Orchestrator

What is an orchestrator?

An orchestrator is the component that coordinates work across agents, tools, or workflow steps. It can route tasks, track dependencies, manage shared state, enforce limits, handle failures, and combine results into a final outcome.

An orchestrator may be deterministic application code, an AI agent, or a combination of both.

What an orchestrator does

In a multi-agent research system, an orchestrator might:

1. break the request into research tasks;
2. assign each task to an appropriate sub-agent;
3. provide bounded context and permissions;
4. track completion and retry failures;
5. verify that outputs include sources;
6. resolve duplicated or conflicting findings;
7. combine the accepted results.

The orchestrator owns coordination even when specialized agents own individual tasks.

Orchestrator versus agent

An agent interprets a goal and chooses actions through an execution loop. An orchestrator manages how work moves among components. An orchestrator can be agentic, but it does not have to be.

For predictable routing, deterministic code is often safer. An agentic orchestrator is useful when assignment or integration requires judgment that cannot be fully predefined.

Orchestrator versus workflow

A workflow is the sequence or graph of work. The orchestrator is the component that executes or coordinates that structure. It may select a branch, start parallel tasks, wait for dependencies, and update state.

An orchestrator also differs from a sub-agent. The orchestrator assigns and integrates work; a sub-agent completes a delegated part.

Design trade-offs

Central orchestration creates clear ownership and makes monitoring easier. It can also become a bottleneck or single point of failure. Peer-to-peer agent systems reduce central control but make state consistency, conflict resolution, and tracing harder.

An orchestrator should not pass the entire system history to every agent. Context should be scoped to the assignment, while shared facts and task status remain traceable.

Common failure modes

Weak orchestration causes duplicated work, lost handoffs, unbounded retries, incompatible formats, and uncertain ownership. A model-based orchestrator may also select the wrong specialist or accept a confident but unsupported result.

Reliable systems use explicit task contracts, budgets, permission boundaries, result validation, and clear terminal states.

Why it matters

As a system gains tools, agents, and parallel work, coordination becomes a primary engineering problem. The orchestrator makes execution observable and keeps local decisions aligned with the overall goal.

Its purpose is not merely dispatching calls. It is maintaining control over dependencies, state, risk, and final integration. See [Single-Agent vs Multi-Agent Systems](/single-agent-vs-multi-agent-systems/) for architecture choices.