Building Agentic AI Systems: Create intelligent, autonomous AI agents that can reason, plan, and adapt

Building Agentic AI Systems: Create intelligent, autonomous AI agents that can reason, plan, and adapt

Master the art of building AI agents with large language models using the coordinator, worker, and delegator approach for orchestrating complex AI systems Free with your book: PDF Copy, AI Assistant, and Next-Gen Reader Key Features Understand the foundations and advanced techniques of building intelligent, autonomous AI agents - Learn advanced techniques for reflection, introspection, tool use, planning, and collaboration in agentic systems - Explore crucial aspects of trust, safety, and ethics in AI agent development and applications Book Description Gain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks. Starting with the foundations of GenAI and agentic architectures, you’ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents. Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention. What you will learn Master the core principles of GenAI and agentic systems - Understand how AI agents operate, reason, and adapt in dynamic environments - Enable AI agents to analyze their own actions and improvise - Implement systems where AI agents can leverage external tools and plan complex tasks - Apply methods to enhance transparency, accountability, and reliability in AI - Explore real-world implementations of AI agents across industries Who this book is for This book is ideal for AI developers, machine learning engineers, and software architects who want to advance their skills in building intelligent, autonomous agents. It's perfect for professionals with a strong foundation in machine learning and programming, particularly those familiar with Python and large language models. While prior experience with generative AI is beneficial, the book covers foundational concepts for those new to agentic systems. Table of Contents Fundamentals of Generative AI - Principles of Agentic Systems - Essential Components of Intelligent Agents - Reflection and Introspection in Agents - Enabling Tool Use and Planning in Agents - Exploring the Coordinator, Worker, and Delegator Approach - Effective Agentic System Design Techniques - Building Trust in Generative AI Systems - Managing Safety and Ethical Considerations - Common Use Cases and Applications - Conclusion and Future Outlook “More than a technical reference, this book serves as an essential guide for shaping the future of Generative AI and intelligent agents. It invites researchers, industry leaders, and innovators to actively participate in crafting the next chapter of AI, one that responsibly advances technological boundaries while enriching society. I wholeheartedly endorse this timely and insightful work. I encourage you to delve deep into the chapters that follow, embracing your role as an active contributor to the exciting and evolving frontier in artificial intelligence.” Matthew R. Scott, Chief Technology Officer, Minset.ai “This book delves into the crucial issues of trust, transparency, explainability, and reliability, as well as ethical considerations such as bias and safety. It describes how agentic systems can be personalized and made context aware, and how they can plan and react to the results of their actions. As somebody that has been working on artificial intelligence for decades, I believe this book will be a great resource for students, researchers, and professionals alike, charting a clear path forward in an era profoundly influenced by intelligent systems.” Dr. Alex Acero, Member of the National Academy of Engineering, IEEE Fellow “This isn’t a ‘just prompt it’ playbook, it’s a signal that agentic systems are moving from novelty to necessity. If you’re still calling everything a chatbot, this book might just help to rewire your vocabulary. I’m glad to see others leaning into what’s next; multi-agent systems (MASs) aren’t theoretical anymore, they’re the scaffolding for how real enterprise autonomy will scale.” Doug Shannon, GenAI & Automation Thought Leader at IgniteGTM, Member o