Developers have been griping that they readily create detailed CLAUDE.md and PROJECT.md files for the AI model Claude, yet they refuse to write comparable docs for teammates. To bridge the gap, the author began treating Claude as a handoff agent, asking each instance to record plans, progress, and open items. When one Claude shuts down, the next reads the file and continues.

At project close he now commands Claude to draft a concise, high‑level summary of the problem solved and code changes, then reviews and signs off before committing. The AI’s output usually matches a human’s quality, requiring only seconds to generate and minimal editing. A hiccup occurred when Claude copied an approval footer from a prior report, prompting a quick rule tweak.

His recommendation is simple: let Claude generate notes, then check the files into the repository like any other artifact. Storing AI‑produced documentation preserves institutional knowledge and spares future engineers from hunting down scattered comments. The practice costs almost nothing and can instantly improve project traceability, making the codebase more maintainable for the whole team in the long run.