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Validating LLM Judges: Catch Rate, False Flags and Held-Out Labels
An LLM judge is only useful once you know how often it catches real failures and how often it wrongly flags good outputs, measured on human labels it was not tuned on. Raw agreement is misleading when failures are rare. This guide covers the split, the two rates, sample sizes and how to correct production estimates.
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