#ai
ai shows up across 3 section(s) and 9 page(s) in this workspace. Use this page as a topic map, not just an archive.
Start here
If you are new to this topic, begin with the strongest entry points first, then move into related notes and supporting material.
Where it appears
- Systems 5 page(s)
- Sentences 1 page(s)
- Shelf 3 page(s)
AI Architecture Explained: How Modern LLM Applications Work
A practical map of the layers that make modern LLM applications reliable: model access, retrieval, orchestration, interfaces, and governance.
I-7 Cognitive Loop: A new standard for Human-AI interaction
A governance-first interaction model that extends Norman's stages for AI-assisted work.
Natural Language Is the New API
Why natural language is an interface for machine behavior, not just a conversation.
What an AI Model Actually Is
Kill the 'AI brain' myth. A model is a statistical engine that predicts the next likely token, not a mind that understands intent.
Why Most AI Projects Fail After the Demo Stage
Why AI projects often stall after promising demos: weak integration, missing governance, low observability, and unclear adoption design.
Confidence Is Cheap. Understanding Is Costly.
Notes: I-7 Cognitive Loop (summary)
A governance-first loop for AI-assisted work, inspired by Norman.
Tools: AI CLIs
Codex, Claude, Gemini, and Azure via terminal for power use.
AI Strategy 2026 deck
A strategy deck on choosing architecture, operating model, and AI roadmap for 2026.