
+ for granted, and then they're gone. You think you can always write
86
+ that book, or climb that mountain, or whatever, and then you realize
87
+ the window has closed. The saddest windows close when other people
88
+ die. Their lives are short too. After my mother died, I wished I'd
89
+ spent more time with her. I lived as if she'd always be there.
90
+ And in her typical quiet way she encouraged that illusion. But an
91
+ illusion it was. I think a lot of people make the same mistake I
92
+ did.The usual way to avoid being taken by surprise by something is to
93
+ be consciously aware of it. Back when life was more precarious,
94
+ people used to be aware of death to a degree that would now seem a
95
+ bit morbid. I'm not sure why, but it doesn't seem the right answer
96
+ to be constantly reminding oneself of the grim reaper hovering at
97
+ everyone's shoulder. Perhaps a better solution is to look at the
98
+ problem from the other end. Cultivate a habit of impatience about
99
+ the things you most want to do. Don't wait before climbing that
100
+ mountain or writing that book or visiting your mother. You don't
101
+ need to be constantly reminding yourself why you shouldn't wait.
102
+ Just don't wait.I can think of two more things one does when one doesn't have much
103
+ of something: try to get more of it, and savor what one has. Both
104
+ make sense here.How you live affects how long you live. Most people could do better.
105
+ Me among them.But you can probably get even more effect by paying closer attention
106
+ to the time you have. It's easy to let the days rush by. The
107
+ "flow" that imaginative people love so much has a darker cousin
108
+ that prevents you from pausing to savor life amid the daily slurry
109
+ of errands and alarms. One of the most striking things I've read
110
+ was not in a book, but the title of one: James Salter's Burning
111
+ the Days.It is possible to slow time somewhat. I've gotten better at it.
112
+ Kids help. When you have small children, there are a lot of moments
113
+ so perfect that you can't help noticing.It does help too to feel that you've squeezed everything out of
114
+ some experience. The reason I'm sad about my mother is not just
115
+ that I miss her but that I think of all the things we could have
116
+ done that we didn't. My oldest son will be 7 soon. And while I
117
+ miss the 3 year old version of him, I at least don't have any regrets
118
+ over what might have been. We had the best time a daddy and a 3
119
+ year old ever had.Relentlessly prune bullshit, don't wait to do things that matter,
120
+ and savor the time you have. That's what you do when life is short.Notes[1]
121
+ At first I didn't like it that the word that came to mind was
122
+ one that had other meanings. But then I realized the other meanings
123
+ are fairly closely related. Bullshit in the sense of things you
124
+ waste your time on is a lot like intellectual bullshit.[2]
125
+ I chose this example deliberately as a note to self. I get
126
+ attacked a lot online. People tell the craziest lies about me.
127
+ And I have so far done a pretty mediocre job of suppressing the
128
+ natural human inclination to say "Hey, that's not true!"Thanks to Jessica Livingston and Geoff Ralston for reading drafts
129
+ of this.
PaulGrahamEssays/vcsqueeze.txt ADDED
@@ -0,0 +1,124 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ November 2005In the next few years, venture capital funds will find themselves
2
+ squeezed from four directions. They're already stuck with a seller's
3
+ market, because of the huge amounts they raised at the end of the
4
+ Bubble and still haven't invested. This by itself is not the end
5
+ of the world. In fact, it's just a more extreme version of the
6
+ norm
7
+ in the VC business: too much money chasing too few deals.Unfortunately, those few deals now want less and less money, because
8
+ it's getting so cheap to start a startup. The four causes: open
9
+ source, which makes software free; Moore's law, which makes hardware
10
+ geometrically closer to free; the Web, which makes promotion free
11
+ if you're good; and better languages, which make development a lot
12
+ cheaper.When we started our startup in 1995, the first three were our biggest
13
+ expenses. We had to pay $5000 for the Netscape Commerce Server,
14
+ the only software that then supported secure http connections. We
15
+ paid $3000 for a server with a 90 MHz processor and 32 meg of
16
+ memory. And we paid a PR firm about $30,000 to promote our launch.Now you could get all three for nothing. You can get the software
17
+ for free; people throw away computers more powerful than our first
18
+ server; and if you make something good you can generate ten times
19
+ as much traffic by word of mouth online than our first PR firm got
20
+ through the print media.And of course another big change for the average startup is that
21
+ programming languages have improved-- or rather, the median language has. At most startups ten years
22
+ ago, software development meant ten programmers writing code in
23
+ C++. Now the same work might be done by one or two using Python
24
+ or Ruby.During the Bubble, a lot of people predicted that startups would
25
+ outsource their development to India. I think a better model for
26
+ the future is David Heinemeier Hansson, who outsourced his development
27
+ to a more powerful language instead. A lot of well-known applications
28
+ are now, like BaseCamp, written by just one programmer. And one
29
+ guy is more than 10x cheaper than ten, because (a) he won't waste
30
+ any time in meetings, and (b) since he's probably a founder, he can
31
+ pay himself nothing.Because starting a startup is so cheap, venture capitalists now
32
+ often want to give startups more money than the startups want to
33
+ take. VCs like to invest several million at a time. But as one
34
+ VC told me after a startup he funded would only take about half a
35
+ million, "I don't know what we're going to do. Maybe we'll just
36
+ have to give some of it back." Meaning give some of the fund back
37
+ to the institutional investors who supplied it, because it wasn't
38
+ going to be possible to invest it all.Into this already bad situation comes the third problem: Sarbanes-Oxley.
