Problem statement

Modern developers often face repetitive tasks, scattered documentation, and the mental load of switching between tools just to stay productive. Writing boilerplate code, understanding unfamiliar code bases, or debugging small issues can consume valuable time and focus. In this chapter, we address that problem by introducing a practical solution: building an AI-powered code assistant using Mistral and Codestral. By integrating these models into your coding workflow, you’ll learn how to accelerate development, reduce context switching, and enhance code understanding, all within your editor.

Let us jump into our first trail and explore how to engage directly with our code using natural language. We’ll use the RAG approach from Chapter 6 to semantically analyze a GitHub repository. This enables us to ask meaningful questions, such as uncovering class hierarchies or figuring out how to instantiate an agent.