About this ebook
This book begins with the fundamentals of Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), embeddings, vector databases, and LangChain. It then introduces LangGraph, a powerful framework for building stateful, multi-step AI workflows and intelligent agents. Readers will learn how to create AI systems that can make decisions, execute conditional workflows, maintain memory, collaborate with multiple agents, integrate external tools, and automate complex business processes.
Packed with practical examples, diagrams, projects, and source code, this book demonstrates how to build production-ready Agentic AI applications using Python and the latest AI technologies. Each chapter focuses on real-world implementation, enabling readers to gain practical experience rather than just theoretical knowledge.
Whether you are developing AI assistants, customer support systems, research agents, coding assistants, document intelligence solutions, or enterprise automation platforms, this book provides the concepts and hands-on guidance needed to build intelligent AI applications from scratch.
What You Will Learn
Fundamentals of Generative AI and Large Language Models (LLMs)
Prompt Engineering techniques for better AI responses
LangChain architecture and core components
Embeddings, Vector Databases, and Semantic Search
Retrieval-Augmented Generation (RAG)
Text Chunking and Document Processing
Memory and Conversation Management
LangGraph architecture and execution model
StateGraph, Nodes, Edges, and Conditional Workflows
Parallel, Sequential, and Iterative AI Workflows
Checkpointing and Persistence in LangGraph
Human-in-the-Loop AI Systems
Multi-Agent Collaboration using LangGraph
AI Tool Calling and Function Execution
Planning, Reasoning, Reflection, and Agent Orchestration
Building Autonomous AI Agents
AI Guardrails and Safety
Integrating APIs, Databases, and External Tools
Deploying Production-Ready Agentic AI Applications
Best Practices, Performance Optimization, and Real-World Projects
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About the author
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.
