How it works
Agent orchestration is a coordination layer sitting above individual agents. It decides task decomposition, routing, ordering, shared state, and when control returns to a human or a deterministic step. The common patterns are:
- Sequential (pipeline): agents run in a fixed order, each consuming the prior output. Predictable, easy to checkpoint, weak at branching work.
- Hierarchical / supervisor: a coordinating agent plans, delegates to workers, and integrates results. Flexible, but the supervisor becomes the reliability bottleneck.
- Swarm / peer: agents hand off to each other by role with no central controller. Resilient and parallel, harder to trace and bound.
Underneath the pattern, an orchestrator owns three things: a shared state or context each agent reads and writes, a routing policy that selects the next agent, and a control boundary that governs tool access, permissions, and stop conditions. Good orchestration keeps these explicit and inspectable. Bad orchestration hides them inside model prose, so you cannot tell why an agent ran or what it was allowed to touch.
Why it matters in an agent harness
Orchestration is where a harness earns its keep. A single agent has one loop to observe and bound; a fleet multiplies the surfaces you must control.
- Blast radius: each worker should carry least-privilege scope, not inherit the whole system's permissions. Orchestration is where you enforce that boundary.
- Observability: you need a trace of who ran, why they were selected, and what they wrote. Without it, a multi-agent failure is unattributable.
- Reversibility: shared state that many agents mutate is easy to corrupt. Checkpoints and rollback per handoff keep a bad step from poisoning the run.
- Failure containment: one worker's hallucination can propagate as another's premise. The orchestrator is the natural place to validate outputs before they become inputs.
- Cost and termination: more agents means more loops, more tokens, and more chances to spin. Iteration and tool budgets belong at the orchestration layer.
The lesson is that orchestration is not "add more agents." It is the discipline of making coordination legible and bounded enough to operate.
Agent orchestration vs multi-agent system
These get used interchangeably, but the distinction changes what you build.
| Multi-agent system | Agent orchestration | |
|---|---|---|
| What it is | The collection of agents | The coordination of them |
| Concern | Which agents exist, their roles | Routing, ordering, state, control |
| Failure it prevents | — | Uncontrolled handoffs, propagation |
| You can have | Many agents, no orchestration | Orchestration of even two agents |
A multi-agent system describes the population. Orchestration describes the control policy over it. You can assemble a multi-agent system and still have no orchestration — agents call each other ad hoc, with no shared boundary. That is exactly the state that produces untraceable runs. Treat orchestration as the layer you design deliberately, not an emergent property of having several agents.
The Rifty take
We optimize for legible, bounded coordination over agent count. Adding an agent adds coordination cost and a new failure surface, so the default answer to "should this be another agent?" is no until a single loop demonstrably cannot hold the work. When we do orchestrate, we insist the routing policy, the permission boundary, and the handoff trace be explicit and inspectable — a coordination step you cannot observe is a coordination step you cannot control or reverse.
Common failure modes
- Implicit routing: the next agent is chosen inside model reasoning with no logged rationale, so runs are unattributable.
- Shared-state corruption: many agents mutate one context without checkpoints, and one bad write cascades.
- Permission inheritance: workers run with the supervisor's full scope instead of least privilege.
- Hallucination propagation: unverified worker output becomes another agent's trusted premise.
- Unbounded loops: no iteration or tool budget on the fleet, so agents ping-pong or spin.
- Orchestration theater: several agents wired together with no real coordination policy — complexity without control.
Frequently asked questions
When should I use multiple orchestrated agents instead of one agent?
Reach for orchestration only when a single agent loop demonstrably cannot hold the work — genuinely distinct roles, parallelizable subtasks, or separate permission scopes. Each added agent brings coordination cost and a new failure surface, so default to one loop until the evidence forces a split.
Which orchestration pattern should I pick?
Match the pattern to the work: sequential pipelines for fixed, predictable stages; hierarchical supervisors for planning and delegation with integration; swarms for resilient parallel handoffs. Sequential is easiest to checkpoint and trace; swarm is hardest to bound. Start with the simplest pattern that fits and add structure only when needed.
How is agent orchestration different from an agent loop?
An agent loop is the single perceive-decide-act cycle inside one agent. Orchestration is the layer above it that coordinates several such loops — deciding routing, ordering, shared state, and control boundaries. You can run one loop with no orchestration, but orchestration always presupposes multiple loops to coordinate.
What is the biggest reliability risk in multi-agent orchestration?
Hallucination propagation: an unverified output from one worker becomes a trusted premise for the next, so a single bad step corrupts the whole run. Contain it by validating outputs at handoffs, checkpointing shared state, and keeping a trace of who ran and why, so failures stay attributable and reversible.
How do I keep orchestration observable and controllable?
Make the three orchestration primitives explicit: routing policy, shared state, and permission boundary. Log which agent was selected and why, checkpoint state at each handoff, give each worker least-privilege scope, and enforce iteration and tool budgets on the fleet. A coordination step you cannot observe is one you cannot reverse.