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Build AI Agents with LangGraph and Python is a hands-on crash course that teaches you how to design, implement, and deploy intelligent, memory-enabled agents using LangGraph and Python. If you’re a developer, product builder, or curious technologist who wants to move beyond prompts and build real LLM-powered apps, this book gives you practical patterns, working code, and production-minded advice.
Inside you’ll find step-by-step examples that take you from a minimal hello-world graph to agents with retrieval-augmented generation (RAG), short- and long-term memory, decisioning, and safe tool use. Learn how to model agents as graphs, define typed contracts with Pydantic, integrate vector search, and connect to modern LLM providers – all while keeping systems observable, testable, and auditable.
This book is built for fast learning: compact chapters, copy-ready code, and exercises that give you working results in hours, not months. Whether you’re prototyping a support triage bot, a research assistant, or an automation playbook, you’ll finish with reusable patterns and a clear roadmap for production. Includes a companion GitHub repo with runnable examples.
Stop guessing with prompts – build reproducible, maintainable agents. Start building today.
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