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Adversarial Review

A reviewer whose job is to find holes, not to approve.

After generating output, pass it to a separate agent with explicit instructions to:

  • Find flaws, gaps, or unstated assumptions
  • Challenge claims that lack evidence
  • Identify edge cases the original missed

The adversarial reviewer is not trying to be helpful to the original output. It’s trying to break it.

  • High-stakes decisions where being wrong is expensive
  • Output that will be trusted without human review
  • Claims that sound plausible but haven’t been verified
  • Any “are we sure?” moment
  • The reviewer should NOT see the original prompt or reasoning, only the output
  • Explicitly instruct it to default to skepticism
  • A finding that survives adversarial review is stronger than one that was never challenged
  • Using the same model instance for both generation and review (context bleeds)
  • Instructing the reviewer to “check if this looks good” (too soft)
  • Ignoring findings because they’re inconvenient