Teams are using different model families for code review to catch blind spots
desilvakai · reddit · 2026-07-24
A pair of founders describe a code-review setup where one AI agent writes changes, a different model family reviews them, and a third model runs an adversarial pass before a human merges the code.
Their key point: review is most useful when the reviewer is meaningfully different from the writer, because a reviewer that uses the same base model often inherits the same blind spots and simply agrees with the original mistakes. The downside is cost: the reviewer has to rebuild context from scratch by pulling the branch, rerunning tests, and re-deriving the reasoning. They ask how others make this pattern cheaper at scale.
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