I build AI Dev OS — an open framework that turns tacit developer knowledge into explicit, enforceable rules for AI coding assistants.
The problem: AI generates code that looks correct but violates your team's conventions, security practices, and architectural patterns. Loading more guidelines into context actually degrades output quality.
The solution: A layered rule architecture (Lifespan Layers) with a two-tier context strategy — 3-5 static rules during generation + comprehensive check & fix after generation. Benchmark: 96.9/100.
npx ai-dev-os init75% of rules survive tool migrations. Switch between Claude Code, Cursor, and Kiro freely.

