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AI Agents in Practice

AI Agents in Practice

By : Valentina Alto
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AI Agents in Practice

AI Agents in Practice

5 (1)
By: Valentina Alto

Overview of this book

As AI agents evolve to take on complex tasks and operate autonomously, you need to learn how to build these next-generation systems. Author Valentina Alto brings practical, industry-grounded expertise in AI Agents in Practice to help you go beyond simple chatbots and create AI agents that plan, reason, collaborate, and solve real-world problems using large language models (LLMs) and the latest open-source frameworks. In this book, you'll get a comparative tour of leading AI agent frameworks such as LangChain and LangGraph, covering each tool's strengths, ideal use cases, and how to apply them in real-world projects. Through step-by-step examples, you’ll learn how to construct single-agent and multi-agent architectures using proven design patterns to orchestrate AI agents working together. Case studies across industries will show you how AI agents drive value in real-world scenarios, while guidance on responsible AI will help you implement ethical guardrails from day one. The chapters also set the stage with a brief history of AI agents, from early rule-based systems to today's LLM-driven autonomous agents, so you understand how we got here and where the field is headed. By the end of this book, you'll have the practical skills, design insights, and ethical foresight to build and deploy AI agents that truly make an impact.
Table of Contents (15 chapters)
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1
Part 1: Foundations of AI Workflows and the Rise of AI Agents
4
Part 2: Designing, Building, and Scaling AI Agents
10
Part 3: Road to an Open, Agentic Ecosystem
14
Index

The Need for Tools and External Integrations

As we mentioned in the preceding chapters, one of the key features and differentiations of AI agents is that they can interact with the world. While LLMs can understand, reason, and generate text, they are ultimately limited by what exists within their training data and current context window. To go beyond passive conversation and perform real, useful actions—such as booking appointments, querying databases, retrieving live information, or executing multi-step workflows—AI agents must be equipped with tools.

Tools are the functional extensions of an agent’s intelligence. They allow agents to call APIs, access external systems, retrieve fresh data, and even manipulate structured knowledge bases.

Throughout this chapter, we will cover the following topics:

  • The anatomy of an AI agent’s tools
  • Hardcoded and semantic functions
  • APIs and web services
  • Databases and knowledge bases
  • ...
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AI Agents in Practice
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