Engineer shares 8 hard blockers for reviewing AI-generated pull requests

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A software engineer writing for DEV Community has outlined a strict eight-blocker rubric for evaluating AI-generated pull requests, arguing that fluent code and passing linters mask deeper risks. The framework focuses on issues that can cause outages, data corruption, access leaks, or irreversible changes — not style or naming preferences. Each blocker requires a cited file path and line number, and any PR carrying an unresolved blocker cannot be merged without written acknowledgment of the risk. Key examples include missing feature flags on irreversible migrations and silent breaking changes to API contracts, such as quietly converting an integer field to a formatted string. The author emphasizes that a clean run should produce silence, not suggestions, and that review tools which flag non-issues get ignored within days.

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