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Coding with AI: Examples in Python
Practical techniques to accelerate software development using generative AI.
Let’s get real. You’d like to hand off a lot of tedious software development tasks to an assistant—and now you can! AI-powered coding tools like Copilot can accelerate research, design, code creation, testing, troubleshooting, documentation, refactoring and more. Coding with AI shows you how. Written for working developers, this book fast-tracks you to AI-powered productivity with bite-size projects, tested prompts, and techniques for getting the most out of AI.
In Coding with AI you’ll learn how
• Incorporate AI tools into your development workflow
• Create pro-quality documentation and tests
• Debug and refactor software efficiently
• Create and organize reusable prompts
Coding with AI takes you through several small Python projects with the help of AI tools, showing you exactly how to use AI to create and refine real software. This book skips the baby steps and goes straight to the techniques you’ll use on the job, every day. You’ll learn to sidestep AI inefficiencies like hallucination and identify the places where AI can save you the most time and effort.
About the technology
Taking a systematic approach to coding with Al will deliver the clarity, consistency, and scalability you need for production-grade applications. With practice, you can use AI tools to break down complex problems, generate maintainable code, enhance your models, and streamline debugging, testing, and collaboration. As you learn to work with AI’s strengths—and recognize its limitations—you’ll build more reliable software and find that the quality of your generated code improves significantly.
About the book
Coding with AI shows you how to gain massive benefits from a powerful array of AI-driven development tools and techniques. And it shares the insights and methods you need to use them effectively in professional projects. Following realistic examples, you’ll learn AI coding for database integration, designing a UI, and establishing an automated testing suite. You’ll even vibe code a game—but only after you’ve built a rock-solid foundation.
What's inside
• Incorporate AI into your development workflow
• Create pro-quality documentation and tests
• Debug and refactor software efficiently
• Create and organize reusable prompts
About the reader
For professional software developers. Examples in Python.
About the author
Jeremy C. Morgan has two decades of experience as an engineer building software for everything from Fortune 100 companies to tiny startups.
Table of Contents
Part 1
1 Introducing generative AI
2 First steps with AI-assisted coding
Part 2
3 Design and discovery
4 Coding the first version of our application
5 Using Blackbox AI to generate base code
6 Generating a software backend with Tabnine
Part 3
7 Building user interfaces with ChatGPT
8 Building effective tests with generative AI
9 Prompt engineering
10 Vibe coding with Cursor
Let’s get real. You’d like to hand off a lot of tedious software development tasks to an assistant—and now you can! AI-powered coding tools like Copilot can accelerate research, design, code creation, testing, troubleshooting, documentation, refactoring and more. Coding with AI shows you how. Written for working developers, this book fast-tracks you to AI-powered productivity with bite-size projects, tested prompts, and techniques for getting the most out of AI.
In Coding with AI you’ll learn how
• Incorporate AI tools into your development workflow
• Create pro-quality documentation and tests
• Debug and refactor software efficiently
• Create and organize reusable prompts
Coding with AI takes you through several small Python projects with the help of AI tools, showing you exactly how to use AI to create and refine real software. This book skips the baby steps and goes straight to the techniques you’ll use on the job, every day. You’ll learn to sidestep AI inefficiencies like hallucination and identify the places where AI can save you the most time and effort.
About the technology
Taking a systematic approach to coding with Al will deliver the clarity, consistency, and scalability you need for production-grade applications. With practice, you can use AI tools to break down complex problems, generate maintainable code, enhance your models, and streamline debugging, testing, and collaboration. As you learn to work with AI’s strengths—and recognize its limitations—you’ll build more reliable software and find that the quality of your generated code improves significantly.
About the book
Coding with AI shows you how to gain massive benefits from a powerful array of AI-driven development tools and techniques. And it shares the insights and methods you need to use them effectively in professional projects. Following realistic examples, you’ll learn AI coding for database integration, designing a UI, and establishing an automated testing suite. You’ll even vibe code a game—but only after you’ve built a rock-solid foundation.
What's inside
• Incorporate AI into your development workflow
• Create pro-quality documentation and tests
• Debug and refactor software efficiently
• Create and organize reusable prompts
About the reader
For professional software developers. Examples in Python.
About the author
Jeremy C. Morgan has two decades of experience as an engineer building software for everything from Fortune 100 companies to tiny startups.
Table of Contents
Part 1
1 Introducing generative AI
2 First steps with AI-assisted coding
Part 2
3 Design and discovery
4 Coding the first version of our application
5 Using Blackbox AI to generate base code
6 Generating a software backend with Tabnine
Part 3
7 Building user interfaces with ChatGPT
8 Building effective tests with generative AI
9 Prompt engineering
10 Vibe coding with Cursor
336 pages, Paperback
Published October 21, 2025
1 person want to read
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Displaying 1 of 1 review
October 22, 2025
Coding with AI is one of the few books on the subject that goes beyond hype and actually teaches a practical workflow. Instead of showing isolated code snippets, it demonstrates how to integrate AI into the real development process: from idea, to prototyping, to production-ready code.
What I particularly appreciated as a reviewer was the balance between explanation and application. It does not treat AI as a magic black box but as a tool that must be guided with structure, intent, and precise prompts. Developers who already know how to code will gain the most, because the book shows how to accelerate existing skills instead of replacing them.
The examples are realistic, the guidance is grounded, and the teaching style is clear without being simplistic. If you want to learn how to actually work with AI in software development instead of just experiment with it, this is the right book.
What I particularly appreciated as a reviewer was the balance between explanation and application. It does not treat AI as a magic black box but as a tool that must be guided with structure, intent, and precise prompts. Developers who already know how to code will gain the most, because the book shows how to accelerate existing skills instead of replacing them.
The examples are realistic, the guidance is grounded, and the teaching style is clear without being simplistic. If you want to learn how to actually work with AI in software development instead of just experiment with it, this is the right book.
Displaying 1 of 1 review