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Multi-agent orchestration: divide the work, keep control

When one agent is not enough: splitting work across agents, who coordinates, and how shared budgets and audit logs keep it controllable.

Updated 2026-08-22Reading time 6 min

One agent, or many?

Most tasks are single-agent tasks. You reach for several agents when the work is genuinely parallel — different repos, different devices, different owners — not because it sounds advanced. Orchestration is a cost multiplier, so it must multiply output, not ceremony.

The patterns that work

PatternWhen it fitsControl needed
Parallel buildsIndependent repos or featuresPer-task budgets
SpecialistsOne agent per domain (code, docs, checks)Clear handoff formats
Scheduled workersNightly jobs on separate devicesCron + alerts

Who coordinates?

Prefer a human coordinator and dumb handoffs: each agent writes its result to a file, the next reads it. A fully autonomous coordinator agent is powerful and correspondingly hard to audit — if you build one, every handoff must land in the audit trail with the same evidence as any other step.

Control scales with the number of agents

Start with two

Run two agents in parallel for a week before adding a third. The failure modes of orchestration — race conditions on shared files, doubled spend, lost handoffs — appear with two agents just as clearly, and cheaply.