Software Engineering in the Age of AI

Artificial intelligence is changing the way software is built. Developers can now generate implementations, write tests, explain unfamiliar code, troubleshoot errors, and build features with AI assistance in a fraction of the time it once took.

But faster implementation does not automatically mean better software.

When AI becomes part of the development process, software engineers need to become better at something even more fundamental: thinking like engineers.

Software Engineering in the Age of AI is a practical guide to navigating software development when AI is increasingly involved in implementation. Rather than focusing on a particular AI tool or teaching a collection of prompts, this book focuses on the engineering judgment required to use AI effectively and responsibly.

Throughout the book, you will learn what to look out for when implementing software with AI assistance, including incorrect assumptions, hidden complexity, security risks, unnecessary abstractions, fragile solutions, misleading tests, and code that appears correct but fails to satisfy the real requirements.

This book is not designed simply to tell you what to watch for, instead it is designed to make you think.

Think Like an Engineer sections appear throughout the book to challenge you to pause before accepting an AI-generated solution. These sections encourage you to question assumptions, examine trade-offs, consider alternative approaches, and understand why a solution works rather than simply accepting that it works.

You will also find Practice Challenges that give you opportunities to apply the ideas from each chapter. These exercises are designed to turn concepts into practical engineering skills and help you develop the habit of critically evaluating AI-assisted implementations.

For deeper understanding, the book includes Case Studies that examine realistic software engineering situations and demonstrate how seemingly reasonable decisions can lead to unexpected problems, and how stronger engineering thinking can prevent them.

Inside, you will explore:

• How AI is changing the software development process
• What to look for when reviewing AI-generated code and implementations
• Why requirements and context matter when working with AI
• How to evaluate architecture and design decisions made with AI assistance
• How to identify security, reliability, maintainability, and testing risks
• Why AI can accelerate technical debt and unnecessary complexity
• How to verify software instead of simply trusting generated output
• How to develop stronger engineering judgment in an AI-assisted workflow

Whether you are a software developer beginning to use AI coding assistants or an experienced engineer adapting to a new development workflow, this book provides a framework for using AI without losing the skills that matter most.