# Generative AI for Software Developers

Generative AI for Software Developers is a practical book about applying generative AI across software engineering workflows. Its listed topics include AI-assisted coding, debugging, testing, documentation, deployment, prompt engineering, fine-tuning, and application architecture, with examples involving GitHub Copilot, Amazon Q Developer, and OpenAI APIs.

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- Market: US
- Language: en-US
- Currency: USD
- Category: Books, Music & Hobbies > Books, Music & Movies > Books & Comics
- Price: 28.99 USD
- Previous price: 54.99 USD
- Discount: 47%
- Price checked: 2026-11-14T05:49:45.980Z
- Rating: 4.7 / 5
- Reviews: 27

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## At a glance

- Addresses AI use across coding, debugging, testing, documentation, deployment, and system design.
- Covers prompt engineering, fine-tuning, SDLC integration, and GenAI application architecture.
- The listing names GitHub Copilot, Amazon Q Developer, and OpenAI APIs, and also mentions other platforms and tools.
- The chapter outline includes agentic AI, application design, and a hands-on application-building guide.

## Pros

- Broad coverage connects developer-assistance tools with later stages such as testing, deployment, and scaling applications.
- The listed hands-on projects and examples may help readers move beyond introductory GenAI concepts toward practical workflows.
- Includes topics relevant to both individual coding tasks and architecture-level decisions.

## Specifications

### Book details
- Publisher: Packt Publishing
- Publication date: October 10, 2025
- Language: English
- Print length: 454 pages
- ISBN-13: 978-1806671199
- ISBN-10: 1806671190
### Dimensions and installation
- Weight listed: 1.71 pounds
- Dimensions: 7.5 x 1.03 x 9.25 inches

## A good fit for

- Software developers and engineers looking to explore GenAI-assisted coding and SDLC workflows.
- Solutions architects interested in GenAI application architecture, scaling, and deployment.
- Readers seeking an introduction that spans prompting, coding tools, and application-building projects.

## Less suited to

- Readers looking only for a reference to one specific coding assistant or programming language.
- Readers who need a narrowly focused guide to one framework, API, or tool rather than broad GenAI coverage.

## Customer feedback

Aggregate customer ratings are strongly positive overall, though a small share are low-star ratings. This offers a favorable but limited signal about the book, not evidence about particular strengths, criticisms, or how well its examples suit a specific reader.

## Frequently asked questions

### What software-development topics does the book cover?
The listing describes coverage of AI-assisted coding, debugging, testing, documentation, deployment, system design, and integration into the software development lifecycle.
### Which tools are named in the listing?
GitHub Copilot, Amazon Q Developer, and OpenAI APIs are named in the main description. Other listing copy also mentions tools and platforms including Amazon Nova, ChatGPT, Claude, and Gemini.
### Is the book described as hands-on?
Yes. The listing says it includes guided projects, practical prompts, coding challenges, and end-to-end GenAI application work.
### What are the listed book details?
The listing gives Packt Publishing as the publisher, English as the language, a print length of 454 pages, and a publication date of October 10, 2025.

## Alternative options

- [The Agentic AI Bible: The Complete and Up-to-Date Guide to Design, Develop, and Scale Goal-Driven, LLM-Powered Agents that Think, Execute and Evolve](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [The Developer's Guide to AI: A Field Guide for the Working Developer](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [Agentic Coding with Claude Code: The everyday developer's guide to agentic coding with Claude Code](https://best-deals.pro/visit/agentic-coding-with-claude-code-developer-guide)
- [The Claude Code Operating Model: Build scalable AI coding systems with Skills, MCP, Hooks, agent orchestration, and SDK patterns](https://best-deals.pro/visit/claude-code-operating-model-ai-coding-workflows)
- [Kubernetes for Generative AI Solutions: A complete guide to designing, optimizing, and deploying Generative AI workloads on Kubernetes](https://best-deals.pro/visit/kubernetes-generative-ai-solutions-book)
- [Generative AI Design Patterns: Solutions to Common Challenges When Building GenAI Agents and Applications](https://best-deals.pro/visit/generative-ai-design-patterns-book)
- [Aside AI Browser in Practice: How to Delegate Real Work from Your Logged-In Browser — and Know Where to Stop](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [Agentic AI for Busy Product Managers: A Practitioner's Guide to the New PM Job](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [Agentic AI for Busy Product Managers: A Practitioner's Guide to the New PM Job \(Second Edition\) \(The Agentic AI Series\)](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [AI technologies for beginners: Understand AI Step by Step with Practical Prompts and Real Projects](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [The Lean AI Handbook: Building, Deploying, and Scaling AI for Business Value](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [Build with Claude Code: From zero to deployed apps with AI-assisted development](https://best-deals.pro/visit/build-with-claude-code-ai-assisted-app-development)

## Add-ons

- [AI Engineering: Building Applications with Foundation Models](https://best-deals.pro/visit/generative-ai-for-software-developers-book)
- [The AI Engineering Bible: The Complete and Up-to-Date Guide to Build, Develop and Scale Production Ready AI Systems](https://best-deals.pro/visit/generative-ai-for-software-developers-book)

## Images

![Generative AI for Software Developers — 1](https://best-deals.pro/i/1E2pj5os2ZqPHcjUDMfetmiHP-NLiMbBJKjjq6Gm8ckRD1a2k7-xfVi4tMTKhGfsaYejAyeHCMGKZqM7xLQDTvuOX1pSlqLcpHCZKfOveS2DQXo3oMAF.jpg)