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

ISBN-13: 978-1803238753, ISBN-10: 1803238755

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Book details

ISBN-10

1803238755
ISBN-13

978-1803238753
Publisher

Packt Publishing
Publication date

April 21, 2025
Language

English
Dimensions

7.5 x 0.65 x 9.25 inches
Print length

288 pages

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Master the art of building AI agents with large language models using the coordinator, worker, and delegator approach for orchestrating complex AI systems

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
Purchase of the print or Kindle book includes a free PDF eBook

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.

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

Review

“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 of Forbes Technology Council

About the Author

Anjanava Biswas is an award-winning senior AI specialist solutions architect with over 17 years of industry experience. Specializing in machine learning, Generative AI, natural language processing, deep learning, data analytics, and cloud architecture, he partners with large enterprises to build and scale advanced AI systems in the cloud. Anjanava is widely recognized for his contributions to the field of applied AI. He has published research in multiple scientific journals and actively contributes to open-source AI/ML projects. His professional accolades include Fellowships with BCS (UK), the IET (UK), and IETE (India), and he is a senior IEEE member. A frequent public speaker, Anjanava has held key positions at industry giants like IBM and Oracle Corp. Originally from India, he now resides in San Diego, CA, with his wife and son, where he continues to innovate and inspire within the tech community.

Wrick Talukdar is a visionary technology leader in generative artificial intelligence (AI) at Amazon, with over two decades of global experience in AI, cloud computing, and product leadership. A pioneer in AI-driven transformation, he has led large-scale modernization initiatives that drive enterprise growth and impact millions worldwide. He has spearheaded the productization of award-winning AI/ML technologies, now deployed at scale for Fortune 500 companies, shaping real-world AI applications. A recognized figure in AI research, Wrick's work in generative AI, multimodality, natural language processing, and computer vision is widely cited and referenced in the field. As a senior IEEE member, Chair, and panelist in multiple industry forums, he advises global committees like CTSoc Industry Forums and NIC, setting industry standards and shaping AI's role for the future. He frequently presents his innovations at premier conferences such as World Technology Summit, IEEE HKN, ICCE, CERAWeek, and ADIPEC, bridging cutting-edge research with real-world AI applications to accelerate industry-wide innovation. Deeply rooted in his computer science background, he co-chairs IEEE NIC to empower young professionals. As an author and thought leader, he continues to push AI's boundaries, inspiring future innovators. Wrick lives in California with his family.

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Wrick Talukdar

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Wrick is a distinguished AI/ML architect and product leader with over two decades of experience driving technological transformations in global enterprises. Renowned for his expertise in AI, Machine Learning, and Cloud Computing, he has consistently leveraged cutting-edge technologies to deliver strategic business value for customers all over the globe.

Throughout his career, Wrick has led digital initiatives that drive significant cost savings and accelerate time-to-market. He has a proven track record of building high-performance teams that deliver innovative AI products and solutions.

As a strategic thinker, Wrick excels in aligning technology with business goals, fostering cross-functional collaboration, and addressing complex challenges with data-driven approaches. His ability to bridge technical expertise with business vision positions him as a key leader in driving sustainable growth and innovation.

Beyond his professional achievements, Wrick has made a lasting impact on the global scientific community, with his research and innovation widely referenced and cited worldwide. He is a keynote speaker

He serves as Chair of IEEE ICGC, is a Senior Member of IEEE, and holds the role of Chief AI/ML Architect for Generative AI Initiatives within the IEEE Industry Engagement Committee (IEC), where he empowers young professionals(YPs) to advance their careers through technology and generative AI. Additionally, as a Senior Member and Advisor of the Consumer Technology Society (CTSoc), he plays a key role in shaping technology standards and provides strategic guidance on major global symposiums, including prestigious conferences like ICCE, Global Technology Summit, IEEE HKN, etc. He is a frequent speaker at world-class conferences such as ADIPEC, CERAWeek, AWS re:Invent, and other global forums, where he shares his latest innovations, solutions, and research in AI and emerging technologies.

When he's not working on cutting-edge AI systems, Wrick is passionate about photography, writing, and sketching portraits. He believes that the real world reveals itself in expressions — a truth he captures through his lens, pen and pencil alike. Wrick lives in California with his family and enjoys exploring the world, one story, one sketch, and one frame at a time.

Anjanava Biswas

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Anjanava Biswas is an award-winning senior AI specialist solutions architect with over 17 years of industry experience. Specializing in machine learning, generative AI, natural language processing, deep learning, data analytics, and cloud architecture, he partners with large enterprises to build and scale advanced AI systems in the cloud. Anjanava is widely recognized for his contributions to the field of applied AI. He has published research in multiple scientific journals and actively contributes to open-source AI/ML projects. His professional accolades include Fellowships with BCS (UK), the IET (UK), IETE (India), and he is a senior IEEE member. A frequent public speaker, Anjanava has held key positions at industry giants like IBM and Oracle Corp. Originally from India, he now resides in San Diego, CA, with his wife and son, where he continues to innovate and inspire within the tech community.

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Interview with the author - Anjanava Biswas

Interview with the author - Wrick Talukdar

Interview with the authors - Anjanava Biswas and Wrick Talukdar

Product information

Publisher	Packt Publishing
Publication date	April 21, 2025
Language	‎English
Print length	288 pages
ISBN-10	1803238755
ISBN-13	978-1803238753
Item Weight	‎1.1 pounds
Dimensions	7.5 x 0.65 x 9.25 inches
Best Sellers Rank	#13,901 in Books (See Top 100 in Books) #2 in Artificial Intelligence (Books) #10 in Natural Language Processing (Books) #33 in Artificial Intelligence & Semantics
Customer Reviews	4.5 out of 5 stars 21Reviews

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Tiny
Must-Read for anyone Using or Building AI
Reviewed in the United States on May 3, 2025
Format: Paperback

We all know AI is the hottest thing going, and Agentic AI is the next step, if you haven’t spent any time reading about this fascinating field, I’ve got just the book for you. In Building Agentic Systems, Anjanava Biswas and Wrick Talukdar deliver a pragmatic and...

We all know AI is the hottest thing going, and Agentic AI is the next step, if you haven’t spent any time reading about this fascinating field, I’ve got just the book for you. In Building Agentic Systems, Anjanava Biswas and Wrick Talukdar deliver a pragmatic and technically grounded guide to the next frontier in artificial intelligence: the integration of generative AI with autonomous, goal-driven agents. This excellent work is not a philosophical tome; it’s a toolbox.The text offers lucid explanations, actionable code samples, and layered conceptual depth to bridge the widening gap in the AI ecosystem: how to move from foundation models to fully agentic systems. The book has three sections—each distilling the what, how, and why of building agents that can reason, act, and improve. Recommended for anyone working any aspects of technology that either use AI today, or are planning to in the future, basically, everyone.
The opening section establishes a strong foundation by tracing the evolution of generative models and their integration with agent architectures. It begins a technique overview for approaches like VAE, GAN, and StyleGAN, offering nuanced distinctions such as Beta-VAE’s probabilistic modeling and the structural roles of encoder-decoder variations. Challenges including data bias, privacy, and computational cost are also explored. Next, the text pivots to core agentic system principles—agency, autonomy, and self-governance with a travel agent scenario to illustrate deliberative, reactive, and hybrid architectures as well as multi-agent coordination. The section concludes with an in-depth look at the reasoning and planning mechanisms that underpin intelligent agents, covering logic models, learning types, and planning methods, linked to generative AI as a theory and implementation bridge
The focus then shifts from conceptual foundations to practical implementation, emphasizing constructingt adaptive, tool-using, and modular generative AI agents. It begins with metacognition—framing reflection and introspection as essential, structured capabilities for agents through user engagement and recommendation acceptance metrics. Next up is tool use and planning, emphasizing how LLMs extend functionality with APIs, fallback mechanisms, and hierarchical task networks. The focus is on integrating tools and planning rather than treating tools or agents as isolated components. The Coordinator-Worker-Delegator (CWD) framework for multi-agent systems is introduced to use real-world agent roles to demonstrate modular design, environmental modeling, memory management, and contextual reasoning. Together, these chapters provide a baseline to build scalable and intelligent agentic systems grounded in real code and design practices.
Finally, the book confronts critical issues of trust, safety, and application head-on, grounding them in actionable system design. It starts with user trust as foundational through explainability tools like attention maps and saliency visualizations as essential system features. Ethical and safety considerations are explored as a core architectural concern including covering adversarial defenses, hallucination mitigation, IP risks, and the implementation of rollback, real-time monitoring, and progressive autonomy. Reinforcement learning feedback loops appear as a broader validation framework. The section culminates in a robust treatment of real-world applications, from e-commerce and logistics to creative domains, with an emphasis on technical coordination and implementation. The closing chapter looks toward AGI and multi-modal systems, realistically assessing both current limitations and future potential for experiential learning and generalization beyond memorized responses.
I thoroughly enjoyed the entire book. The graphics are excellent, the explanations are well-reasoned, and the use of a continuing example with the travel agent grounds the reader. I keep trying to think of what might have been an area to improve but this is one of the better systems. If one area fell a little short, it might have been external case-studies about which companies are using Agentic systems and how they achieved success or failure. However, as this is a cutting-edge technology, I can see why these samples are not yet available.

Overall, Building Agentic Systems is more than a timely read—it’s a manual for a future already in progress. Biswas and Talukdar manage to synthesize deep technical insight with practical application, offering a roadmap that spans both vision and execution. Much like Mark Peters’ writing on DevOps and cyberpower, the strength of this book lies in its clarity of mission: to help readers not just understand but build. For developers, architects, and product leaders looking to go beyond prompt engineering into the dynamic territory of generative agents, this is essential reading. Agentic systems are not just coming—they're being built now. If you use AI, build AI, or plan on either, this book is a must-read

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Harsha
Essential Guide for Anyone Building AI Agents Today"
Reviewed in the United States on April 28, 2025
Format: Paperback

TL;DR: "Building Agentic AI Systems" provides a comprehensive roadmap for developing autonomous AI agents that can reason, plan, and adapt. This book bridges theory and practice brilliantly, making complex concepts accessible without sacrificing depth....

TL;DR: "Building Agentic AI Systems" provides a comprehensive roadmap for developing autonomous AI agents that can reason, plan, and adapt. This book bridges theory and practice brilliantly, making complex concepts accessible without sacrificing depth.

Aha! Moments:
The chapter on the Coordinator-Worker-Delegator model was a revelation for me. This framework for organizing multiple agents with distinct roles completely changed how I approach multi-agent system design. Instead of building monolithic agents, I now see the value in specialized roles working in concert.

Another eye-opener was the distinction between mere "tool use" and true "planning" in agent systems. The authors clarify how agents that just call tools are fundamentally different from ones that can strategize and sequence actions toward goals - a distinction I now see everywhere in current AI systems.

Standout Ideas:
The book's approach to "reflection and introspection" in agents is particularly innovative. Rather than treating agents as static systems, the authors demonstrate how they can analyze their own reasoning, learn from experiences, and improve decision-making - making systems that grow smarter over time rather than remaining fixed.

I was also impressed by the practical implementation examples using frameworks like LangGraph, CrewAI, and AutoGen. These concrete demonstrations show how theoretical concepts translate into working code, complete with comparison of different implementation approaches.

Usefulness:
If you're building AI systems that need to move beyond simple prompt-response patterns into truly autonomous behaviors, this book provides both the conceptual foundation and practical techniques needed. It's given me a structured way to think about agent memory architectures, planning algorithms, and multi-agent collaboration that I'm already applying in my work.

I highly recommend this book to AI engineers, AI product managers, and researchers looking to understand where AI is heading as it moves beyond foundation models to truly agentic systems.

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Paul Pollock
Insightful Guide to Building Smarter, Autonomous AI Systems
Reviewed in the United States on May 12, 2025
Format: Paperback

"Building Agentic AI Systems" is an insightful guide for anyone looking to dive into the world of generative AI and autonomous agents. The authors do an excellent job breaking down complex concepts like agentic systems, reflection, introspection, and the...

"Building Agentic AI Systems" is an insightful guide for anyone looking to dive into the world of generative AI and autonomous agents. The authors do an excellent job breaking down complex concepts like agentic systems, reflection, introspection, and the Coordinator-Worker-Delegator (CWD) model into digestible sections. The book provides a strong theoretical foundation while also offering practical examples and Python-based frameworks like CrewAI and LangGraph, which make it accessible for developers and researchers alike.
What I particularly liked was the focus on real-world applications across industries like travel, healthcare, and robotics. The travel agent example, for instance, really brought the CWD model to life, showing how agents can collaborate and adapt to solve complex tasks. The attention to ethical considerations, such as building trust in AI and addressing biases, added a much-needed dimension of responsibility to the technical discussions.
That said, I think some sections could have been streamlined. The extensive technical details, while helpful for advanced readers, might overwhelm beginners looking for a more high-level overview. Also, while the examples are practical, a bit more variety in non-technical use cases would have been nice to showcase the versatility of agentic systems.
Overall, this book is an excellent resource for anyone interested in the intersection of generative AI and autonomous systems. It strikes a great balance between theory and practice, and I can see myself referring back to it as I explore building my own AI systems.

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Brahmananda Reddy
A Clear and Practical Guide to Building AI Agents
Reviewed in the United States on June 3, 2025
Format: Paperback

I appreciated how Building Agentic AI Systems focused more on practical frameworks than hype. The writing is clear, and the visuals make it easier to follow complex agent architectures. I especially liked the chapters on memory, planning, and real-world case studies....

I appreciated how Building Agentic AI Systems focused more on practical frameworks than hype. The writing is clear, and the visuals make it easier to follow complex agent architectures. I especially liked the chapters on memory, planning, and real-world case studies.

What stood out is the distinction between agents and tools — not every system needs to be an agent, and the book makes that nuance easy to understand.

One area that could be improved is the depth in the eval and benchmarking chapters — a bit more on implementation trade-offs would help experienced builders.

Overall, a solid read for anyone working with LLMs and looking to move beyond prompt engineering into structured, multi-step agent design.

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Sai Ch
Great one!
Reviewed in the United States on May 13, 2025
Format: Paperback

Just wrapped up “Building Agentic AI Systems” and it's one of the most practical guides I've read on building intelligent AI agents. 🙌 The book starts by breaking down Generative AI fundamentals, like VAEs, GANs, and Transformers, in a beginner-friendly way....

Just wrapped up “Building Agentic AI Systems” and it's one of the most practical guides I've read on building intelligent AI agents. 🙌
The book starts by breaking down Generative AI fundamentals, like VAEs, GANs, and Transformers, in a beginner-friendly way. It then dives into agentic systems - AI agents that don’t just respond but actually think, plan, reflect, and adapt on their own.
What I loved most is how it connects these concepts to real-world tools. It shows how to build agents that can use tools (like LangChain or AutoGen), collaborate with others in a system (multi-agent setup), and even manage memory and decision-making over time.
There’s a whole section on designing ethical, trustworthy AI - including how to handle bias, data privacy, and adversarial risks - which is super relevant for deploying GenAI responsibly.
The book also includes YAML config examples, CI/CD setups, and practical design patterns that make it easier to move from theory to implementation. If you’re working with LLMs, agent orchestration, or GenAI applications, this is a must-read.

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Ashish Lal
A must-read for AI developers and architects
Reviewed in the United States on April 29, 2025
Format: Paperback

If you like to learn the fundamentals of how to build Agentic systems with generative AI, this is the book to read. From CDW, role based agents, state spaces and complex Agentic flows, this book has it all. It also provides incredibly practical guidance that strikes the...

If you like to learn the fundamentals of how to build Agentic systems with generative AI, this is the book to read. From CDW, role based agents, state spaces and complex Agentic flows, this book has it all. It also provides incredibly practical guidance that strikes the perfect balance between theoretical concepts and hands-on implementation.
The authors clearly explain how to design effective conversational design workflows (CDW) that form the backbone of any robust agentic system. The section on role-based agents was particularly illuminating, demonstrating how different specialized AI agents can collaborate to solve complex problems that single agents struggle with.
What impressed me most was the deep dive into state spaces and how they enable persistent memory and contextual awareness in AI systems. The examples of complex agentic flows show you exactly how to orchestrate multiple agents working together toward common goals.
The code examples are clean, well-commented, and actually work in real-world scenarios. I implemented several of the patterns from the book in my own projects with excellent results.
Whether you're just starting with generative AI or looking to take your agentic systems to the next level, this book provides the solid foundation and advanced techniques you need to succeed in this rapidly evolving field. Highly recommended for anyone serious about building the next generation of AI systems.

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Murugan Lakshmanan
Insightful Guide to Creating Smart AI Agents
Reviewed in the United States on May 6, 2025
Format: Paperback

"Building Agentic AI Systems" by Anjanava Biswas and Wrick Talukdar is a fantastic guide for anyone interested in developing intelligent, autonomous AI systems...the authors strike the perfect balance between theory and practical examples...by making complex topics...

"Building Agentic AI Systems" by Anjanava Biswas and Wrick Talukdar is a fantastic guide for anyone interested in developing intelligent, autonomous AI systems...the authors strike the perfect balance between theory and practical examples...by making complex topics like VAEs, GANs and transformer based models approachable for readers with various levels of expertise. I particularly liked the clear explanations of how these systems can reason, adapt and self-improve. Also, the discussions around ethical considerations, transparency and trust were thoughtful and relevant...highlighting crucial aspects of responsible AI usage. Overall, this book is informative, and highly recommended for AI professionals or anyone looking to deepen their understanding of autonomous intelligent agents.

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pratyush ranjan
Unlock the power of AI agents
Reviewed in the United States on May 12, 2025
Format: Paperback

This comprehensive guide is exactly what I needed to truly grasp how to design AI agents that go beyond simple task execution. The authors are recognized experts in the feild and they did an amazing job explaining 100 level or high level of Gen AI to advanced complex...

This comprehensive guide is exactly what I needed to truly grasp how to design AI agents that go beyond simple task execution. The authors are recognized experts in the feild and they did an amazing job explaining 100 level or high level of Gen AI to advanced complex agents. The authors also give lots of hands on code and real world examples to get started with building your own agents.

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Top reviews from other countries

Thomas Pauly
Verified Purchase
AI-Agent-Fairy-Land
Reviewed in Germany on May 23, 2025

In times when true advise is needed to cut through the hype - this book is extremely either extremely shallow or overstating dramatically ( rather than a grounded description of what LLM-based agents can reliably do today) E.G. - if you believe this is the current state of...

In times when true advise is needed to cut through the hype - this book is extremely either extremely shallow or overstating dramatically ( rather than a grounded description of what LLM-based agents can reliably do today) E.G. - if you believe this is the current state of technology: "A reflective travel agent can introspect on the potential impact of its recommendations and adapt its strategies to align with ethical norms and human values. (p.183)." go ahead - waste your money. I am trying to return it for a few days now - Amazon for what ever reason doesn't let me.

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Kindle Customer
Verified Purchase
Fantastic resource
Reviewed in India on April 23, 2025

So I was waiting for a good book around this topic and finally found one! Really liked the tone of the book and the way authors have explained the topic with examples. fresh perspective on building autonomous systems. All in all- brilliant read.

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