Pitting two AI code reviewers against each other exposes a critical blindspot
adrianscottcom · x · 2026-10-03
The author shares a workflow of making AI models critique each other's code reviews. The second reviewer's verdict: the review was exceptionally strong overall but contained one critical blindspot (Finding 5 would break at runtime if naively implemented) and a couple of subtle inaccuracies (Findings 1, 3, and a Nit), while the follow-up advice about hashing rather than dropping a handle was "top-tier." Cross-reviewing is a practical way to surface hidden flaws in single-model reviews.
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