Guide to Using Generative AI in Programming

Description

Guide to Using Generative AI in Programming.

Discover how generative AI is reshaping software development—and learn how to use it as a powerful partner in modern programming.

Generative AI is transforming the way software is designed, written, tested, and maintained. As AI-powered coding assistants become increasingly capable, developers must understand not only how to leverage these tools effectively but also where human expertise remains essential. This book offers a balanced, practical introduction to integrating generative AI into the software development process while maintaining quality, security, and professional standards.

Combining hands-on guidance with insights from current research, the book demonstrates how AI can support a wide range of programming activities, including code generation, debugging, documentation, testing, information retrieval, and code review. It also examines the limitations and potential risks of AI-generated code, emphasizing the importance of critical thinking, verification, and sound software engineering practices.

Readers will gain a clear understanding of how large language models operate, why they produce the results they do, and how their underlying design influences both their strengths and their shortcomings. Through practical examples spanning multiple programming languages, the book illustrates effective techniques for incorporating AI into real-world development workflows.

Inside you’ll learn how to:

• Understand the fundamentals of large language models and generative AI.
• Use AI tools to accelerate coding, testing, debugging, and software analysis.
• Create effective prompts that generate accurate, maintainable, and production-quality code.
• Learn new programming languages and frameworks with AI-assisted guidance.
• Evaluate AI-generated output for correctness, security, and performance.
• Explore the latest research on AI-assisted software engineering and programming education.
• Understand how generative AI fits within the broader evolution of programming languages, paradigms, and software abstraction.

The book also explores the changing landscape of programming education, showing how AI is influencing the way developers learn, teach, and collaborate. Rather than replacing programmers, it argues that generative AI is most valuable when combined with human judgment, creativity, and problem-solving skills.

Designed for students, educators, and professional software developers, this guide is ideal for anyone seeking to understand both the practical applications and the underlying theory of generative AI in programming. Readers should have a basic understanding of programming concepts, but no previous experience with AI tools is required.