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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

Multi-Agent Applications

Until now, we’ve explored how to build powerful single-agent systems—intelligent entities that leverage tools, knowledge, memory, and orchestration layers to solve complex tasks. These agents can be highly capable when properly configured, drawing on vast knowledge and integrations to act independently. However, the true potential of agentic systems begins to unfold when we move beyond the solitary agent.

Just as humans rely on teams with diverse roles and expertise, AI systems can benefit immensely from having multiple agents working in tandem, each with its own specialization, perspective, or function.

This chapter explores how agents can communicate, coordinate, and cooperate to complete tasks that would be difficult—or even impossible—for a single agent to handle alone. In this chapter, we will cover the following topics:

  • Introduction to multi-agent systems
  • Understanding and designing different workflows...
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AI Agents in Practice
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