Agent Orchestration
Coordinating multiple AI models, tools, or agents to work together on a complex goal.
Agent orchestration is managing a multi-step workflow where multiple AI agents or tools cooperate. Example: - Agent A: "Analyze this image." - Agent B: "Based on that analysis, search for related products." - Agent C: "Rank the products by price and rating." - Final output: A ranked recommendation.
Orchestration frameworks like LangChain, AutoGen, and Crew.ai help manage state, routing, and communication. Orchestration is complex because you need to: - Define each agent's role and tools. - Route messages between agents. - Handle errors and retries. - Manage context and memory. - Monitor costs and latency.
Orchestration shines for complex tasks but adds operational overhead. Simple tasks don't need orchestration.
Example
A hiring assistant orchestrates: Agent A screens resumes, Agent B interviews candidates, Agent C compares qualifications.