Design, implement, and scale autonomous AI systems for production
Valentina Alto

#AI
#LLM
#GenAI
Master the art of building AI agents with this hands-on guide to orchestration, multi-agent systems, real-world case studies, and ethical insights to drive immediate business impact
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.
This book is ideal for AI engineers and data scientists looking to move beyond basic LLM implementations to build sophisticated autonomous agents. Software developers and system architects will find practical guidelines for integrating agents into existing tech stacks. Product managers and technical entrepreneurs will gain strategic insights into how AI agents can solve business problems across industries. A basic understanding of machine learning concepts and working knowledge of Python are required to make the most of this book and implement production-ready AI agent systems.
Part 1: Foundations of AI Workflows and the Rise of AI Agents
Chapter 1: Evolution of GenAI Workflows
Chapter 2: The Rise of AI Agents
Part 2: Designing, Building, and Scaling AI Agents
Chapter 3: The Need for an AI Orchestrator
Chapter 4: The Need for Memory and Context Management
Chapter 5: The Need for Tools and External Integrations
Chapter 6: Building Your First AI Agent with LangChain
Chapter 7: Multi-Agent Applications
Part 3: Road to an Open, Agentic Ecosystem
Chapter 8: Orchestrating Intelligence: Blueprint for Next-Gen Agent Protocols
Chapter 9: Navigating Ethical Challenges in Real-World AI
Valentina Alto is a technical architect specializing in AI and intelligent apps at Microsoft Innovation Hub in Dubai. During her tenure at Microsoft, she covered different roles as a solution specialist, focusing on data, AI, and applications workloads within the manufacturing, pharmaceutical, and retail industries and driving customers' digital transformations in the era of AI. Valentina is an active tech author and speaker who contributes to books, articles, and events on AI and machine learning. Over the past two years, Valentina has published two books on generative AI and large language models, further establishing her expertise in the field.









