Retrieval-Augmented Generation Is a Data Product

RAG is often treated as plumbing: split documents, create embeddings and place results in a prompt. That gets data into context. It does not establish that the evidence is correct, current or appropriate for the user.

Which sources are authoritative? Who owns them? How quickly must changes appear? What should happen when sources conflict or access changes? Retrieval needs evaluation using real questions, expected evidence and deliberate no-answer cases, not just attractive demonstrations.

Measure source coverage, ranking quality, citation usefulness, freshness and permission correctness separately from final-answer quality. Each failure has a different remedy.

A vector store is infrastructure. RAG becomes a product when a team owns the evidence experience, including what happens when the right answer is that no reliable evidence exists.