The article emphasizes that single, monolithic AI agents, similar to monolithic software applications, lead to bottlenecks and increased errors. It advocates for Multi-Agent Systems (MAS) as an AI equivalent of microservices architecture, promoting decentralization and specialization for enhanced modularity, testability, and reliability. The guide details eight multi-agent design patterns using the Google Agent Development Kit (ADK), including Sequential Pipeline, Coordinator/Dispatcher, Parallel Fan-Out/Gather, Hierarchical Decomposition, Generator and Critic, Iterative Refinement, and Human-in-the-Loop. Each pattern is explained with use cases, diagrams, and ADK pseudocode, providing concrete examples for building production-grade agent teams. It concludes with pro-tips on state management, clear descriptions for routing, and starting with simple designs to manage complexity.




