Most agents that "hallucinate" in production aren't actually hallucinating. The right context existed in the index. It just didn't make it to the top of the retrieval window.
Reranking is the layer that decides whether your agent sees the answer or the noise. And the choice between reranker types shapes the failure mode you'll spend the next quarter debugging.
I keep seeing teams pick a reranker the way you'd pick a vector DB — benchmark on a public dataset, ship the winner, move on. That works for retrieval-augmented chatbots. It doesn't work for agents, because the failure modes are different in a way the benchmarks don't surface — and because, as we learned the hard way building HiveIn, there is no single reranker that fits every retrieval call you make once you have more than one shape of query.
The shape of the silent failure:
User → Agent: "Cancel my subscription."
