GitHub Copilot and AI Coding Tools in Practice: Accelerate AI Adoption from Individual Developers to Enterprise

GitHub Copilot and AI Coding Tools in Practice: Accelerate AI Adoption from Individual Developers to Enterprise book cover

GitHub Copilot and AI Coding Tools in Practice: Accelerate AI Adoption from Individual Developers to Enterprise

Author(s): Nick Wienholt (Author)

  • Publisher: Apress
  • Publication Date: September 27, 2025
  • Edition: First Edition
  • Language: English
  • Print length: 352 pages
  • ISBN-10: B0FF979LBV
  • ISBN-13: 9798868817830

Book Description

Learn the current state of generative AI coding tools like GitHub Copilot, what the underlying models mean, and how to use them across the full development life-cycle. Look ahead to the near future of AI-generated software and understand how software developers can stay relevant in the industry.

Many companies have predicted that human coders will soon be redundant due to AI-generated code, but there is a big gap between the expectations and what is actually happening on the ground. A closer look at the current state of the tools and research in this area will offer realism and guidance to developers worried regarding redundancy.

Close the gap between hype and practical applications by receiving context and clear technical information on usage, understanding, and deployment of these tools.

What You Will Learn:

  • How to use coding and software AI tools
  • How software AI tools work
  • How software AI tools fit in an industry context
  • How to use AI tools across the SDLC – it’s more than just faster coding

Who This Book is For

All software industry participants interested in mastering AI-generated code.

Editorial Reviews

From the Back Cover

Learn the current state of generative AI coding tools like GitHub Copilot, what the underlying models mean, and how to use them across the full development life-cycle. Look ahead to the near future of AI-generated software and understand how software developers can stay relevant in the industry.

Many companies have predicted that human coders will soon be redundant due to AI-generated code, but there is a big gap between the expectations and what is actually happening on the ground. A closer look at the current state of the tools and research in this area will offer realism and guidance to developers worried regarding redundancy.

Close the gap between hype and practical applications by receiving context and clear technical information on usage, understanding, and deployment of these tools.

What You Will Learn:

  • How to use coding and software AI tools
  • How software AI tools work
  • How software AI tools fit in an industry context
  • How to use AI tools across the SDLC – it’s more than just faster coding

About the Author

Nick Wienholt is a Sydney-based software engineer with more than 25 years of experience in the design and implementation of large-scale software systems, and has spent the last decade focused on development in the data science and AI space. He has a strong track record of delivery across a variety of financial and e-commerce systems, having consulted and worked with a large number of major corporate and propriety trading firms across Australia, and has been a keen user and advocate of ML/AI tools to accelerate development since their release.

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