Deep Web Research with AG2 and GPT Researcher
Ask an LLM to research a topic and write a report. It'll produce something -- sometimes quite good. But probe the sources, check the claims, or ask for substantial revisions and the limitations show up fast. The agent that searched the web is also the one drawing conclusions from it. There's no review step between research and writing. Errors and gaps pass straight through to the final document.
The fix isn't a better prompt. It's division of labor.
GPT Researcher, created by Assaf Elovic, is built on this idea: specialized agents, each with a distinct job, working through a staged pipeline. A researcher gathers, an editor outlines, a reviewer challenges the findings, a revisor incorporates the feedback, and a writer only touches finalized content. Every handoff is a quality check.
This post walks through the build-with-ag2 example, which runs the full pipeline with AG2 as the orchestration layer. The example ships with two run modes -- a terminal script and a web UI built on AG-UI that shows pipeline progress in real time and includes a human-in-the-loop review step before writing begins.