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  • Book Overview & Buying Building Agentic AI Systems
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Building Agentic AI Systems

Building Agentic AI Systems

By : Anjanava Biswas, Wrick Talukdar
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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
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Part 2: Designing and Implementing Generative AI-Based Agents
10
Part 3: Trust, Safety, Ethics, and Applications

Creative and artistic applications

The integration of LLM-based agents in creative fields marks a significant evolution beyond simple generative AI tools. This section explores how agentic systems are transforming creative workflows through their ability to understand context, maintain creative direction, and actively collaborate with human artists. Unlike traditional AI tools that simply generate content, these agents can engage in sustained creative dialogues, adapt to changing requirements, and balance multiple artistic and technical constraints simultaneously.

Evolution of creative and artistic agents

The development of creative and artistic agents represents a paradigm shift in how AI systems contribute to the creative process. Early generative AI tools focused primarily on producing static outputs based on predefined prompts, offering limited interaction and adaptability. Modern agentic systems, however, have evolved to actively participate in dynamic and iterative creative...

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Building Agentic AI Systems
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