39
+ Sarbanes-Oxley is a law, passed after the Bubble, that drastically
40
+ increases the regulatory burden on public companies. And in addition
41
+ to the cost of compliance, which is at least two million dollars a
42
+ year, the law introduces frightening legal exposure for corporate
43
+ officers. An experienced CFO I know said flatly: "I would not
44
+ want to be CFO of a public company now."You might think that responsible corporate governance is an area
45
+ where you can't go too far. But you can go too far in any law, and
46
+ this remark convinced me that Sarbanes-Oxley must have. This CFO
47
+ is both the smartest and the most upstanding money guy I know. If
48
+ Sarbanes-Oxley deters people like him from being CFOs of public
49
+ companies, that's proof enough that it's broken.Largely because of Sarbanes-Oxley, few startups go public now. For
50
+ all practical purposes, succeeding now equals getting bought. Which
51
+ means VCs are now in the business of finding promising little 2-3
52
+ man startups and pumping them up into companies that cost $100
53
+ million to acquire. They didn't mean to be in this business; it's
54
+ just what their business has evolved into.Hence the fourth problem: the acquirers have begun to realize they
55
+ can buy wholesale. Why should they wait for VCs to make the startups
56
+ they want more expensive? Most of what the VCs add, acquirers don't
57
+ want anyway. The acquirers already have brand recognition and HR
58
+ departments. What they really want is the software and the developers,
59
+ and that's what the startup is in the early phase: concentrated
60
+ software and developers.Google, typically, seems to have been the first to figure this out.
61
+ "Bring us your startups early," said Google's speaker at the Startup School. They're quite
62
+ explicit about it: they like to acquire startups at just the point
63
+ where they would do a Series A round. (The Series A round is the
64
+ first round of real VC funding; it usually happens in the first
65
+ year.) It is a brilliant strategy, and one that other big technology
66
+ companies will no doubt try to duplicate. Unless they want to have
67
+ still more of their lunch eaten by Google.Of course, Google has an advantage in buying startups: a lot of the
68
+ people there are rich, or expect to be when their options vest.
69
+ Ordinary employees find it very hard to recommend an acquisition;
70
+ it's just too annoying to see a bunch of twenty year olds get rich
71
+ when you're still working for salary. Even if it's the right thing
72
+ for your company to do.The Solution(s)Bad as things look now, there is a way for VCs to save themselves.
73
+ They need to do two things, one of which won't surprise them, and
74
+ another that will seem an anathema.Let's start with the obvious one: lobby to get Sarbanes-Oxley
75
+ loosened. This law was created to prevent future Enrons, not to
76
+ destroy the IPO market. Since the IPO market was practically dead
77
+ when it passed, few saw what bad effects it would have. But now
78
+ that technology has recovered from the last bust, we can see clearly
79
+ what a bottleneck Sarbanes-Oxley has become.Startups are fragile plants—seedlings, in fact. These seedlings
80
+ are worth protecting, because they grow into the trees of the
81
+ economy. Much of the economy's growth is their growth. I think
82
+ most politicians realize that. But they don't realize just how
83
+ fragile startups are, and how easily they can become collateral
84
+ damage of laws meant to fix some other problem.Still more dangerously, when you destroy startups, they make very
85
+ little noise. If you step on the toes of the coal industry, you'll
86
+ hear about it. But if you inadvertantly squash the startup industry,
87
+ all that happens is that the founders of the next Google stay in
88
+ grad school instead of starting a company.My second suggestion will seem shocking to VCs: let founders cash
89
+ out partially in the Series A round. At the moment, when VCs invest
90
+ in a startup, all the stock they get is newly issued and all the
91
+ money goes to the company. They could buy some stock directly from
92
+ the founders as well.Most VCs have an almost religious rule against doing this. They
93
+ don't want founders to get a penny till the company is sold or goes
94
+ public. VCs are obsessed with control, and they worry that they'll
95
+ have less leverage over the founders if the founders have any money.This is a dumb plan. In fact, letting the founders sell a little stock
96
+ early would generally be better for the company, because it would
97
+ cause the founders' attitudes toward risk to be aligned with the
98
+ VCs'. As things currently work, their attitudes toward risk tend
99
+ to be diametrically opposed: the founders, who have nothing, would
100
+ prefer a 100% chance of $1 million to a 20% chance of $10 million,
101
+ while the VCs can afford to be "rational" and prefer the latter.Whatever they say, the reason founders are selling their companies
102
+ early instead of doing Series A rounds is that they get paid up
103
+ front. That first million is just worth so much more than the
104
+ subsequent ones. If founders could sell a little stock early,
105
+ they'd be happy to take VC money and bet the rest on a bigger
106
+ outcome.So why not let the founders have that first million, or at least
107
+ half million? The VCs would get same number of shares for the
108
+ money. So what if some of the money would go to the
109
+ founders instead of the company?Some VCs will say this is
110
+ unthinkable—that they want all their money to be put to work
111
+ growing the company. But the fact is, the huge size of current VC
112
+ investments is dictated by the structure
113
+ of VC funds, not the needs of startups. Often as not these large
114
+ investments go to work destroying the company rather than growing
115
+ it.The angel investors who funded our startup let the founders sell
116
+ some stock directly to them, and it was a good deal for everyone.
