Overview

BUILDING REAL-WORLD AI AGENTS WITH LANGCHAIN AND LANGGRAPH: A Practical Guide to Production-Ready Workflows, RAG Systems, and Multi-Agent Automation is the definitive guide for developers, engineers, and data professionals who want to move beyond prototypes and build intelligent AI systems that perform reliably in real-world environments. This book provides a step-by-step, hands-on approach to designing, deploying, and scaling LLM applications using LangChain and LangGraph. You will learn how to construct production-ready workflows, implement retrieval-augmented generation (RAG) pipelines, and design multi-agent systems capable of reasoning, coordinating, and automating complex tasks. Through clear explanations and practical code illustrations, this guide shows how to bridge the gap between experimental models and robust, enterprise-grade AI solutions. Every chapter focuses on actionable strategies, from orchestrating agents and managing context to reducing hallucinations and integrating external tools, ensuring that your AI systems are not only smart but also stable, secure, and reliable. The book also addresses essential enterprise considerations, including observability, monitoring, CI/CD pipelines, ethical AI practices, and compliance requirements. Readers gain the knowledge to build AI systems that can adapt to real-time data, handle errors gracefully, and maintain accountability, making them suitable for high-stakes applications across industries. By the end of this book, you will have the technical expertise and confidence to design, deploy, and scale AI agents that deliver tangible value. You will understand how advanced workflows, multi-agent coordination, and reliable RAG systems are constructed in practice, enabling you to create solutions that go beyond simple chatbots or prototypes. This is the ultimate guide for anyone serious about mastering LangChain and LangGraph to build production-ready AI agents that are intelligent, resilient, and ready for real-world challenges.

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