Description
This prompt forces the AI (as Grok) to ruthlessly sanity-check machine learning outputs by stripping away accuracy worship, exposing contradictions, domain-logic violations, fake confidence, unstable predictions, and misleading metrics, revealing where the model will confidently fail in real-world decisions, and delivering blunt, high-impact recommendations — from sanity constraints to evaluation slices and human-in-the-loop safeguards — so the system becomes trustworthy rather than merely good on paper.



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