Retrieval-augmented generation works when the knowledge base is trustworthy and the retrieval layer is measurable. Without that foundation, AI answers become confidently wrong.
Begin with document quality: ownership, freshness, and access controls. Then evaluate retrieval precision before optimizing prompts.
Production systems need failure modes: low-confidence responses, escalation paths, and citation visibility. Users should know when the system is uncertain.
Treat evaluation as a product feature. Track answer quality, latency, and cost as first-class operational metrics.
