A ground-up guide to hub-and-spoke orchestration: one coordinator that plans the task, hands slices to specialised subagents, controls what each one sees, checks the combined work for gaps, and assembles a reliable answer.
A single AI agent can handle many tasks, but complex work often benefits from being split across several specialised agents.
One agent might search for information, another might extract facts from documents, another might compare evidence, and another might write the final answer. Multi-agent orchestration is the design discipline for coordinating that split without letting the system become chaotic.
An agent is an AI-driven component that receives a task, may use tools such as search or file analysis, and returns a result. Orchestration means deciding which agent should do which part of the work, what information each agent receives, when each agent runs, how errors are handled, and how the final output is assembled.
One practical pattern for controlled workflows is hub-and-spoke orchestration. In this pattern, one central coordinator manages the flow of work, while specialised subagents handle narrower tasks around it.
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