LANGCHAIN FOR BEGINNERS

Learn to Build Real AI Applications Not Just Talk About Them

Every day, more developers are asked to add AI features to their products. Most tutorials stop at "here's how to call an API." This book goes further.

LangChain for Beginners is a hands-on, project-based guide that takes you from your very first language model call to building complete, production-aware AI applications agents that use tools, assistants that remember conversations, and RAG systems that answer questions using your own documents.

You won't just read about LangChain. You'll build with it, chapter by chapter, until the concepts become second nature.

Inside, you'll learn how to:

• Connect to language models and structure prompts that actually work
• Process documents and build Retrieval-Augmented Generation (RAG) systems
• Create AI agents that can use tools to take real action, not just generate text
• Add memory so your assistants hold a genuine, multi-turn conversation
• Use LangGraph to build agent workflows with branching, looping, and human approval steps
• Build agentic RAG systems that grade their own retrievals and rewrite failed queries
• Test, debug, and evaluate LLM applications so they behave predictably
• Take a project from a working prototype to something ready for production

Each chapter builds directly on the last, with clear explanations before every line of code, common mistakes flagged before you make them, and a hands-on project to lock in what you've learned. By the final chapter, you'll have built a complete, multi-capability AI assistant from scratch and you'll understand exactly why every piece of it works.

Written for:

• Python developers new to AI application development
• Beginners who want a structured, no-fluff path into LangChain
• Anyone who has tried scattered tutorials and wants one coherent, practical guide

No prior AI or machine learning background required. Just basic Python and a willingness to build.

Stop reading about AI agents. Start building them.