AI-Agents-in-Practice
AI Agents in Practice, published by Packt
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AI Agents in Practice, First Edition
This is the code repository for AI Agents in Practice, First Edition, published by Packt.
Design, Implement, and Scale Autonomous AI Systems for Production
Valentina Alto
About the book
In an era where AI agents are expected to operate autonomously and tackle complex tasks, AI Agents in Practice is your roadmap to building these next-generation systems. This book helps you go beyond simple chatbots and create AI agents that plan, reason, collaborate, and solve real-world problems using large language models and the latest open-source frameworks. You'll get a comparative tour of leading AI agent frameworks like LangChain and LangGraph, covering each tool's strengths, ideal use cases, and how to apply them in real projects. Through step-by-step examples, learn to construct single-agent and multi-agent architectures using proven design patterns to orchestrate AI agents working together. Case studies across industries show AI agents driving value in real scenarios, while guidance on responsible AI helps you implement ethical guardrails from day one. AI Agents in Practice also sets 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, you'll have the practical skills, design insights, and ethical foresight to build and deploy AI agents that truly make an impact.
Key Learnings
- Master core agent components like LLMs, memory systems, tool integration, and context management
- Build production-ready AI agents using frameworks like LangChain with code
- Create effective multi-agent systems using orchestration patterns for problem-solving
- Implement industry-specific agents for e-commerce, customer support, and more
- Design robust memory architectures for agents with short and long-term recall
- Apply responsible AI practices with monitoring, guardrails, and human oversight
- Optimize AI agent performance and cost for production environments
Chapters
Requirements for this book
Here is a list of things you need to have:
| Software/hardware covered in the book | System requirements |
|---|---|
| Python 3.10 or higher | Windows, macOS, or Linux |
| Node.js | Windows, macOS, or Linux |
| LLM chat and embedding models | Windows, macOS, or Linux You can decide to leverage your LLM of choice. Throughout the book, we will be using GPT-4o from Azure OpenAI or OpenAI. Other options include (but are not limited to) the following: • Hugging Face Hub • Anthropic • Gemini |
Get to know Authors
Valentina Alto 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.
Collected info
- ★ 116 stars
- ⎇ 60 forks
- Language: Jupyter Notebook
- Source updated: 9/21/2026

