Agent Orchestration
Definition
Agent orchestration is the process of coordinating multiple AI agents, managing their workflows, handling communication between them, and ensuring they work together effectively toward a common goal.
Why It Matters
As AI systems grow more complex, orchestration becomes critical. Without proper coordination, agents can duplicate work, create conflicts, or get stuck in loops. Good orchestration ensures efficient task routing, proper sequencing of dependent tasks, error handling, and resource management across your agent fleet.
How It Works
Orchestration systems typically include: task routing (directing requests to the right agent), state management (tracking progress across agents), dependency handling (ensuring tasks execute in the right order), error recovery (handling failures gracefully), and observability (logging and monitoring agent activities). Tools like LangGraph provide graph-based orchestration, while CrewAI uses role-based coordination.
When to Use It
Invest in orchestration when you have: (1) multiple agents that need to collaborate, (2) complex workflows with dependencies between steps, (3) requirements for reliability and error handling, or (4) need for monitoring and debugging agent behavior. For single-agent systems, simpler patterns usually suffice.