An orchestrator-worker agent pattern is a setup where one lead agent plans, delegates, and coordinates work, while several worker agents or tools handle smaller tasks in parallel or in sequence.
This pattern helps when a single LLM call is not enough because the job is too broad, too long, or naturally decomposes into parts. The lead agent reduces the problem into sub-tasks, assigns them, and then combines the results.
In practice, you reach for it when you want:
It is a common way to make agent systems more reliable and easier to debug.
The lead agent first interprets the user request and decides what needs to be done. It may create a plan, split the work into chunks, and decide which worker should handle each chunk.
Workers are usually narrower than the lead agent. A worker might search documents, write code, summarize an article, run a calculation, or extract fields from text. The lead agent does not need every worker to be a full agent; sometimes a worker is just a tool wrapper with a specific job.
After workers finish, the lead agent collects their outputs, checks for consistency, resolves conflicts, and produces the final answer or next action. This “plan → delegate → aggregate” loop is the core of the pattern.
This is closely related to hierarchical agent designs in the literature and in platform docs, but the exact boundary between “worker,” “tool,” and “sub-agent” varies by system. The pattern is conceptual more than standardized.
User: “Compare these three vendor contracts and tell me the key differences.”
Orchestrator / lead agent:
Worker outputs:
Lead agent response:
“Here are the key differences in pricing, renewal, and termination terms…”
In short: use it when the work is naturally divisible and coordination is the main challenge, not when you just want a bigger prompt.
