AI Agents
Contributing to LangChain's open_deep_research
Ran and contributed to LangChain's flagship open-source deep research agent — a supervisor + sub-researcher multi-agent system that placed #6 on Deep Research Bench.
LangGraphLangChainTavilyMCPLangGraph Platform
Worked with LangChain’s open_deep_research architecture: a supervisor agent decomposes a research request into a brief, dispatches parallel sub-researchers using a think_tool for intermediate reasoning and a ResearchComplete signal, then compresses and merges findings into a final report — all under explicit token-budget management.
Key Results
- →#6 on Deep Research Bench with a score of 0.4344 (0.4943 on the GPT-5 configuration)
- →Supervisor + sub-researcher multi-agent architecture: clarify → research brief → parallel ConductResearch → compression → report
- →Evaluated with an LLM-as-judge (RACE score, Gemini judge) against benchmark tasks