1 Introduction to Generative AI

This chapter covers

How generative AI automates common coding tasks
The evolution from basic code completion to modern AI development assistants like GitHub Copilot and ChatGPT
Core components of Generative AI including LLMs, training data, and pattern recognition
Real-world development workflow using AI tools from planning to deployment
Common challenges with AI coding tools
Essential factors for adopting AI tools in your development process

Robots are not going to replace humans, they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull – these are the jobs robots will be taking.

- Sabine Hauert, Co-founder of Robohub.org

Hey, what if you could turn plain English into code, and save thousands of hours building software? That's the promise of generative AI tools. When I first learned of these tools I was skeptical - we all were. But after over a year of building real software with these tools, I've cut my coding time down drastically and found myself writing better code than ever before.

It’s likely you’ve already used ChatGPT or Claude for coding. You’ve likely seen GitHub Copilot suggestions pop up in your editor. Or maybe you're just curious about all the AI buzz. It’s everywhere. If you’re curious about how to leverage these tools to make yourself super productive, you're in the right place. This book is your practical guide to using AI tools to supercharge your coding - no AI expertise required.

1.1 Purpose and focus of this book

1.2 Generative AI for Coders

1.2.1 Code Generation and Autocompletion

1.2.2 Bug Detection and Automated Fixes

1.2.3 Documentation Generation

1.2.4 4. Code Refactoring and Optimization

1.2.5 Test Case Generation and Mock Data Creation

1.3 Developer Tools Landscape

1.3.1 Integrated Developer Tools

1.3.2 Standalone Tools

1.3.3 Summary

1.4 How does Generative AI work?

1.5 What is an LLM, and why should I care?

1.6 Why do these tools sometimes get it wrong?

1.6.1 How LLMs Differ from Databases

1.6.2 Training Phase Issues

1.6.3 Misinterpreting Context

1.7 The Potential of LLMs

1.8 Generative AI vs. Code Completion

1.8.1 Other types of Generative AI

1.8.2 Why we care about generative AI

1.9 Project Workflow with AI Assistance

1.10 Key factors to consider

1.11 Don’t fear the rise of AI

1.12 Go forth and code!

1.13 Summary