The distinction isn't whether code comes from AI or humans, but how we integrate and take responsibility for it. If you're encapsulating AI-generated code behind a well-defined interface and treating it like any third party dependency, then testing that interface for correctness is a reasonable approach.
The real complexity arises when you have AI help write code you'll commit under your name. In this scenario, code review absolutely matters because you're assuming direct responsibility.
I'm also questioning whether AI truly increases productivity or just reduces cognitive load. Sometimes "easier" feels faster but doesn't translate to actual time savings. And when we do move quicker with AI, we should ask if it's because we've unconsciously lowered our quality bar. Are we accepting verbose, oddly structured code from AI that we'd reject from colleagues? Are we giving AI-generated code a pass on the same rigorous review process we expect for human written code? If so, would we see the same velocity increases from relaxing our code review process amongst ourselves (between human reviewers)?