Agent Architectures: Design Patterns for Multi-Agent AI Systems - Patterns · Protocols · Coordination · Governance

Design Patterns for Multi-Agent AI Systems Multi-agent AI systems are transforming how we build intelligent applications. But moving from a single chatbot to coordinated agent teams requires new architectural thinking. Agent Architectures provides the definitive guide to designing multi-agent systems that actually work. You'll master four foundational patterns: Orchestrator: Central coordination for complex workflows with clear task boundaries Council: Multi-agent deliberation and voting for high-stakes decisions requiring diverse perspectives Swarm: Emergent behavior through indirect coordination for exploration and optimization Guardian: Policy enforcement and safety boundaries for production systems Beyond individual patterns, you'll learn how to combine them into hybrid architectures, implement secure agent identity and authentication, and build the policy infrastructure that enterprise deployments demand. Each chapter includes production-ready Python code, available in the companion repository. Whether you're building autonomous research assistants, collaborative coding tools, or enterprise automation systems, this book gives you the architectural blueprints to succeed. What you'll learn: When to use each pattern and their trade-offs Communication protocols (MCP, A2A) for agent interoperability Agent identity, authentication, and access control A complete research assistant example combining all patterns Companion code: github.com/vijaygwu/Agent-Architectures Read more