Generative AI for Software Developers: Future-Proof Your Career with AI-Powered Development and Practical Hands-On Skills - Softcover

Shrivastava, Saurabh; Arora, Kamal; Dubey, Ashutosh; Thakur, Dhiraj; Sahay, Sanjeet

Softcover

ISBN 13: 9798312543698

Publisher: Independently published, 2025

Synopsis

Generative AI for Software Developers — Winning Strategies and Practical Tactics for AI-Powered Development

“Generative AI for Software Developers” is an essential guide to mastering AI-driven development, helping engineers future-proof their careers. This book provides a structured, hands-on approach to understanding, implementing, and optimizing Generative AI tools and techniques in modern software engineering. Covering everything from AI-assisted coding and debugging to system design and deployment, this book equips developers with real-world applications and best practices to integrate AI into their workflows effectively.

“A must-read for developers and architects looking to harness Generative AI for software innovation. It provides clear strategies, practical insights, and hands-on examples to master AI-powered development.” — David Ping, Head of GenAI/ML Solutions Architecture, AWS

“This book demystifies Generative AI and its role in modern software engineering. Whether you're a beginner or an experienced developer, this guide will help you integrate AI effectively into your workflow.” — Mrinal Priyadarshi, Senior ML Software Engineer, Amazon

“A hands-on guide that bridges theory and practice, helping developers move from experimenting with AI to building production-ready applications.” — Luis Lopez, Senior Generative AI Engineer, Google

Whether you're an aspiring AI developer or a seasoned software engineer or Solutions Architect, this book will help you navigate the future of software development with Generative AI.

What’s inside?
✔ Comprehensive Introduction to Generative AI for Developers
✔ Mastering AI-Powered Code Generation & Debugging
✔ Effective Strategies for AI-Driven Software Development
✔ Practical Guide to Prompt Engineering & AI Model Fine-Tuning
✔ Integrating AI into the Software Development Lifecycle (SDLC)
✔ Building Scalable AI-Powered Applications for Real-World Use Cases

Who is this book for
This book is designed for software developers, engineers, architects, and tech professionals who want to:

• Understand the core concepts behind Generative AI and its real-world applications.
• Master AI-driven development workflows to improve efficiency and code quality.
• Use tools like GitHub Copilot, Amazon Q Developer, and OpenAI APIs to automate coding tasks.
• Apply AI techniques for debugging, documentation, testing, and deployment.
• Learn prompt engineering and fine-tuning strategies for optimizing AI outputs.
• Architect scalable AI-driven applications with well-defined best practices.

Why This Book Matters Now
The software industry is evolving faster than ever, and developers who understand AI-driven development will have a competitive edge in the job market. Whether you are looking to stay ahead in your current role, enhance your coding efficiency, or explore new career opportunities in AI-driven development, this book will guide you on your journey.
Generative AI isn’t replacing developers—it’s empowering them.

Book Outline:
Chapter 1 — The Art and Science of Generative AI
Chapter 2 — Getting Started with Generative AI
Chapter 3 — Generative AI Architecture Fundamentals
Chapter 4 — Generative AI in Software Development
Chapter 5 — Prompt Engineering for Software Developers
Chapter 6 — Integrating Generative AI into the Software Development Cycle
Chapter 7 — Generative AI for Specific Programming Tasks
Chapter 8 — Generative AI Application Architecture & Design
Chapter 9 — Reinforcement Learning and Agentic AI Architecture
Chapter 10 — Well-Architecting and Fine-Tuning Generative AI Applications
Chapter 11 — Hands-On Guide to Building a Generative AI Application

Edition details

• Publisher: Independently published
• Publication date: 2025
• ISBN 13: 9798312543698
• Binding: Paperback
• Language: English
• Number of pages: 432