AI Code Reviews Are Backwards (Do This Instead)

A few weeks ago, I wrote about The Review Bottleneck — how AI-generated code comes with so much confident explanation that we’ve stopped actually reviewing it.

We’re not doing more engineering. We’re doing more trusting.

The response was overwhelming. Developers everywhere said: “I thought I was the only one.”

So I made a video breaking down what’s actually happening — and what I’m trying instead.

The Core Problem

AI code reviews aren’t making us better reviewers. They’re making us worse.

Not because the AI is bad — but because the volume of explanation has become impossible to process.

When you’re staring at:

  • 300 lines of code
  • 1,200 words of AI explanation
  • 800 words of AI review feedback
  • 15 inline comments about trade-offs

You’re not carefully evaluating. You’re skimming and trusting.

What I’m Doing Instead

The video walks through my current approach:

The 30-minute rule — If I can’t understand a PR in 30 minutes of focused review, it’s too big. Break it down.

No AI reviewer without human review — AI review is a supplement, not a replacement.

The explain-it test — If I can’t explain the core logic to someone else, I don’t approve it.

Does this slow me down? Yes.

Does it help? I think so.

The Uncomfortable Truth

Research shows AI-generated code creates 1.7x more issues than human-written code. Yet:

  • 46% of all code is now AI-generated
  • 84% of developers use AI coding tools regularly
  • Only 30% of AI-suggested code actually gets accepted

We’re generating more code than ever. But we’re not reviewing it properly.

The quality gate we automated away isn’t coming back.

We need to figure out what replaces it.

Watch the Full Breakdown

The video goes deeper into:

  • Why AI code review tools make the problem worse, not better
  • The “automation bias” trap we’re all falling into
  • Practical strategies for reviewing AI code honestly
  • What comes next when the review bottleneck becomes permanent

Check it out and let me know what you think. Are you actually reviewing AI code? Or just hoping the explanation is right?


Related: Read the full analysis in The Review Bottleneck: Why AI Explanations Are Making Us Trust Less, Not More

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