Too Many AI Code Review Comments Can Bury the Ones That Actually Matter

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A software developer observed that an AI code reviewer generated around a dozen comments on a routine 200-line pull request, most of which were technically valid but low-priority. The sheer volume caused the developer reviewing the PR to skim through comments and nearly miss the one genuinely critical finding buried among trivial suggestions. The author argues that AI review tools are designed to maximise issue detection, but the real challenge in code review is signal-to-noise ratio — identifying what truly deserves a developer's attention. This experience prompted the author to begin building Codzee, a tool aimed at prioritising meaningful feedback over exhaustive flagging. The post closes with open questions to the developer community about trust, comment thresholds, and how to balance thoroughness with usability in automated code review.

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