Generative Agentic AI

De: Ajit Singh

Narrado por: Virtual Voice

"Generative Agentic AI" is a comprehensive textbook and practical guide designed to navigate the exciting confluence of generative AI and autonomous agent technology. It systematically demystifies how we can empower Large Language Models (LLMs) and other foundation models to not only generate content but to actively reason, plan, and execute complex tasks in both digital and physical environments. This book bridges the gap between theoretical knowledge and practical implementation, making it an essential resource for the next generation of AI engineers and developers.


Key Features:


1. Beginner to Advanced Progression: The 10-chapter structure ensures a smooth learning curve, starting from "What is an Agent?" and progressing to deploying complex multi-agent systems.
2. Hands-On Practicals: Every chapter is packed with code examples, practical tutorials, and labs using popular frameworks like LangChain, LlamaIndex, and AutoGen.
3. Real-World Case Studies: Explore how agentic AI is being used in real applications, from automated software engineering and scientific research to personalized customer support.
4. Complete Capstone Project: The final chapter guides you step-by-step through building a complete, live DIY project—an AI Research Assistant—consolidating all the concepts learned throughout the book.
5. Simple and Explanatory Language: Complex architectural concepts are broken down into simple, easy-to-understand terms with clear diagrams and analogies.
6. Focus on Design and Architecture: Learn not just how to code an agent, but how to design a robust, scalable, and efficient agentic system from the ground up.



To Whom is This Book For?


This book is tailored for a wide audience, covering the needs of both beginners and advanced learners:

1. B.Tech/M.Tech Computer Science Students: The content is strictly aligned with the AICTE model curriculum and NEP 2020 guidelines, making it a perfect textbook for undergraduate and postgraduate courses on Artificial Intelligence, Machine Learning, and Intelligent Systems.
2. Aspiring AI/ML Engineers: For those looking to build a career in AI, this book provides the practical, hands-on skills required for roles involving the development of AI agents, chatbots, and autonomous systems.
3. Software Developers & Professionals: Developers seeking to upskill and integrate agentic AI capabilities into their applications will find this book an invaluable practical guide.
4. Researchers and Academics: The book serves as a strong foundation for those interested in exploring advanced research topics in agentic AI, including reasoning, planning, and multi-agent collaboration.


As you turn these pages, you are not just learning a subject; you are acquiring the skills to build the future. The concepts within this book—planning, tool use, self-correction, and multi-agent collaboration—are the very principles that will define the next generation of software, services, and human-computer interaction.