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AI systems / FIELD GUIDE

RAG starts with knowledge ownership

Retrieval-augmented generation depends on the documents it retrieves. Before choosing embeddings or a vector database, decide who owns the knowledge and which version is trustworthy.

The decision that matters

Create an inventory with document owner, review state, intended audience and revision date. Separate approved procedures from drafts and historical notes. Retrieval must respect the reader’s permissions; a relevant passage is still inappropriate if the user cannot access it. Treat source deletion and access revocation as lifecycle events that must reach the search index, not just the document interface.

A practical scenario

Consider two refund procedures in a knowledge base: a current policy and an older draft with a more generous limit. Both may look semantically relevant. An assistant that selects the draft can produce a confident but unsuitable answer. A review state and explicit supersession link help the retrieval layer choose the appropriate source before the model writes anything.

Before you ship

  • Assign an owner and review state to important documents.
  • Carry access rules into retrieval filters.
  • Test updates, deletion and permission revocation end to end.

A useful next step

Choose a small, well-maintained collection for the first retrieval workflow. Ask reviewers whether the selected passages are sufficient before judging the generated answer. Improving source quality often resolves failures that would otherwise be misdiagnosed as a model or prompting problem.

Primary reference & further reading

This guide combines general engineering recommendations with an illustrative scenario. Provider behavior can change; check current documentation before applying it. Read our editorial approach.