Retrieval Is a Relevance Filter, Not a File Dump
Explain why retrieval quality depends on filtering and ranking, not just fetching more chunks.
Retrieval is a selection system. Its job is not to prove you indexed a lot of files; its job is to present a small evidence set the model can actually reason over. OpenAI's retrieval guide emphasizes metadata filters and ranking controls because relevance is not binary. If the retrieved set is broad, stale, or internally contradictory, the generation step inherits that mess. This is why mature RAG workflows tune the retriever before they tune the model prompt. Metadata can constrain the search to the right project, region, document type, or date range. Ranking thresholds can drop chunks that are merely…
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