The claim that most BrowseComp uplift came from index optimization rather than post-training is a pointed datapoint in the debate over where agent leverage actually lives. Readers should note the source: Foody runs Exa, so this is partly a sales pitch, and BrowseComp — which rewards surfacing obscure pages — is precisely the benchmark most flattering to an index vendor. Still, the underlying thesis rings true: deep research agents are often bottlenecked by retrieval quality, freshness and coverage rather than raw model capability. If the pattern holds, the moat in AI search shifts to expensive index infrastructure, and labs that treat search as a commodity tool will keep underperforming on agentic evals.