Agent Orchestration
Agent orchestration is the coordination layer that assigns work, sequences dependencies, and aggregates results across multiple AI agents.
In plain English
Agent orchestration is what turns a pile of capable agents into a working team. It is the scheduling and routing logic: which agent runs first, what inputs it gets, what it is supposed to return, and who picks up the result. Simple orchestration uses a single coordinator. More advanced orchestration uses directed graphs where agents run in parallel, fan out, and merge back.
Good orchestration handles three hard problems. First, dependencies — step B needs the output of step A, so the coordinator has to sequence them. Second, failure — when a specialist fails or times out, the orchestrator must retry, substitute, or surface the failure. Third, aggregation — when parallel specialists each produce a chunk of the answer, the orchestrator reconciles them into one coherent result.
Why it matters for Black Box
Orchestration is the IP. Any shop can wire a model to a couple of tools. The moat is the CEO loop, the delegation playbook, the evaluator gates, the summarizer, and the circuit breakers that make a multi-turn multi-agent run feel reliable from the owner's seat.
Examples
- Running the Research and Browser specialists in parallel, then passing both outputs to the Content specialist.
- Looping the Coding specialist with the Evaluator until tests pass or a cap is reached.
- Detecting a specialist stall and rerouting the task to a different specialist.