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The GitHub Copilot Handbook

You're reading from   The GitHub Copilot Handbook A practical guide to transforming the software development life cycle with GitHub Copilot

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Product type Paperback
Published in Nov 2025
Publisher Packt
ISBN-13 9781806116638
Length 290 pages
Edition 1st Edition
Tools
Concepts
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Authors (2):
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Rob Bos Rob Bos
Author Profile Icon Rob Bos
Rob Bos
Randy Pagels Randy Pagels
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Randy Pagels
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Table of Contents (18) Chapters Close

Preface 1. What is GitHub Copilot?
2. GitHub Copilot Explained FREE CHAPTER 3. Getting Started with Generative AI 4. Choosing the Right GitHub Copilot Plan 5. Getting Started with GitHub Copilot
6. Mastering GitHub Copilot in Your IDE: Inline Suggestions, Chat, and Agent Mode 7. Going Beyond Code: Debugging, Terminal, and Collaboration with GitHub Copilot 8. Exploring GitHub Copilot Integrations
9. Collaborating with Copilot on GitHub.com: Issues, PRs, Reviews, and Coding Agent 10. Extending GitHub Copilot with the Model Context Protocol (MCP) 11. Getting the Most Out of GitHub Copilot
12. Navigating the GitHub Copilot Learning Curve 13. Building an Internal GitHub Copilot Community 14. Changing the Narrative: Reframing Engineering with AI 15. Unlock Your Exclusive Benefits 16. Other Books You May Enjoy
17. Index

Getting Started with Generative AI

Before we dive into the features and applications of GitHub Copilot, we want to make sure you have a basic understanding of the underlying technology. Having a grasp on the mechanics of generative AI gives you a solid foundation to have realistic expectations of what these tools can do for you and where they shine and where they have shortcomings. This understanding prevents disappointment when the technology doesn’t deliver the value you might have been expecting, something we have seen during the many training sessions and hackathons we have delivered. It also sets the right context for the things generative AI does not work so well with, as there are definitely some rough edges in its current state.

However, keep in mind that things are evolving fast, because the models, our understanding of working with models, and chaining features together, are all improving over time. This field has been rapidly accelerating over the last few years...

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