mrmanna
1
follower
ยท
1 following
None yet
posted
an
update
4 days ago
https://www.youtube.com/watch?v=voF6x1aV_z4
Deterministic AI Design with Capability OS: Save from the AI Bubble - Live demo of Omni Agent
Everyone is piloting agents, copilots and AI platforms. Very few are asking a harder question: which of these systems will still be trusted when the AI bubble bursts?
In this session I'll share my 1.5-year journey from raw LLM experiments and messy AI-generated code to a deterministic, decision-first architecture for agentic systems.
I will demo Omni Agentโ-โa Capability OS for Enterprise AIโ-โand then walk through how it is designed and built using Decision-Driven Software Engineering (DDSE) and the Agentic Contract Model (ACM) so that execution stays bounded, auditable and aligned to your decisions, not the model's mood.
What you'll see
ย โข End-to-end walkthrough of Omni Agent: goals, plans, tasks, ledgers, telemetry
ย โข A real scenario on a codebase (e.g. an Angular chat app)โ-โfrom "investigate this" to concrete actions and tracked outcomes
ย โข How decisions, capabilities, contracts and context are modeled in DDSE & ACM
ย โข Architecture view of Omni Agent as a "Capability OS": planner, executor, context layers and extensibility
ย โข Honest trade-offs: what is still weak, what's missing, and where this approach may or may not fit your environment
Who this is for
ย โข Engineering leaders and architects evaluating agentic platforms
ย โข Developers who want more than "prompt + tools" and care about system design
ย โข Anyone worried about the AI bubble and looking for deterministic, governable AI systems
Format
ย โข ~40 minutes of platform demo + design walkthrough (via YouTube Premiere)
ย โข I'll be present live in the chat
ย โข Follow-up Q&A thread on LinkedIn for deeper questions
View all activity
view post
๐๐๐ฆ๐ ๐๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป ๐ฝ๐๐ฏ๐น๐ถ๐๐ต๐ฒ๐ ๐๐๐ โ ๐ฎ๐ป ๐ข๐ฅ๐ ๐ณ๐ผ๐ฟ ๐๐ผ๐ป๐๐ฒ๐
๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐ถ๐ป ๐๐๐ ๐ฆ๐๐๐๐ฒ๐บ๐ Just as Hibernate abstracts databases for transactions, CEF abstracts knowledge stores for Context Engineering. Build, test, and benchmark intelligent context models in minutes, without the complexity of enterprise graph infrastructure. https://github.com/ddse-foundation/cef https://ddse-foundation.github.io/cef/
See translation
๐๐๐ฆ๐ ๐๐ผ๐๐ป๐ฑ๐ฎ๐๐ถ๐ผ๐ป ๐ฝ๐๐ฏ๐น๐ถ๐๐ต๐ฒ๐ ๐๐๐ โ ๐ฎ๐ป ๐ข๐ฅ๐ ๐ณ๐ผ๐ฟ ๐๐ผ๐ป๐๐ฒ๐
๐ ๐๐ป๐ด๐ถ๐ป๐ฒ๐ฒ๐ฟ๐ถ๐ป๐ด ๐ถ๐ป ๐๐๐ ๐ฆ๐๐๐๐ฒ๐บ๐
