The hidden engineering costs of live web search in AI agents
BananaOutrageous475 · reddit · 2026-10-20
A practitioner lays out the non-obvious problems that emerge when agents do live web search: research agents fire parallel queries across multiple steps and pass huge result payloads to the model; providers fast on average can choke at high concurrency; thin-but-relevant results force per-page fetches; stale results are worse than none for prices and incidents; more text improves grounding but raises token costs. They ask whether teams track p95/p99 latency, freshness, source coverage and tokens-per-correct-answer, and whether different agent workloads need separate search setups.
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