Agent pull requests are everywhere. Here’s how to review them.

<h1> The Agent That Created 107 PRs (And Why That Was the Problem) </h1> <p>One of our leaders has a way of framing AI initiatives that I find genuinely useful. Three buckets:

<p>Instead of one huge, un-reviewable pull request, teach coding agents to decompose work into a clean, ordered stack with GitHub stacked pull requests.</p> <p>The post <a

<!-- SC_OFF --><div class="md"><pre><code>Built a system where Claude Code writes the code and Codex CLI reviews it independently — the reviewer never sees the builder's

<p><em>8 dimensions. 38 checks. 5 seconds. 0% industry pass rate.</em></p> <h2> The Problem </h2> <p>DAST exists for web apps. DAST exists for APIs. DAST does not exist for AI

<p>See how four GitHub Agent Apps can help you scope, secure, roll out, and ship a feature across the SDLC–all without leaving GitHub. </p> <p>The post <a

<p>On March 31, 2026, Anthropic accidentally shipped the entire source code of Claude Code — its flagship AI coding agent — inside a routine npm update. No hack. No reverse

<h2> What is AI code review? </h2> <p><strong>AI code review is the automated analysis of code changes using artificial intelligence to find bugs, security vulnerabilities,

<h1> How I Built an AI-Powered Code Review Bot That Saves 10 Hours/Week—Here's the Cheapest Way to Deploy It </h1> <p>My team was drowning. Every pull request meant 20-30 minutes