Book
Generative AI for Software Development
Sergio Pereira
Summary
Sergio Pereira tested as many AI development tools as he could find and wrote this to give practitioners a way to evaluate them instead of chasing whichever tool is loudest that week. The book moves chapter by chapter through where generative AI actually gets used in a development workflow: code generation and autocomplete, UI and UX design, bug detection and code review, automated testing, predictive performance work, documentation, and chat-based assistants, closing with case studies of teams that adopted these tools successfully. It doesn't assume a machine learning background, and each chapter builds toward one question: which tool fits this task, and where does it fall short.
Target Readers
- Developers who already use one AI coding tool and want a framework for evaluating others against their actual workflow
- Engineering managers who need to judge generative AI's real productivity impact rather than take a vendor's claims at face value
- Teams deciding where in their development process, code review, testing, or documentation, AI assistance is worth adopting first
Tags
Colophon
- Publisher
- オライリー・ジャパン
- ISBN
- 978-4-8144-0146-8
- Published
- Jan 2026
- List price
- ¥3,080incl. taxMay differ from the actual selling price on Amazon
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Prerequisites
- Recommended
Software Engineering at Google
Titus Winters, Tom Manshreck, Hyrum Wright
Reason: After understanding the engineering practices of large organizations, you view how generative AI changes the flow of development with the same discipline. AI is a tool that pays off only on a foundation of review, testing, and design judgment.
- Recommended
The Pragmatic Programmer
David Thomas, Andrew Hunt
Reason: Once you have the pragmatic mindset—sharpen your tools, own your judgment—you take in generative AI as a new tool. The ability to verify AI output rather than trust it blindly is the very craftsmanship of the AI era.
Next Books
- Recommended
Responsible Software Engineering
Daniel Barrett, Google Engineering
Reason: Once you can bring AI into development, you advance to the question of responsibility—the impact that power has on society. You take a view that weaves correctness, bias, and accountability of outputs into design from the start.