The post frames project-level AGENTS.md/CLAUDE.md files as neural network weights, where agent sessions are forward passes, session transcript corrections are loss signals, and file edits are backward passes.

A fixed token budget caps the file, and updates require batching multiple sessions before making small, targeted edits rather than appending rules after single incidents. The author built a tool called backpass to automate reading session transcripts and applying these iterative updates.