You don't eliminate hallucination — you engineer systems where errors are rarer, detectable, and cheap: grounding, citations, refusal paths, and
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Retrieval-first architecture means the model answers from provided passages, not memory. The un-grounded confident answer is the failure class to design out.
Every claim traceable to a source; thin retrieval triggers 'I don't know' plus escalation. A bot that declines gracefully beats one that invents policy.
Structured outputs, enums, and validation catch a large error class mechanically — free-text is where hallucination lives; schemas are fences.
Evaluation sets from real cases give you an error number before launch and drift alerts after. Unmeasured systems hallucinate confidently; measured ones tell you exactly how often.
Skipping the discipline this article describes until an incident, audit, or stalled project forces it — every practice above is cheaper adopted early than retrofitted under pressure.
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