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Building Agentic AI Systems

Building Agentic AI Systems

By : Anjanava Biswas, Wrick Talukdar
4 (1)
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Building Agentic AI Systems

Building Agentic AI Systems

4 (1)
By: Anjanava Biswas, Wrick Talukdar

Overview of this book

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.
Table of Contents (18 chapters)
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Part 1: Foundations of Generative AI and Agentic Systems
5
Part 2: Designing and Implementing Generative AI-Based Agents
10
Part 3: Trust, Safety, Ethics, and Applications

Integrating tool use and planning

Most of the earlier work in AI planning and tool usage was done in isolation, focusing on either planning algorithms or tool capabilities separately. However, to achieve truly intelligent agents, there is a need to integrate tool use with planning effectively. As we already saw in the previous section, our travel planner gave us a detailed travel plan but none of the details were factual – that is, it contained information that the LLM simply made up. In order to infuse our system with actual flight, hotel, and activity data so that the travel plan is grounded in facts, we will need to utilize tools along with the planning algorithm. This section will discuss how to combine these two aspects to generate relevant responses and complete tasks accurately.

Reasoning about tools

Agents need the ability to reason about the available tools at their disposal, understanding the functionality, capabilities, and limitations of each tool, as well...

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Building Agentic AI Systems
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