Learning GitHub Copilot

Chapter 1. Foundations

Welcome to Learning GitHub Copilot! I’m excited you’re reading this book and hope you find it useful. AI tools like ChatGPT and AI agents have changed, and will continue to change, how we interact with software applications. GitHub Copilot and similar tools have changed, and will continue to change, how programmers create software applications. Through its ability to take context from existing code or natural language prompts, GitHub Copilot provides a richer and more powerful code-generation capability than any we’ve seen before.

In this book, I’ll help you understand how to use GitHub Copilot’s capabilities—from performing code generation and completion, forming tests, and translating and explaining code, to working with repositories, pull requests, and issues directly in GitHub. You’ll see examples of using Copilot across multiple domains and programming languages. You’ll learn to leverage it to your advantage and craft prompts to get the best results. You’ll even learn how to add your own custom functionality to it. And you’ll understand how it does what it does, including why it sometimes doesn’t provide the results you expect—and how to mitigate those situations.

Some foundational knowledge is required to begin with, though. That’s the purpose of this chapter. I’ll start by explaining GitHub Copilot at a high level. We’ll then explore the key underlying technology, its overall flow, some usage considerations, how it differs from tools like ChatGPT, ...