How we built our multi-agent research system

This post details the development of a multi-agent research system, emphasizing principles for agent coordination, evaluation, and reliability. It introduces an orchestrator-worker pattern with specialized subagents for parallel information gathering and analysis, significantly improving performance on breadth-first queries. Key learnings include prompt engineering strategies for delegation, scaling effort, tool design, self-improvement, and parallel tool calling, which reduce research time and increase information coverage.