Agent Orchestration Testing
Agent orchestration testing verifies the layer that routes tasks between multiple AI agents — deciding which agent runs next, passing state between them, and handling retries or timeouts — separately from testing what any individual agent does. It's closer to testing a workflow engine than testing a model.
The orchestrator is the part of a multi-agent system most likely to be plain, deterministic code (a state machine, a graph, a queue), which means it's actually testable the traditional way — unit tests for routing logic, integration tests for state handoffs — even though the agents it's coordinating are not.
The highest-value tests target failure paths: what happens when an agent times out, returns malformed output, or calls a tool that errors? A good orchestrator degrades gracefully — retries, falls back to a simpler agent, or surfaces a clear failure — rather than hanging or silently dropping the task. Testing should deliberately inject these failures rather than only exercising the happy path.
Logging the full routing decision trail (which agent ran, why, with what input) is what makes orchestration bugs debuggable at all — without it, a wrong final answer gives no clue whether the fault was a bad routing decision or a bad agent response.
