Building Applications with AI Agents

Chapter 2. Designing Agent Systems

Most practitioners don’t begin with a grand design document when building agent systems. They start with a messy problem, a foundation model API key, and a rough idea of what might help. This chapter is your quick start to get you up and running. We’ll cover each of the following topics in more depth through the rest of the book, and many will get their own chapter, but this chapter will give you an overview of how to design an agentic system, all grounded in a specific example of managing customer support for an ecommerce platform.

Our First Agent System

Let’s start with the problem we’re solving. Every day, your customer-support team fields dozens or hundreds of emails asking to refund a broken mug, cancel an unshipped order, or change a delivery address. For each message, a human agent has to read free-form text, look up the order in your backend, call the appropriate API, and then type a confirmation email. This repetitive two-minute process is ripe for automation—but only if we carve off the right slice. When we realize that humans type keys and click buttons, often following rules and guidelines, we see that many of these same patterns can be performed by well-designed systems that rely on foundation models. We want our agent to take a raw customer message plus the order record, decide which tool to call (issue_refund, cancel_order, or update_​address_for_order), invoke that tool with the correct parameters, and then send a brief confirmation ...