Adding Logs to the Agent › Adding Logs to the Agent

When you build an AI agent, you're creating something that makes decisions on its own. It decides when to use tools, how to reason through problems, and what information to retrieve from memory. This autonomy is powerful, but it also means you can't always predict what the agent will do. Sometimes it works perfectly. Other times, it gives an unexpected answer or calls the wrong tool. When that happens, you need a way to understand what went wrong.

This is where logging comes in. By adding logs at key decision points in your agent's code, you create a trail of breadcrumbs showing exactly what the agent did and why. Think of it like keeping a lab notebook during an experiment. Without notes, you won't remember what worked and what didn't. With good notes, you can trace back through every step and spot the problem.

Let's see how to add logging to our personal assistant so we can peer inside its decision-making process.