TLDR Tech / Data
How to evaluate LLMs before production
GitHub's secret-scanning work shows why LLM evaluation should optimize the production decision, not generic benchmark scores. Prompts, models, input construction, and eval configs were versioned like code, then tested against production-like ambiguity. That discipline cut false positives by 95% offline while preserving recall within the safety guardrail.
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