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Supercharged Coding with GenAI

You're reading from   Supercharged Coding with GenAI From vibe coding to best practices using GitHub Copilot, ChatGPT, and OpenAI

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Product type Paperback
Published in Aug 2025
Last Updated in Sep 2025
Publisher Packt
ISBN-13 9781836645290
Length 460 pages
Edition 1st Edition
Languages
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Authors (2):
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Hila Paz Herszfang Hila Paz Herszfang
Author Profile Icon Hila Paz Herszfang
Hila Paz Herszfang
Peter V. Henstock Peter V. Henstock
Author Profile Icon Peter V. Henstock
Peter V. Henstock
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Foundations for Coding with GenAI FREE CHAPTER
2. From Automation to Full Software Development Life Cycle: The Current Opportunity for GenAI 3. Your Quickstart Guide to OpenAI API 4. A Guide to GitHub Copilot with PyCharm, VS Code, and Jupyter Notebook 5. Best Practices for Prompting with ChatGPT 6. Best Practices for Prompting with OpenAI API and GitHub Copilot 7. Part 2: Basics to Advanced LLM Prompting for GenAI Coding
8. Behind the Scenes: How ChatGPT, GitHub Copilot, and Other LLMs Work 9. Reading and Understanding Code Bases with GenAI 10. An Introduction to Prompt Engineering 11. Advanced Prompt Engineering for Coding-Related Tasks 12. Refactoring Code with GenAI 13. Fine-Tuning Models with OpenAI 14. Part 3: From Code to Production with GenAI
15. Documenting Code with GenAI 16. Writing and Maintaining Unit Tests 17. GenAI for Runtime and Memory Management 18. Going Live with GenAI: Logging, Monitoring, and Errors 19. Architecture, Design, and the Future 20. Other Books You May Enjoy 21. Index
Appendix

Introducing GitHub Copilot – our AI pair programmer

GitHub Copilot is an AI-powered tool that uses LLMs trained on vast and diverse datasets containing a significant amount of open source code from public repositories across various programming languages, including Python. By combining the model’s extensive knowledge with your code’s context, GitHub Copilot provides tailored coding suggestions, as well as chat and code analysis features, to assist in your development process.

Code completion design overview

To provide meaningful code completions, Copilot processes the input and output of the LLM, like the code completion program developed in Lab 2.3. For the input, Copilot structures a prompt based on the lines surrounding the cursor, function signatures, and additional context, such as recent edits, Git details, file names and open files. The LLM’s output is further processed, including validation to ensure it compiles successfully.

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