Blog
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Which signal failed
A query returned nothing useful. A procedure for finding whether lexical missed, dense missed, fusion buried it, or the document was never indexed.
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When a reranker earns its latency
A cross-encoder reads the query and passage together, which is why it ranks better and costs more. Where it belongs, what to feed it, and when to skip it.
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Fusing two ranked lists
BM25 scores and cosine similarities aren't on the same scale. Reciprocal rank fusion, score normalisation, and what each method throws away.
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What keyword search misses
Vocabulary mismatch: when the user's words and the document's words don't overlap, term scoring has nothing to score. Where stemming stops helping.
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What vector search misses
Identifiers, rare terms, negation and exact phrases. Five query classes where embeddings return plausible neighbours instead of the document you asked for.