Same-Model Review Blindness

Greptile's Rodrigo Caridad on two 500-PR labelled datasets (~1,500 verified high-severity bugs): each frontier model catches fewer bugs in code authored by its own model family than in the other family's code — Opus 4.7 53.7% same-model vs 60.0% cross-model, GPT 5.5 50.5% vs 62.0%. The crossover is a pure interaction (both reviewers average ~56% overall and the two datasets differ by 2.6pp), but the post's offered mechanism — that a model misses the bug categories it produces most — reproduces only ~7% of its own headline when the category table is reweighted by the bug mix, so the blindness operates WITHIN category, not through composition. Vendor-built ground truth with an unspecified labelling procedure, one arm's prompt tuned against the outcome metric, no released artifact — filed case-study, not empirical