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Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Agentic AI with Langchain & Langgraph: Build Reliable Multi-Agent LLM Systems with Python, RAG Workflows, and Production-Ready Patterns

Agentic AI with Langchain & Langgraph: Build Reliable Multi-Agent LLM Systems with Python, RAG Workflows, and Production-Ready Patterns

Paperback

ISBN13: 9798275093902
Publisher: Independently Published
Published: Nov 18 2025
Pages: 126
Weight: 0.41
Height: 0.27 Width: 6.14 Depth: 9.21
Language: English
Unlock the power of agentic AI and start building systems that think, reason, and collaborate. This practical guide shows you exactly how to design intelligent, reliable, and scalable multi-agent applications using LangChain, LangGraph, and Python. Whether you are a developer, data engineer, researcher, or AI enthusiast, this book gives you the tools and patterns needed to build production-grade LLM systems that deliver real results.

You will learn how to create autonomous agents that can plan, retrieve information, call tools, work together, and execute complex tasks with minimal human intervention. Each concept is explained clearly and supported with step-by-step examples you can use immediately. From designing your first agent to deploying advanced RAG architectures and fault-tolerant workflows, this guide removes the guesswork and puts modern agentic AI in your hands.

Inside this book, you will discover:

1. How agentic AI works and why it is transforming automation, AI engineering, and product development

2. The exact process for building intelligent agents with LangChain, LangGraph, and Python

3. Proven multi-agent patterns, collaboration strategies, and workflow designs that scale in real applications

4. Essential RAG techniques for grounding your agents in reliable, up-to-date information

5. Error handling, memory design, state management, tool calling, routing, and workflow orchestration

6. Architectures that prevent hallucination, reduce failure, and keep agents aligned with your goals

7. Hands-on projects you can build and deploy, including research copilots, AI workflows, knowledge assistants, and autonomous task agents

8. Optimization, monitoring, debugging, and performance best practices for production-ready systems