117
+ The angels made a huge return on that investment, so they're happy.
118
+ And for us founders it blunted the terrifying all-or-nothingness
119
+ of a startup, which in its raw form is more a distraction than a
120
+ motivator.If VCs are frightened at the idea of letting founders partially
121
+ cash out, let me tell them something still more frightening: you
122
+ are now competing directly with Google.
123
+ Thanks to Trevor Blackwell, Sarah Harlin, Jessica
124
+ Livingston, and Robert Morris for reading drafts of this.
PaulGrahamEssays/vw.txt ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ January 2012A few hours before the Yahoo acquisition was announced in June 1998
2
+ I took a snapshot of Viaweb's
3
+ site. I thought it might be interesting to look at one day.The first thing one notices is is how tiny the pages are. Screens
4
+ were a lot smaller in 1998. If I remember correctly, our frontpage
5
+ used to just fit in the size window people typically used then.Browsers then (IE 6 was still 3 years in the future) had few fonts
6
+ and they weren't antialiased. If you wanted to make pages that
7
+ looked good, you had to render display text as images.You may notice a certain similarity between the Viaweb and Y Combinator logos. We did that
8
+ as an inside joke when we started YC. Considering how basic a red
9
+ circle is, it seemed surprising to me when we started Viaweb how
10
+ few other companies used one as their logo. A bit later I realized
11
+ why.On the Company
12
+ page you'll notice a mysterious individual called John McArtyem.
13
+ Robert Morris (aka Rtm) was so publicity averse after the
14
+ Worm that he
15
+ didn't want his name on the site. I managed to get him to agree
16
+ to a compromise: we could use his bio but not his name. He has
17
+ since relaxed a bit
18
+ on that point.Trevor graduated at about the same time the acquisition closed, so in the
19
+ course of 4 days he went from impecunious grad student to millionaire
20
+ PhD. The culmination of my career as a writer of press releases
21
+ was one celebrating
22
+ his graduation, illustrated with a drawing I did of him during
23
+ a meeting.(Trevor also appears as Trevino
24
+ Bagwell in our directory of web designers merchants could hire
25
+ to build stores for them. We inserted him as a ringer in case some
26
+ competitor tried to spam our web designers. We assumed his logo
27
+ would deter any actual customers, but it did not.)Back in the 90s, to get users you had to get mentioned in magazines
28
+ and newspapers. There were not the same ways to get found online
29
+ that there are today. So we used to pay a PR
30
+ firm $16,000 a month to get us mentioned in the press. Fortunately
31
+ reporters liked
32
+ us.In our advice about
33
+ getting traffic from search engines (I don't think the term SEO
34
+ had been coined yet), we say there are only 7 that matter: Yahoo,
35
+ AltaVista, Excite, WebCrawler, InfoSeek, Lycos, and HotBot. Notice
36
+ anything missing? Google was incorporated that September.We supported online transactions via a company called
37
+ Cybercash,
38
+ since if we lacked that feature we'd have gotten beaten up in product
39
+ comparisons. But Cybercash was so bad and most stores' order volumes
40
+ were so low that it was better if merchants processed orders like phone orders. We had a page in our site trying to talk merchants
41
+ out of doing real time authorizations.The whole site was organized like a funnel, directing people to the
42
+ test drive.
43
+ It was a novel thing to be able to try out software online. We put
44
+ cgi-bin in our dynamic urls to fool competitors about how our
45
+ software worked.We had some well
46
+ known users. Needless to say, Frederick's of Hollywood got the
47
+ most traffic. We charged a flat fee of $300/month for big stores,
48
+ so it was a little alarming to have users who got lots of traffic.
