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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

Planning algorithms for agents

Planning is a fundamental capability of intelligent agents, enabling them to reason about their actions and devise strategies to achieve their objectives effectively. Planning algorithms form the backbone of how LLM agents determine and sequence their actions. An algorithm is a step-by-step set of instructions or rules designed to solve a specific problem or complete a task. It is a sequence of unambiguous and finite steps that takes inputs and produces an expected output in a finite amount of time.

There are several planning algorithms in AI, each with its own strengths and approaches. However, when working with LLM agents, we need to consider their practicality in handling natural language, uncertainty, and large state spaces (all possible situations or configurations that an agent might encounter during its task). For example, in a simple robot navigation task, state spaces might include all possible positions and orientations, but in LLM agents...

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Building Agentic AI Systems
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