When we audited our AI coding-agent instructions (CLAUDE.md files, skills, agent definitions) against our actual monorepo, we found docs that were confidently wrong: styling guides producing CSS that never matched the build, test templates that crashed on render, "best practices" used by 1 of 50 real files. Every wrong doc cost a multi-thousand-token debug loop each time an agent followed it. This talk is the playbook that came out of fixing it: how to distribute knowledge across instruction surfaces based on their loading semantics, and how to test docs the way you test code.
This talk has been presented at AI Coding Summit Berlin, check out the latest edition of this Tech Conference.























