AI Agent 系列 (第4集) | 打造你的 AI 虛擬團隊：Multi-Agent 架構全解析

This episode explores building AI virtual teams using Multi-Agent architecture. It breaks down the roles of Supervisor (指揮官) and Worker (專家) agents in a hierarchical system. The content provides a comprehensive analysis of how to structure multiple AI agents to work together effectively, enabling delegation and specialization within an AI team framework.

Key Points

• •Multi-Agent architecture enables building virtual teams with specialized AI agents
• •Supervisor agent acts as a coordinator/manager directing tasks to appropriate workers
• •Worker agents are specialized experts handling specific domains or tasks
• •Clear role definition between Supervisor and Worker agents improves system efficiency
• •Hierarchical agent structure allows for task delegation and workflow orchestration
• •Multi-Agent systems enable parallel processing and specialized expertise distribution
• •Supervisor uses routing logic to assign tasks to the most suitable Worker agent
• •Worker agents can be customized with domain-specific knowledge and capabilities

Workflow Diagram

Concepts