One team's path to trusting AI generated code

Our team merges 4x more pull requests than we did a year ago. Almost all of that code is AI-generated, human assisted. We tried scaling code review to match — more reviewers, AI review tools, stricter checklists — and none of it worked. What worked was stopping the fight over diffs entirely and building a verification layer around intent.

This is the story of how one engineering team replaced the PR review bottleneck with an intent-driven verification workflow: capturing what a change should do before a single line is generated, encoding team standards as reusable invariants, and letting deterministic checks — not tired reviewers — produce the evidence that a change is safe to ship.

I'll walk through the specific practices that made the difference — especially how we turned years of recurring review comments into machine-enforceable invariants — and share the results, the failures, and what we'd do differently.