What is a Research Agent?

A basic search tool returns raw results and leaves the reading and synthesis to a human. A research agent instead runs a multi-step loop: it plans what to search for, issues several searches, reads the returned pages or documents, decides whether the answer is sufficiently supported or needs another round of digging, and eventually produces a synthesized answer with citations back to its sources. This mirrors how a human researcher works, but at a speed and breadth a person can't match for wide, shallow information-gathering tasks. The hard part of building a good research agent isn't fetching information — it's judgment: knowing when a source is reliable, when a claim needs a second source to confirm it, and when the agent has gathered enough to stop rather than looping indefinitely. Adversarial verification, where a second pass actively tries to falsify a claim rather than just repeating it, meaningfully improves the trustworthiness of the final output over an agent that simply summarizes the first few search results it finds. Research agents are increasingly used not just for general questions but for domain-specific due diligence: competitive analysis, vendor evaluation, or fact-checking a claim before it goes into a customer-facing document.