Morgan J. Coding with AI. Examples in Python 2025 Final
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- Textbook in PDF format 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 to: 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 Morgan is on a mission to help developers get better at what they do. He's a Senior Training Architect for KodeKloud and an avid tech blogger and speaker. He has two decades of experience as an engineer building software for everything from Fortune 100 companies to tiny startups. Jeremy hosts the popular tech blog, www.jeremymorgan.com. He also contributes to open source as a .NET Foundation Member, DevOps Institute Ambassador, and serves on a DevNetwork advisory board. Table of Contents Part 1 Introducing generative AI First steps with AI-assisted coding Part 2 Design and discovery Coding the first version of our application Using Blackbox AI to generate base code Generating a software backend with Tabnine Part 3 Building user interfaces with ChatGPT Building effective tests with generative AI Prompt engineering Vibe coding with Cursor Get a free eBook (PDF or EPUB) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book
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