Orchestrator Agent

A manager handed a research report doesn’t write every section. They split the work, give each person a brief, then edit the pieces into one document. An orchestrator agent does the same with AI agents. Asked to compare five vendors, it can start one subagent per vendor, give each a narrow brief and a search tool, and write the comparison from their summaries. The subagents are the workers: each is an agent with its own instructions, context window and tool permissions, and usually reports back only to the orchestrator.

The main benefit is focus. A subagent that only reads one vendor’s documents doesn’t fill the lead agent’s context with all of them, and independent pieces can run in parallel. Anthropic’s write-up of its research system describes this design: a lead agent plans, starts subagents in parallel and combines their findings. The costs are coordination and tokens. Every brief the orchestrator writes can be vague, every subagent can go off course, and the lead agent has to notice. That is why the pattern suits work that splits cleanly, and why a single agent is often the better default.

This is one structure inside a broader multi-agent system, the hierarchical one. A looser group of agents coordinating without one clear lead is closer to an agent swarm.

On Chain of Thought, AMD’s Anush Elangovan describes running about a dozen main agents, each with sub-agents. In episode 56 at 8:11, he gives each sub-agent one transpiler target, the numerics it must check and a performance guarantee, then reviews the result. Later in the same episode, Conor says that “sometimes subagents do really dumb things” (37:52). Galileo sponsored episode 56. In episode 63 at 31:11, Yutori’s Dhruv Batra describes his product as a multi-agent system with “a top-level orchestrator” that launches web navigators. In episode 76 at 32:39, Sonar’s Andrea Malagodi says the setups he has seen work best use an orchestrator agent with engineering, product and quality personas that challenge each other. Episode 76 credits Svix, Walrus Memory and Inngest as Season 4 presenting sponsors; see the Svix read. In episode 62 at 33:29, Kris Lovejoy uses the same shape to explain AI-driven attacks: an orchestration agent directing many smaller agents.

Our reading is that the orchestrator is a manager, so it inherits a manager’s problems. Clear briefs, narrow permissions for each subagent and a check of what comes back matter more than the number of agents running.