Agent orchestration is the coordination of several AI agents working on one piece of work: deciding which agent handles which step, in what order, passing results between them and deciding when the work is done. It can be done by fixed rules, by a dedicated orchestrator agent, or by a mix. Orchestration organises the work; it does not, on its own, govern it.
Why does orchestration matter once agents act?
A single agent with a dozen tools becomes hard to test and hard to certify. Splitting the job, so one agent gathers documents, another checks them, and a third drafts the outcome, makes each agent narrower and easier to prove. Orchestration is what holds the pieces together.
It also introduces a new risk. When work passes between agents, authority can pass with it, often without anyone deciding that it should. An agent cleared only to read can end up triggering an action through another agent that is cleared to execute. We call this authority sprawl, and orchestration without authority sprawl sets out how to prevent it.
How does agent orchestration work in practice?
There are two common patterns. In rule-based orchestration, a defined workflow decides which agent runs next, like a flowchart with agents at some of the steps. In agent-led orchestration, an orchestrator agent reads the task, breaks it into parts and assigns them to other agents, adjusting the plan as results come in.
Either way, each handoff should carry three things: the task, the facts with their provenance, and the identity of the agent asking. The receiving agent then acts under its own bounds, not the sender's. Coordinating other agents is itself a capability, the highest depth in our model, and reserved for orchestrators that have earned it.
What does orchestration look like in an example?
A business bank's onboarding work involves collecting documents, checking company records, screening directors and preparing the account file. An orchestrator assigns collection to one agent, record checks to another and screening to a third. A pre-trained agent for document collection might handle the first step. When screening returns a possible match, the orchestrator does not resolve it. It routes the case to a named analyst, because resolving a match is outside every agent's bounds in this flow.
How is agent orchestration different from an agentic operating system?
Orchestration answers "who does what next". An agentic operating system answers "is this agent allowed to do this, now, on this evidence", for every action from every agent, and records the verdict. An orchestration layer can be part of the system, but routing work is not the same as holding authority over it. The distinction is drawn out in how an agentic operating system differs from an orchestration layer.
Where Pryme fits
In Pryme, coordinating other agents is depth 5, open only to orchestrators. Every action a sub-agent takes is still checked against that sub-agent's own minimum chain, so an orchestrator cannot pass on authority it was never granted. See the governed agentic operating system, explained.
Questions people ask
Is agent orchestration the same as workflow automation?
Not quite. Workflow automation runs fixed steps in a fixed order. Agent orchestration can do that, but it can also let an orchestrator change the plan as it goes, which is more flexible and needs tighter bounds.
How many agents should one orchestrator manage?
As few as the job needs. Each extra agent adds handoffs to test and certify. Split work where it makes each agent easier to prove, not to look sophisticated.