Building Autonomous AI Agents: A Practical Guide to LLMs, RAG, Knowledge Graphs, and Real-World Deployment is the definitive resource for anyone looking to harness the power of AI to build intelligent, self-directed systems. Whether you are a software engineer, data scientist, AI enthusiast, or technology leader, this book provides a hands-on, practical approach to designing autonomous agents that can plan, reason, and act in complex environments.Inside this book, you will discover how to leverage Large Language Models (LLMs) to drive decision-making, design robust retrieval-augmented generation (RAG) pipelines, and integrate knowledge graphs for superior context and reasoning. You'll learn step-by-step how to construct modular agent architectures, orchestrate multi-agent systems, and deploy fully functional AI agents in real-world scenarios. Each chapter combines detailed explanations, practical examples, and expert insights, guiding you from foundational concepts to advanced implementation techniques.By reading this book, you will gain the skills to: Build autonomous agents capable of completing complex tasks with minimal supervision.Enhance the reliability and accuracy of AI-driven decision-making.Design intelligent systems that can interact seamlessly with external APIs, databases, and tools.Scale AI solutions from prototypes to production-ready deployments.Every concept is presented with clarity and actionable guidance, ensuring that by the end of this book, you are not just familiar with the theory of autonomous agents, you are ready to implement them effectively.If you've been searching for a single, comprehensive guide that demystifies the creation of intelligent agents and shows exactly how to turn advanced AI techniques into practical applications, this is the book you need. Your journey to mastering autonomous AI systems starts here, and the solutions you've been seeking are now within reach.