Your AI Agent Doesn't Have a Search Problem. It Has a Context Problem
Web search often gets blamed when AI agents fail, and that’s fair to some extent. But the real fault line is what happens to the search results after the agent finds them.
Ask an AI agent a simple question, and it usually gets the answer right. But ask it something that depends on freshness, nuance, or multiple sources, and things start to go off the rails. The agent will still answer, but it might give you a completely off-base response with the same confidence it had when answering the easy question.
Most teams initially chalk this up as a search problem, thinking they can swap in a better search API, add another data source, or make adjustments to the retrieval rankings. Make no mistake: search quality matters. But the harder failure often sits downstream.
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