49
+ I once calculated how much Frederick's was costing us in bandwidth,
50
+ and it was about $300/month.Since we hosted all the stores, which together were getting just
51
+ over 10 million page views per month in June 1998, we consumed what
52
+ at the time seemed a lot of bandwidth. We had 2 T1s (3 Mb/sec)
53
+ coming into our offices. In those days there was no AWS. Even
54
+ colocating servers seemed too risky, considering how often things
55
+ went wrong with them. So we had our servers in our offices. Or
56
+ more precisely, in Trevor's office. In return for the unique
57
+ privilege of sharing his office with no other humans, he had to
58
+ share it with 6 shrieking tower servers. His office was nicknamed
59
+ the Hot Tub on account of the heat they generated. Most days his
60
+ stack of window air conditioners could keep up.For describing pages, we had a template language called RTML, which
61
+ supposedly stood for something, but which in fact I named after
62
+ Rtm. RTML was Common Lisp augmented by some macros and libraries,
63
+ and concealed under a structure editor that made it look like it
64
+ had syntax.Since we did continuous releases, our software didn't actually have
65
+ versions. But in those days the trade press expected versions, so
66
+ we made them up. If we wanted to get lots of attention, we made
67
+ the version number an
68
+ integer. That "version 4.0" icon was generated by our own
69
+ button generator, incidentally. The whole Viaweb site was made
70
+ with our software, even though it wasn't an online store, because
71
+ we wanted to experience what our users did.At the end of 1997, we released a general purpose shopping search
72
+ engine called Shopfind. It
73
+ was pretty advanced for the time. It had a programmable crawler
74
+ that could crawl most of the different stores online and pick out
75
+ the products.
PaulGrahamEssays/want.txt ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ November 2022Since I was about 9 I've been puzzled by the apparent contradiction
2
+ between being made of matter that behaves in a predictable way, and
3
+ the feeling that I could choose to do whatever I wanted. At the
4
+ time I had a self-interested motive for exploring the question. At
5
+ that age (like most succeeding ages) I was always in trouble with
6
+ the authorities, and it seemed to me that there might possibly be
7
+ some way to get out of trouble by arguing that I wasn't responsible
8
+ for my actions. I gradually lost hope of that, but the puzzle
9
+ remained: How do you reconcile being a machine made of matter with
10
+ the feeling that you're free to choose what you do?
11
+ [1]The best way to explain the answer may be to start with a slightly
12
+ wrong version, and then fix it. The wrong version is: You can do
13
+ what you want, but you can't want what you want. Yes, you can control
14
+ what you do, but you'll do what you want, and you can't control
15
+ that.The reason this is mistaken is that people do sometimes change what
16
+ they want. People who don't want to want something — drug addicts,
17
+ for example — can sometimes make themselves stop wanting it. And
18
+ people who want to want something — who want to like classical
19
+ music, or broccoli — sometimes succeed.So we modify our initial statement: You can do what you want, but
20
+ you can't want to want what you want.That's still not quite true. It's possible to change what you want
21
+ to want. I can imagine someone saying "I decided to stop wanting
22
+ to like classical music." But we're getting closer to the truth.
23
+ It's rare for people to change what they want to want, and the more
24
+ "want to"s we add, the rarer it gets.We can get arbitrarily close to a true statement by adding more "want
25
+ to"s in much the same way we can get arbitrarily close to 1 by adding
26
+ more 9s to a string of 9s following a decimal point. In practice
27
+ three or four "want to"s must surely be enough. It's hard even to
28
+ envision what it would mean to change what you want to want to want
29
+ to want, let alone actually do it.So one way to express the correct answer is to use a regular
30
+ expression. You can do what you want, but there's some statement
31
+ of the form "you can't (want to)* want what you want" that's true.
32
+ Ultimately you get back to a want that you don't control.
33
+ [2]
34
+ Notes[1]
35
+ I didn't know when I was 9 that matter might behave randomly,
36
+ but I don't think it affects the problem much. Randomness destroys
37
+ the ghost in the machine as effectively as determinism.[2]
38
+ If you don't like using an expression, you can make the same
39
+ point using higher-order desires: There is some n such that you
40
+ don't control your nth-order desires.
41
+ Thanks to Trevor Blackwell,
42
+ Jessica Livingston, Robert Morris, and
43
+ Michael Nielsen for reading drafts of this.
PaulGrahamEssays/web20.txt ADDED
@@ -0,0 +1,299 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+
2
+
3
+ Want to start a startup? Get funded by
4
+ Y Combinator.
5
+
6
+
7
+
8
+
9
+ November 2005Does "Web 2.0" mean anything? Till recently I thought it didn't,
10
+ but the truth turns out to be more complicated. Originally, yes,
11
+ it was meaningless. Now it seems to have acquired a meaning. And
12
+ yet those who dislike the term are probably right, because if it
13
+ means what I think it does, we don't need it.I first heard the phrase "Web 2.0" in the name of the Web 2.0
14
+ conference in 2004. At the time it was supposed to mean using "the
15
+ web as a platform," which I took to refer to web-based applications.
16
+ [1]So I was surprised at a conference this summer when Tim O'Reilly
17
+ led a session intended to figure out a definition of "Web 2.0."
