Architecting Multi-Agent Systems: Build Production-Ready Agentic AI with MCP, A2A, and Enterprise Orchestration

The agentic AI space is accelerating fast - and most engineers are shipping fragile prototypes they will be rewriting in six months. They are locked into single frameworks, missing the foundational reasoning behind orchestration decisions, and finding that agents that demo beautifully collapse under real-world load. >What you will learn: - Build multi-agent systems from first principles using the PicoAgents library, so no framework is a black box to you again- Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols for interoperable, extensible agent communication- Design production-grade RAG pipelines and agent memory architectures that survive real workloads- Apply orchestration patterns - routing, reflection, tool use, and handoffs - across complex multi-agent workflows- Evaluate and test your agents systematically with structured benchmarks before you ship, not after- Deploy, observe, and scale agentic AI in enterprise environments using LLMOps and observability best practices Navigate governance, cost optimisation, and compliance for enterprise-grade agentic AI deployments Written by a Microsoft Research contributor and AutoGen core team member, this is the book for software engineers, ML engineers, and technical leads who have moved past what an AI agent is and need to ship systems that hold up in the real world. Whether you are architecting your first production