Agentic System Development

About the Book

"Agentic System Development" is a comprehensive, practical-oriented textbook designed to guide undergraduate (B.Tech) and postgraduate (M.Tech) computer science students, as well as aspiring AI developers, through the principles, design, and implementation of autonomous agentic systems.


Philosophy

The core philosophy of this book is "Learning by Doing." I believe that the most profound understanding of complex systems comes from building them from the ground up. This book systematically demystifies agentic AI by breaking it down into manageable, understandable, and implementable parts. It deliberately prioritizes practical application, demonstrable skills, and real-world relevance over dense, abstract theory. Every concept is introduced with the ultimate goal of its application, ensuring that the reader is not just a passive consumer of information but an active creator of technology.


Key Features

1. Practical First Approach: Heavy emphasis on implementation, coding, and deployment over theoretical discourse.
2. Beginner Friendly: Assumes no deep prior expertise in agent theory. Algorithms and code are kept simple and are well-commented.
3. End-to-End Coverage: Uniquely covers the entire lifecycle of agent development: from initial design and architecture to component implementation, multi-agent coordination, deployment, and future trends.
4. Modern Tooling: Incorporates the latest and most relevant industry-standard frameworks and libraries (e.g., LangChain, AutoGen) for building LLM-powered agents.
5. Real-World Case Studies: Includes case studies on systems like personalized recommendation agents, automated trading bots, and smart home controllers to illustrate concepts in action.
6. Complete Capstone Project: A full, working project with step-by-step code and explanations provides an invaluable portfolio piece for students.


To Whom This Book Is For

1. B.Tech and M.Tech Computer Science Students: It serves as a primary textbook for courses on Artificial Intelligence, Intelligent Systems, Multi-Agent Systems, and Software Engineering.
2. Aspiring AI/ML Developers: Professionals and enthusiasts who want to transition from traditional software or data science roles into the cutting-edge field of agentic AI.
3. Software Engineers and Architects: Individuals looking to understand how to design and integrate autonomous components into their existing or new software systems.
4. Academic Researchers and Educators: A practical guide for teaching and for setting up lab-based courses on intelligent agent development.