Self-improving review systems adapt from developer feedback

Run a reviewer on merged PRs, cross-reference developer responses, classify each comment, and have the reviewer edit its own prompt on a schedule. The prompt evolves on data. Every change is traceable to a pattern: developers ignored this type of comment 8 times in 14 days, so suppress it.

The system works because it closes the feedback loop that humans usually skip. Most teams tweak their reviewer’s prompt manually every few weeks based on vague memory of what was annoying. The automated version runs every two weeks, classifies every comment against developer actions, and makes targeted edits backed by data. The result is a review prompt that evolves with the team’s codebase and conventions, rather than staying static while the code around it changes.