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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

Importance of trust in AI

Trust constitutes a key ingredient for the successful adoption and acceptance of AI systems in general, including generative AI. If users lack confidence in the inner workings and decision-making processes of this new technology, it’s highly doubtful that they will be willing to use or rely on its outputs. Building up trust in generative AI systems is an essential step toward gaining user confidence and ensuring that its use is widespread, responsible, and ethical.

Consider a scenario where a travel agency employs a generative AI system to assist customers in planning their vacations. The AI can suggest personalized itineraries, recommend accommodations, and provide travel tips based on the customer’s preferences and historical data. However, if customers do not trust the AI’s recommendations, they are unlikely to rely on its suggestions or share personal information necessary for tailoring the recommendations.

This means that trust...

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Building Agentic AI Systems
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