Orchestrator Agent

In a well-designed multi-agent system, not all agents are equal. The orchestrator occupies a distinct role: it receives the original objective, constructs the execution plan, assigns work to the appropriate specialist agents (a research agent, a coding agent, a review agent), monitors completion, handles failures, and integrates the sub-outputs into the deliverable. This separation of concerns is what makes multi-agent systems manageable — the orchestrator holds the plan; the specialists hold the expertise.

The orchestrator pattern mirrors enterprise management structures deliberately. Like a project manager, the orchestrator must track which tasks are in flight, which are blocked, and which have produced results that require review before the next step can proceed. Unlike a project manager, it operates at machine speed and can manage hundreds of concurrent sub-tasks. Frameworks like LangGraph, CrewAI, and AutoGen all provide first-class orchestrator constructs — typically a supervisor agent with the ability to invoke sub-agents and route their outputs.

The enterprise governance value of explicit orchestrator agents is significant: all task assignments flow through a single, logged, policy-enforced layer. Access controls are applied once (at the orchestrator) rather than duplicated across every specialist agent. Cost attribution is centralized — the orchestrator can track spend per task and enforce budget constraints before delegating to expensive sub-agents. And failure handling is unified — the orchestrator is the single point of escalation when a sub-agent cannot complete its task.