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AI for Developers: Building Better Software with AI Assistants
Paperback
Series: AI for Everyone, Book 17
Publisher: Finnoybu Press
Published: Apr 5 2026
Pages: 366
Weight: 1.38
Height: 0.76 Width: 7.50 Depth: 9.25
Language: English
The book I wish existed when I started using AI to write code.
Not a product manual. Not a prompt cookbook. Not a manifesto about how AI will replace developers (it will not) or a screed about how AI is just autocomplete (it is not). A practical, comprehensive guide to integrating AI into your software development workflow - across every major tool, every phase of development, and every type of project you are likely to encounter.
AI for Developers covers Claude Code, GitHub Copilot, Cursor, ChatGPT, Gemini Code Assist, Amazon Q Developer, Windsurf, and others. It teaches you how to use them together, when to reach for each one, and - critically - when to close the AI tab and think for yourself.
This book assumes you can already code. It does not explain what a function is, how a REST API works, or why version control matters. What it does is build a systematic AI-augmented workflow on top of skills you already have.
What's inside:
- Foundations. What AI actually means for development in 2026, the full landscape of coding-focused tools, and how to set up an AI-augmented development environment that does not get in your way.
- Core development skills, augmented. Writing code, reviewing code, debugging, refactoring, testing, and documentation - each chapter covers the patterns that work, the patterns that fail, and the prompt structures that consistently produce shippable output.
- Domain-specific development. Architecture decisions with AI in the loop. Frontend and backend specifics. DevOps and infrastructure. Working in large codebases (where AI tools really earn their keep). Git workflows. API design and consumption.
- Advanced concerns. Security review with AI. Database work and SQL generation. Mobile development. AI pair programming as a discipline, not just an autocomplete habit. Failure modes - the well-known ways AI generates plausible code that is subtly broken, and how to catch them. And building AI features into your own applications: API integration, function calling, RAG, evaluation, and cost control.
- The bigger picture. Adopting AI tools across a team without splitting the team in two. The trajectory of AI-assisted development and how to keep your skills durable as the tools evolve.
- Tool comparison tables, prompt patterns, configuration guides, a glossary, and curated further reading in the appendices.
Tool-specific tips appear in callout boxes labeled by name (Claude Code, Copilot, Cursor, etc.). Cross-tool advice - the stuff that works everywhere - is the through-line of the book. You leave with a toolkit, not a single-vendor allegiance.
For the developer who has stared at an AI-generated function, thought that looks right, shipped it, and then spent the next three hours debugging the one edge case the AI confidently ignored - this book is for you.
Includes coverage of Claude Code, GitHub Copilot, Cursor, ChatGPT, Gemini Code Assist, Amazon Q Developer, Windsurf, function calling, RAG, evaluation harnesses, and the 2026 agentic coding workflows.
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