How to Tune Vector Search Without Guessing

Your collection works. Queries return in a few milliseconds, results are mostly right, and product keeps forwarding you the ones that aren’t. You open the search API reference and get exact definitions for hnsw_ef, reciprocal rank fusion k, and quantization oversampling. The definitions are correct. They still don’t tell you which setting is failing on your data. So you change one setting, rerun the queries, and the score moves by 0.01. Did relevance improve, or did the same queries land differently?