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AI Agents in Practice
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In the previous chapters, we explored the theory behind AI agents—their architecture, the role of tools, memory, and planning, and how frameworks such as LangChain make it possible to orchestrate these components. Now, it’s time to move from theory to practice.
In this chapter, we’ll walk through the process of building your first AI agent using LangChain. We’ll do so through a practical use case: an e-commerce assistant for a digital piadineria. From understanding the scenario and assembling the core building blocks to developing and evaluating the agent’s performance, you’ll gain hands-on experience with LangChain’s capabilities. You’ll also explore how to trace and observe agent behavior using tools such as LangSmith, and finally, how to extend this assistant into a mobile experience.
We will cover the following topics: