Building Agentic AI Systems
Create intelligent, autonomous AI agents that can reason, plan, and adapt
Published on 21. April 2025
Book
Paperback/Softback
292 pages
978-1-80323-875-3 (ISBN)
Description
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 DescriptionGain 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 forThis 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.
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 DescriptionGain 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 forThis 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.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 16 mm
Weight
550 gr
ISBN-13
978-1-80323-875-3 (9781803238753)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Anjanava Biswas | Wrick Talukdar | Matthew R. Scott
Building Agentic AI Systems
Create intelligent, autonomous AI agents that can reason, plan, and adapt
E-Book
04/2025
Packt Publishing
from
€39.59
Available for download
Persons
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.
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.
Content
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
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