Episode Details

This story was originally published on HackerNoon at: https://hackernoon.com/ai-code-review-in-regulated-environments-what-a-human-expert-still-has-to-own.
Why a name on a pull request isn't proof anyone actually reviewed it, and what AI-generated code is exposing about code review at scale.
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A landmark study found 40% of AI-generated code contained vulnerabilities, yet nearly every one of those PRs still carries a human "reviewed" stamp. Defect detection drops sharply past ~400 lines per review, exactly the size AI-generated PRs tend to land at. A named reviewer isn't proof of judgment. Three categories of decisions (regulatory intent, compliance-sensitive architecture, escalation calls) need to go to a specific accountable person, not general review.