Build a Deep Research Agent: Plan, Search, Verify, Cite
Originally published on AI Tech Connect. What you need to know The architecture has converged. GPT Researcher, LangChain's Open Deep Research and Milvus's DeepSearcher were built independently and all landed on the same
Originally published on AI Tech Connect.
What you need to know The architecture has converged. GPT Researcher, LangChain's Open Deep Research and Milvus's DeepSearcher were built independently and all landed on the same shape: a planner, parallel search workers, and a publisher. The loop matters more than the search engine. A mediocre search used four times with reflection between rounds beats an excellent search used once. Verification is its own stage. Extract claims with their source attached, check claims against stored excerpts, and hunt for contradictions before a word of the report is written. Citations are a data-flow property. One number per unique URL, assigned by code, mapped claim-by-claim β not a formatting request buried in a prompt. Fully local is practical. An open-weight Qwen-class model on Ollama, localβ¦
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