
Codex Code Review Plugin: How to Review Pull Requests in Codex
Codex's Code Review plugin opens GitHub PRs in the desktop and web app, runs a private Codex review, and lets you choose which findings to post.
16 articles

Codex cloud now reviews GitLab merge requests and runs @codex tasks in beta on all ChatGPT plans. Setup for GitLab.com and Self-Managed 19.0+.

Codex's Code Review plugin opens GitHub PRs in the desktop and web app, runs a private Codex review, and lets you choose which findings to post.

Railway preview environments for agent pull requests: an isolated copy of your whole stack for every PR, so you verify agent changes by running them.

Build an AI pull request reviewer on Railway: a webhook service runs OpenCode headless on every PR diff and posts findings as a review, never touching the code.

Diffs vs whole files for code editing agents: a paper finds full-file generation beating diff edits on Flutter/Dart tasks. The lesson: route by task locality.

Linear's 2026 data shows coding agents tripled weekly PRs for connected teams, yet total product-development time rose. What it means for engineering leads.

Vibe maintenance for AI-generated pull requests: Steve Yegge's workflow to automate triage, let agents repair good ideas, and keep maintainer taste in charge.

GitHub stacked pull requests are in public preview: how stacks split one large change into small, reviewable PRs with one-click merge and a gh-stack skill.

LLM agents resolve real Java merge conflicts more often than structured merge tools in a calibrated ConflictBench study. Their edge is coverage: tools abstain.

PAIChecker finds 13.6% of SWE-bench Verified instances pair a PR with an issue it does not resolve, penalizing agents that solve the stated problem.

Best AI code review tools in 2026: CodeRabbit, DeepSource, Greptile, SonarQube and Copilot code review compared on pricing, platform support and security.

Fable 5 posts an 80.3% SWE-Bench Pro score and costs 2x Opus 4.8 - here is the task-profile scoring guide that tells you when the premium pays off.

The rsync Claude debate shows why teams need reproducible defect forensics before AI attribution becomes a public blame machine.
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