No Claim Without Evidence
A practical field guide for building AI systems you can verify, not just demo.
No Claim Without Evidence shows how to design LLM workflows with evidence links, evals, review rules, action traces, and release gates. It uses an extraction case study to demonstrate how clean-looking output can still be unsupported, then turns those lessons into reusable operating patterns for AI builders, product teams, and operators.
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