Something's been bugging me about how most teams are handling AI-generated UI code right now.
The pattern goes: Cursor, Copilot, v0, or Claude Code writes the component. It looks right. It compiles. It probably even matches the Figma file at a glance. Then six sprints later someone notices the button padding doesn't match the design tokens anymore, or the loading state was never implemented, or there's a hardcoded hex value sitting in a component that's supposed to pull from the theme. Nobody did that on purpose. It just... drifted.
The numbers back this up if you don't already feel it in your own codebase. Faros AI's 2026 engineering report found code churn is up 861% against pre-AI baselines, and 31.3% more PRs are now merging without any human review at all. Humans didn't get worse at reviewing. There's just more to review than any team can keep up with, and a lot of what's slipping through isn't broken code — it's code that's quietly disagreeing with the design system it's supposed to be implementing.
So teams reach for the obvious fix: point another AI model at the diff and ask it to catch what the first one missed.
I think that's the wrong architecture, and it's worth explaining why.
