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Unlike traditional LLM applications, LangGraph enables developers to create AI systems that can reason across multiple steps, maintain conversation state, use memory, execute conditional workflows, collaborate through multiple agents, and interact with humans during execution. Built on top of the LangChain ecosystem, LangGraph provides a graph-based orchestration framework for developing reliable and scalable AI applications.
Inside this book, you will learn:
Introduction to LangGraph and Agentic AI
Understanding Graph-Based AI Workflows
Installing and Configuring LangGraph
State Management and Shared Memory
Nodes, Edges, START, and END
Building Sequential, Conditional, and Cyclic Workflows
Parallel Execution and Dynamic Routing
Reducers and State Updates
Persistence and Checkpointing
Human-in-the-Loop Workflows
Streaming Responses and Event Handling
Multi-Agent Architectures
Tool Calling and External API Integration
Retrieval-Augmented Generation (RAG) with LangGraph
Long-Term and Short-Term Memory
Error Handling and Debugging
LangSmith Integration for Monitoring
Building AI Assistants and Autonomous Agents
End-to-End Real-World Projects
Best Practices for Production Deployment
Every chapter includes clear explanations, architecture diagrams, source code examples, practical exercises, interview questions, and real-world implementation scenarios. Whether you are creating AI chatbots, enterprise assistants, autonomous workflows, or intelligent automation systems, this book equips you with the knowledge and skills needed to build reliable AI agents.
By the end of this book, you will be able to design, develop, and deploy sophisticated AI agent systems capable of reasoning, planning, remembering context, using tools, collaborating with other agents, and solving complex real-world problems using LangGraph.
Whether you are a beginner entering the world of Generative AI or an experienced developer looking to build advanced AI agent applications, LangGraph is your complete guide to mastering modern AI workflow orchestration.
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Arvind Choudhary is an experienced Software Developer, Corporate Trainer, and Technology Mentor from India with around 12 years of professional experience in the IT industry. He has worked extensively for 8 years as a developer and 4 years as a corporate trainer, helping students, professionals, and organizations build strong technical skills in modern software technologies.
He specializes in Java Full Stack Development, Python Full Stack Development, MERN Stack, Flutter, Android Development, Artificial Intelligence (AI), Machine Learning (ML), Generative AI, Agentic AI, AI Agents, and Android Firmware Development.
Throughout his career, Arvind Choudhary has trained and mentored numerous students and working professionals through live projects, practical implementation, industry-focused training, and real-world application development. His teaching approach focuses on simplifying complex technical concepts into easy-to-understand practical learning experiences.
As an author and trainer, he is passionate about sharing knowledge in emerging technologies including Generative AI, AI Automation, Prompt Engineering, Large Language Models (LLMs), and modern software engineering practices. His goal is to help learners become industry-ready developers and technology innovators.
Arvind Choudhary continues to contribute to the technology community through technical training, content creation, software development, and educational initiatives focused on next-generation technologies.