18
+ Didn't it already mean using the web as a platform? And if it
19
+ didn't already mean something, why did we need the phrase at all?OriginsTim says the phrase "Web 2.0" first
20
+ arose in "a brainstorming session between
21
+ O'Reilly and Medialive International." What is Medialive International?
22
+ "Producers of technology tradeshows and conferences," according to
23
+ their site. So presumably that's what this brainstorming session
24
+ was about. O'Reilly wanted to organize a conference about the web,
25
+ and they were wondering what to call it.I don't think there was any deliberate plan to suggest there was a
26
+ new version of the web. They just wanted to make the point
27
+ that the web mattered again. It was a kind of semantic deficit
28
+ spending: they knew new things were coming, and the "2.0" referred
29
+ to whatever those might turn out to be.And they were right. New things were coming. But the new version
30
+ number led to some awkwardness in the short term. In the process
31
+ of developing the pitch for the first conference, someone must have
32
+ decided they'd better take a stab at explaining what that "2.0"
33
+ referred to. Whatever it meant, "the web as a platform" was at
34
+ least not too constricting.The story about "Web 2.0" meaning the web as a platform didn't live
35
+ much past the first conference. By the second conference, what
36
+ "Web 2.0" seemed to mean was something about democracy. At least,
37
+ it did when people wrote about it online. The conference itself
38
+ didn't seem very grassroots. It cost $2800, so the only people who
39
+ could afford to go were VCs and people from big companies.And yet, oddly enough, Ryan Singel's article
40
+ about the conference in Wired News spoke of "throngs of
41
+ geeks." When a friend of mine asked Ryan about this, it was news
42
+ to him. He said he'd originally written something like "throngs
43
+ of VCs and biz dev guys" but had later shortened it just to "throngs,"
44
+ and that this must have in turn been expanded by the editors into
45
+ "throngs of geeks." After all, a Web 2.0 conference would presumably
46
+ be full of geeks, right?Well, no. There were about 7. Even Tim O'Reilly was wearing a
47
+ suit, a sight so alien I couldn't parse it at first. I saw
48
+ him walk by and said to one of the O'Reilly people "that guy looks
49
+ just like Tim.""Oh, that's Tim. He bought a suit."
50
+ I ran after him, and sure enough, it was. He explained that he'd
51
+ just bought it in Thailand.The 2005 Web 2.0 conference reminded me of Internet trade shows
52
+ during the Bubble, full of prowling VCs looking for the next hot
53
+ startup. There was that same odd atmosphere created by a large
54
+ number of people determined not to miss out. Miss out on what?
55
+ They didn't know. Whatever was going to happen—whatever Web 2.0
56
+ turned out to be.I wouldn't quite call it "Bubble 2.0" just because VCs are eager
57
+ to invest again. The Internet is a genuinely big deal. The bust
58
+ was as much an overreaction as
59
+ the boom. It's to be expected that once we started to pull out of
60
+ the bust, there would be a lot of growth in this area, just as there
61
+ was in the industries that spiked the sharpest before the Depression.The reason this won't turn into a second Bubble is that the IPO
62
+ market is gone. Venture investors
63
+ are driven by exit strategies. The reason they were funding all
64
+ those laughable startups during the late 90s was that they hoped
65
+ to sell them to gullible retail investors; they hoped to be laughing
66
+ all the way to the bank. Now that route is closed. Now the default
67
+ exit strategy is to get bought, and acquirers are less prone to
68
+ irrational exuberance than IPO investors. The closest you'll get
69
+ to Bubble valuations is Rupert Murdoch paying $580 million for
70
+ Myspace. That's only off by a factor of 10 or so.1. AjaxDoes "Web 2.0" mean anything more than the name of a conference
71
+ yet? I don't like to admit it, but it's starting to. When people
72
+ say "Web 2.0" now, I have some idea what they mean. And the fact
73
+ that I both despise the phrase and understand it is the surest proof
74
+ that it has started to mean something.One ingredient of its meaning is certainly Ajax, which I can still
75
+ only just bear to use without scare quotes. Basically, what "Ajax"
76
+ means is "Javascript now works." And that in turn means that
77
+ web-based applications can now be made to work much more like desktop
78
+ ones.As you read this, a whole new generation
79
+ of software is being written to take advantage of Ajax. There
80
+ hasn't been such a wave of new applications since microcomputers
81
+ first appeared. Even Microsoft sees it, but it's too late for them
82
+ to do anything more than leak "internal"
83
+ documents designed to give the impression they're on top of this
84
+ new trend.In fact the new generation of software is being written way too
85
+ fast for Microsoft even to channel it, let alone write their own
86
+ in house. Their only hope now is to buy all the best Ajax startups
87
+ before Google does. And even that's going to be hard, because
88
+ Google has as big a head start in buying microstartups as it did
89
+ in search a few years ago. After all, Google Maps, the canonical
90
+ Ajax application, was the result of a startup they bought.So ironically the original description of the Web 2.0 conference
91
+ turned out to be partially right: web-based applications are a big
92
+ component of Web 2.0. But I'm convinced they got this right by
93
+ accident. The Ajax boom didn't start till early 2005, when Google
94
+ Maps appeared and the term "Ajax" was coined.2. DemocracyThe second big element of Web 2.0 is democracy. We now have several
95
+ examples to prove that amateurs can
96
+ surpass professionals, when they have the right kind of system to
97
+ channel their efforts. Wikipedia
98
+ may be the most famous. Experts have given Wikipedia middling
99
+ reviews, but they miss the critical point: it's good enough. And
100
+ it's free, which means people actually read it. On the web, articles
101
+ you have to pay for might as well not exist. Even if you were
102
+ willing to pay to read them yourself, you can't link to them.
