Practical Multi-Agent AI Systems: How to Architect, Build, and Scale Next-Generation AI Systems That Work in the Real World (Tech Today)

Build production-grade multi-agent AI systems with LangChain, LangGraph, and MCP Practical Multi-Agent AI Systems: How to Architect, Build, and Scale Next-Generation AI Systems That Work in the Real World walks through a complete, production-grade multi-agent system as a continuous project example.Using LangChain, LangGraph, MCP, A2A, and language models from OpenAI, Anthropic, and Amazon Bedrock, the book covers knowledge retrieval, personalized response generation, escalation orchestration, error handling, controls to secure multi-agent AI systems, integration testing and model evaluations, and deployment considerations with real, runnable code designed for practitioners.Each chapter pairs architectural insights with hands-on implementation, covering patterns including ReAct, Supervisor-Driven Network, Hierarchical Network, Tree-Of-Thought, Chain-Of-Agents, Sequential Orchestration, Semantic Consensus, Hand-Off Orchestration, and Magentic Orchestration.All code examples are available