 AI agents write code, and you're still reviewing manually? GitHub says — get used to it, their PRs are everywhere. GitHub released a guide on reviewing pull requests from AI agents. Spoiler: the old approach doesn't work. What changed? Previously, a PR from a human — clear structure, author's logic, you could ask "why did you do this." Agent PR — a black box. An agent can generate 500 lines that pass tests but break the architecture. How to review PRs from agents — in short: 1. Look at the diff, not the description — agents write beautiful commit messages, but the real value is in the changes. 2. Look for "dead code" — agents love generating functions that are never called. 3. Check dependencies — an agent might add 3 libraries for a single utility. 4. Look at tests — if tests are green but the code looks strange, it's not a bug, it's technical debt. 5. Pay attention to repeating patterns — agents tend to copy-paste with variations. Why is this important for developers? GitHub Copilot Coding Agents are already in production. Agent-driven development is not hype, it's reality. Those who learn to review AI code now will be a step ahead in a year. What about ASI Biont? We use AI agents not only for code but also for analytics, partner search, email communications. And yes, we review their work too. Every agent goes through checks — like code in CI/CD. Try it yourself: https://asibiont.com/ 1500 tokens at the start for new users — launch your own AI agent and see how it performs.