Introduction
AI can now write working websites and apps from plain-language instructions. This opens software building to non-programmers — but the person giving instructions is still responsible for what goes live: security, data, correctness.
Kinds of AI coding tools
| Type | Examples | Best for |
|---|---|---|
| Chat assistants | Claude, ChatGPT, Gemini | Explaining code, writing files, fixing errors |
| App builders / playgrounds | Google AI Studio, Claude Artifacts, ChatGPT Canvas | Quick prototypes and single-page tools you can preview |
| Agentic coding tools | Claude Code, GitHub Copilot agent, Cursor | Working across a whole project: reading files, running tests, making many edits |
| In-editor autocomplete | GitHub Copilot, Gemini Code Assist | Developers typing code faster |
What AI is good at — and not
- ✅ Boilerplate pages, forms, CRUD screens, database tables, explanations, fixing error messages.
- ⚠️ Understanding your real business rules unless you explain them; security edge cases; large changes without breaking something else.
The safe workflow
- Plan — write a short spec: users, screens, data, rules.
- Generate — small pieces at a time.
- Read — ask AI to explain anything you don't understand.
- Test — try normal and wrong inputs.
- Deploy — with backups, HTTPS and passwords kept out of code you share.
Never paste real passwords, API keys or customer data into chat tools. Use placeholders like
DB_PASSWORD and fill them only on your server.