Multi-agent orchestration is the coordination of multiple AI agents working together in a pipeline or workflow. Each agent has a single responsibility, defined input/output contracts, and constrained permissions. The orchestration layer manages handoffs between agents, enforces governance gates at transition points, and maintains end-to-end audit trails across the entire pipeline.
Key Concepts
01Single responsibility — each agent does one thing well with clearly defined boundaries
02Contract-based handoffs — data flows between agents through validated contracts, not ad-hoc interfaces
03Quality gates — validation checks between agents prevent bad data from propagating downstream
04End-to-end audit — full provenance chain from first agent input to final pipeline output
05Independent scaling — each agent can be scaled, updated, or replaced without affecting others