103
+ They're not part of the conversation.Another place democracy seems to win is in deciding what counts as
104
+ news. I never look at any news site now except Reddit.
105
+ [2]
106
+ I know if something major
107
+ happens, or someone writes a particularly interesting article, it
108
+ will show up there. Why bother checking the front page of any
109
+ specific paper or magazine? Reddit's like an RSS feed for the whole
110
+ web, with a filter for quality. Similar sites include Digg, a technology news site that's
111
+ rapidly approaching Slashdot in popularity, and del.icio.us, the collaborative
112
+ bookmarking network that set off the "tagging" movement. And whereas
113
+ Wikipedia's main appeal is that it's good enough and free, these
114
+ sites suggest that voters do a significantly better job than human
115
+ editors.The most dramatic example of Web 2.0 democracy is not in the selection
116
+ of ideas, but their production.
117
+ I've noticed for a while that the stuff I read on individual people's
118
+ sites is as good as or better than the stuff I read in newspapers
119
+ and magazines. And now I have independent evidence: the top links
120
+ on Reddit are generally links to individual people's sites rather
121
+ than to magazine articles or news stories.My experience of writing
122
+ for magazines suggests an explanation. Editors. They control the
123
+ topics you can write about, and they can generally rewrite whatever
124
+ you produce. The result is to damp extremes. Editing yields 95th
125
+ percentile writing—95% of articles are improved by it, but 5% are
126
+ dragged down. 5% of the time you get "throngs of geeks."On the web, people can publish whatever they want. Nearly all of
127
+ it falls short of the editor-damped writing in print publications.
128
+ But the pool of writers is very, very large. If it's large enough,
129
+ the lack of damping means the best writing online should surpass
130
+ the best in print.
131
+ [3]
132
+ And now that the web has evolved mechanisms
133
+ for selecting good stuff, the web wins net. Selection beats damping,
134
+ for the same reason market economies beat centrally planned ones.Even the startups are different this time around. They are to the
135
+ startups of the Bubble what bloggers are to the print media. During
136
+ the Bubble, a startup meant a company headed by an MBA that was
137
+ blowing through several million dollars of VC money to "get big
138
+ fast" in the most literal sense. Now it means a smaller, younger, more technical group that just
139
+ decided to make something great. They'll decide later if they want
140
+ to raise VC-scale funding, and if they take it, they'll take it on
141
+ their terms.3. Don't Maltreat UsersI think everyone would agree that democracy and Ajax are elements
142
+ of "Web 2.0." I also see a third: not to maltreat users. During
143
+ the Bubble a lot of popular sites were quite high-handed with users.
144
+ And not just in obvious ways, like making them register, or subjecting
145
+ them to annoying ads. The very design of the average site in the
146
+ late 90s was an abuse. Many of the most popular sites were loaded
147
+ with obtrusive branding that made them slow to load and sent the
148
+ user the message: this is our site, not yours. (There's a physical
149
+ analog in the Intel and Microsoft stickers that come on some
150
+ laptops.)I think the root of the problem was that sites felt they were giving
151
+ something away for free, and till recently a company giving anything
152
+ away for free could be pretty high-handed about it. Sometimes it
153
+ reached the point of economic sadism: site owners assumed that the
154
+ more pain they caused the user, the more benefit it must be to them.
155
+ The most dramatic remnant of this model may be at salon.com, where
156
+ you can read the beginning of a story, but to get the rest you have
157
+ sit through a movie.At Y Combinator we advise all the startups we fund never to lord
158
+ it over users. Never make users register, unless you need to in
159
+ order to store something for them. If you do make users register,
160
+ never make them wait for a confirmation link in an email; in fact,
161
+ don't even ask for their email address unless you need it for some
162
+ reason. Don't ask them any unnecessary questions. Never send them
163
+ email unless they explicitly ask for it. Never frame pages you
164
+ link to, or open them in new windows. If you have a free version
165
+ and a pay version, don't make the free version too restricted. And
166
+ if you find yourself asking "should we allow users to do x?" just
167
+ answer "yes" whenever you're unsure. Err on the side of generosity.In How to Start a Startup I advised startups
168
+ never to let anyone fly under them, meaning never to let any other
169
+ company offer a cheaper, easier solution. Another way to fly low
170
+ is to give users more power. Let users do what they want. If you
171
+ don't and a competitor does, you're in trouble.iTunes is Web 2.0ish in this sense. Finally you can buy individual
172
+ songs instead of having to buy whole albums. The recording industry
173
+ hated the idea and resisted it as long as possible. But it was
174
+ obvious what users wanted, so Apple flew under the labels.
