Measure Your Team's Code Review Limits Before AI Pull Requests Overwhelm Them

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Researcher Margaret-Anne Storey recently introduced the concept of 'cognitive debt' — the gradual erosion of shared understanding about how a system works — during a DORA community session. A software developer writing on DEV Community argues this debt is quietly accumulating in teams that review AI-generated pull requests at scale, without realising their review process has become ineffective. The author warns that standard delivery metrics like merge rate and time-to-approve can appear healthy even as review quality collapses, masking real risk behind green dashboards. Drawing a parallel to mutation testing in software quality assurance, they propose seeding review queues with known-defective 'canary' pull requests to measure how reliably reviewers catch real problems. They recommend starting with one canary per twenty pull requests, tracked over four-week windows, to establish a statistically meaningful detection rate before cognitive debt causes a serious incident.

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