AI-assisted commits show a fix-rate gap in one small repo study, but the control group is flawed

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A developer checked whether their own side projects mirrored a Harvard working paper that found coding agents raised pull request volume while slowing review. Comparing commits with and without an AI co-author trailer, they initially saw AI commits starting with fix or revert at more than double the rate. Closer inspection showed the no-trailer group was almost entirely one scaffolding day with unknown authorship, and that AI commits used feat/fix naming and touched more files. When the analysis counted per file instead of per commit, the gap disappeared, with roughly 46% versus 47% of touched files being re-edited within 72 hours. The author concludes that two repos cannot show whether AI-assisted work gets fixed more or less, and that the original result came from naming habits, a one-day control group and commit size.

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