How do you benchmark the search layer inside AI agents? One dev's metric checklist
BananaOutrageous475 · reddit · 2026-10-21
A developer lays out a systematic framework for evaluating web-search providers in agent stacks, beyond eyeballing final answers: watch for stale results, thin snippets, duplicate URLs, and bloated payloads; use p95/p99 latency since parallel searches mean one slow request stalls the whole step; benchmark providers on a fixed query set with model, prompt, and result count held constant, measuring answer accuracy, source quality, freshness, unique relevant results, wall-clock latency under load, tokens used, and cost per usable answer; and match the provider to workload — monitoring agents need freshness, research agents coverage, coding assistants low latency and dense doc passages. The key idea: benchmark the retrieval layer separately from generation.
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