An orchestrator agent is an AI agent whose job is to coordinate other agents or steps — breaking a big goal into smaller parts, handing each part to the right place, and pulling the results back together. It's the project manager of a multi-agent setup, rather than a hands-on worker itself.
As businesses move from using a single AI assistant to running several purpose-built AI agents, a new question appears: who makes sure they all work together toward the same goal, in the right order, without duplicating or contradicting each other? That's the job of an orchestrator agent.
Rather than doing the detailed work itself, an orchestrator breaks a larger goal down into smaller pieces, decides which specialised agent (or step) should handle each piece, and then assembles the individual results into one coherent output. It's the coordination layer sitting above the agents actually doing the work.
This becomes valuable once a business has more than one or two agents running — the same way a project needs a manager once it has more than one person working on it. A single orchestrator overseeing several task-specific agents is generally more reliable than expecting one agent to handle a complex, many-part goal entirely on its own.
ExampleAsked to "prepare this month's client report," an orchestrator agent might send one agent off to gather the relevant figures, hand a second agent the job of drafting a plain-English summary of them, and then assemble both into a single finished report — checking the pieces fit together before it's done.
Most businesses starting out with AI agents won't need an orchestrator immediately — it becomes useful once you're running multiple agents on interconnected parts of the same larger task. It's worth knowing the concept early, even if you build toward it gradually.
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