175
+ [4]
176
+ Though really it might be better to describe iTunes as Web 1.5.
177
+ Web 2.0 applied to music would probably mean individual bands giving
178
+ away DRMless songs for free.The ultimate way to be nice to users is to give them something for
179
+ free that competitors charge for. During the 90s a lot of people
180
+ probably thought we'd have some working system for micropayments
181
+ by now. In fact things have gone in the other direction. The most
182
+ successful sites are the ones that figure out new ways to give stuff
183
+ away for free. Craigslist has largely destroyed the classified ad
184
+ sites of the 90s, and OkCupid looks likely to do the same to the
185
+ previous generation of dating sites.Serving web pages is very, very cheap. If you can make even a
186
+ fraction of a cent per page view, you can make a profit. And
187
+ technology for targeting ads continues to improve. I wouldn't be
188
+ surprised if ten years from now eBay had been supplanted by an
189
+ ad-supported freeBay (or, more likely, gBay).Odd as it might sound, we tell startups that they should try to
190
+ make as little money as possible. If you can figure out a way to
191
+ turn a billion dollar industry into a fifty million dollar industry,
192
+ so much the better, if all fifty million go to you. Though indeed,
193
+ making things cheaper often turns out to generate more money in the
194
+ end, just as automating things often turns out to generate more
195
+ jobs.The ultimate target is Microsoft. What a bang that balloon is going
196
+ to make when someone pops it by offering a free web-based alternative
197
+ to MS Office.
198
+ [5]
199
+ Who will? Google? They seem to be taking their
200
+ time. I suspect the pin will be wielded by a couple of 20 year old
201
+ hackers who are too naive to be intimidated by the idea. (How hard
202
+ can it be?)The Common ThreadAjax, democracy, and not dissing users. What do they all have in
203
+ common? I didn't realize they had anything in common till recently,
204
+ which is one of the reasons I disliked the term "Web 2.0" so much.
205
+ It seemed that it was being used as a label for whatever happened
206
+ to be new—that it didn't predict anything.But there is a common thread. Web 2.0 means using the web the way
207
+ it's meant to be used. The "trends" we're seeing now are simply
208
+ the inherent nature of the web emerging from under the broken models
209
+ that got imposed on it during the Bubble.I realized this when I read an interview with
210
+ Joe Kraus, the co-founder of Excite.
211
+ [6]
212
+
213
+ Excite really never got the business model right at all. We fell
214
+ into the classic problem of how when a new medium comes out it
215
+ adopts the practices, the content, the business models of the old
216
+ medium—which fails, and then the more appropriate models get
217
+ figured out.
218
+
219
+ It may have seemed as if not much was happening during the years
220
+ after the Bubble burst. But in retrospect, something was happening:
221
+ the web was finding its natural angle of repose. The democracy
222
+ component, for example—that's not an innovation, in the sense of
223
+ something someone made happen. That's what the web naturally tends
224
+ to produce.Ditto for the idea of delivering desktop-like applications over the
225
+ web. That idea is almost as old as the web. But the first time
226
+ around it was co-opted by Sun, and we got Java applets. Java has
227
+ since been remade into a generic replacement for C++, but in 1996
228
+ the story about Java was that it represented a new model of software.
229
+ Instead of desktop applications, you'd run Java "applets" delivered
230
+ from a server.This plan collapsed under its own weight. Microsoft helped kill it,
231
+ but it would have died anyway. There was no uptake among hackers.
232
+ When you find PR firms promoting
233
+ something as the next development platform, you can be sure it's
234
+ not. If it were, you wouldn't need PR firms to tell you, because
235
+ hackers would already be writing stuff on top of it, the way sites
236
+ like Busmonster used Google Maps as a
237
+ platform before Google even meant it to be one.The proof that Ajax is the next hot platform is that thousands of
238
+ hackers have spontaneously started building things on top
239
+ of it. Mikey likes it.There's another thing all three components of Web 2.0 have in common.
240
+ Here's a clue. Suppose you approached investors with the following
241
+ idea for a Web 2.0 startup:
242
+
243
+ Sites like del.icio.us and flickr allow users to "tag" content
244
+ with descriptive tokens. But there is also huge source of
245
+ implicit tags that they ignore: the text within web links.
246
+ Moreover, these links represent a social network connecting the
247
+ individuals and organizations who created the pages, and by using
248
+ graph theory we can compute from this network an estimate of the
249
+ reputation of each member. We plan to mine the web for these
250
+ implicit tags, and use them together with the reputation hierarchy
251
+ they embody to enhance web searches.
252
+
253
+ How long do you think it would take them on average to realize that
254
+ it was a description of Google?Google was a pioneer in all three components of Web 2.0: their core
255
+ business sounds crushingly hip when described in Web 2.0 terms,
256
+ "Don't maltreat users" is a subset of "Don't be evil," and of course
257
+ Google set off the whole Ajax boom with Google Maps.Web 2.0 means using the web as it was meant to be used, and Google
258
+ does. That's their secret. They're sailing with the wind, instead of sitting
259
+ becalmed praying for a business model, like the print media, or
260
+ trying to tack upwind by suing their customers, like Microsoft and
261
+ the record labels.
262
+ [7]Google doesn't try to force things to happen their way. They try
263
+ to figure out what's going to happen, and arrange to be standing
264
+ there when it does. That's the way to approach technology—and
265
+ as business includes an ever larger technological component, the
266
+ right way to do business.The fact that Google is a "Web 2.0" company shows that, while
267
+ meaningful, the term is also rather bogus. It's like the word
268
+ "allopathic." It just means doing things right, and it's a bad
269
+ sign when you have a special word for that.
270
+ Notes[1]
271
+ From the conference
272
+ site, June 2004: "While the first wave of the Web was closely
273
+ tied to the browser, the second wave extends applications across
274
+ the web and enables a new generation of services and business
275
+ opportunities." To the extent this means anything, it seems to be
276
+ about
277
+ web-based applications.[2]
278
+ Disclosure: Reddit was funded by
279
+ Y Combinator. But although
280
+ I started using it out of loyalty to the home team, I've become a
281
+ genuine addict. While we're at it, I'm also an investor in
282
+ !MSFT, having sold all my shares earlier this year.[3]
283
+ I'm not against editing. I spend more time editing than
284
+ writing, and I have a group of picky friends who proofread almost
285
+ everything I write. What I dislike is editing done after the fact
286
+ by someone else.[4]
287
+ Obvious is an understatement. Users had been climbing in through
288
+ the window for years before Apple finally moved the door.[5]
289
+ Hint: the way to create a web-based alternative to Office may
290
+ not be to write every component yourself, but to establish a protocol
291
+ for web-based apps to share a virtual home directory spread across
292
+ multiple servers. Or it may be to write it all yourself.[6]
293
+ In Jessica Livingston's
294
+ Founders at
295
+ Work.[7]
296
+ Microsoft didn't sue their customers directly, but they seem
297
+ to have done all they could to help SCO sue them.Thanks to Trevor Blackwell, Sarah Harlin, Jessica Livingston, Peter
298
+ Norvig, Aaron Swartz, and Jeff Weiner for reading drafts of this, and to the
299
+ guys at O'Reilly and Adaptive Path for answering my questions.
PaulGrahamEssays/weird.txt ADDED
@@ -0,0 +1,30 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ August 2021When people say that in their experience all programming languages
2
+ are basically equivalent, they're making a statement not about
3
+ languages but about the kind of programming they've done.99.5% of programming consists of gluing together calls to library
4
+ functions. All popular languages are equally good at this. So one
5
+ can easily spend one's whole career operating in the intersection
6
+ of popular programming languages.But the other .5% of programming is disproportionately interesting.
7
+ If you want to learn what it consists of, the weirdness of weird
8
+ languages is a good clue to follow.Weird languages aren't weird by accident. Not the good ones, at
9
+ least. The weirdness of the good ones usually implies the existence
10
+ of some form of programming that's not just the usual gluing together
11
+ of library calls.A concrete example: Lisp macros. Lisp macros seem weird even to
12
+ many Lisp programmers. They're not only not in the intersection of
13
+ popular languages, but by their nature would be hard to implement
14
+ properly in a language without turning it into a dialect of
15
+ Lisp. And macros are definitely evidence of techniques that go
16
+ beyond glue programming. For example, solving problems by first
17
+ writing a language for problems of that type, and then writing
18
+ your specific application in it. Nor is this all you can do with
19
+ macros; it's just one region in a space of program-manipulating
20
+ techniques that even now is far from fully explored.So if you want to expand your concept of what programming can be,
21
+ one way to do it is by learning weird languages. Pick a language
22
+ that most programmers consider weird but whose median user is smart,
23
+ and then focus on the differences between this language and the
24
+ intersection of popular languages. What can you say in this language
25
+ that would be impossibly inconvenient to say in others? In the
26
+ process of learning how to say things you couldn't previously say,
27
+ you'll probably be learning how to think things you couldn't
28
+ previously think.
29
+ Thanks to Trevor Blackwell, Patrick Collison, Daniel Gackle, Amjad
30
+ Masad, and Robert Morris for reading drafts of this.