Welcome to the future of coding! This guide will help you become a master at coding with AI assistance.
Vibe coding is about:
- Describing what you want instead of how to build it
- Iterating quickly with AI suggestions
- Learning by doing rather than studying syntax
- Focusing on ideas while AI handles the implementation
Cursor (Recommended)
- Built-in AI that understands your entire project
- Press
Cmd+Kto ask questions or generate code - Press
Cmd+Lto chat about your code
ChatGPT/Claude
- Great for planning and problem-solving
- Copy/paste code for help
- Ask for explanations and alternatives
GitHub Copilot
- Auto-completes as you type
- Great for learning patterns
- Works in VS Code
❌ Bad: "Make a website"
✅ Good: "Create a personal portfolio website with a dark mode toggle, sections for projects and contact info, using React and Tailwind CSS"
Start simple, then add:
- "Create a button that says Hello"
- "Make it blue with rounded corners"
- "Add a click animation"
- "Make it show a random greeting when clicked"
Creating Features:
Create a [feature] that [does something] using [technology].
It should [requirement 1], [requirement 2], and [requirement 3].
Include error handling and user feedback.
Debugging:
This code [describe problem]. Here's the error: [paste error].
The expected behavior is [what should happen].
Can you fix it and explain what was wrong?
Learning:
Explain this code in simple terms: [paste code]
What does each part do?
How could it be improved?
Always start new projects with context files:
CLAUDE.md - Tell AI about your project:
- What you're building
- Tech stack preferences
- Coding style
- Current goals
README.md - Document as you go:
- What the project does
- How to run it
- What you've built so far
Ask AI to create a basic structure:
"Create a basic Express server with:
- A home route that returns JSON
- Error handling
- Clear comments explaining each part
- A README with setup instructions"
Work in small increments:
- Ask for one feature
- Test it
- Understand it
- Ask for the next feature
Always ask:
- "Explain what this code does"
- "What are the potential issues?"
- "How could this be improved?"
- "What's a simpler way to write this?"
- Planning: "What's the best structure for a todo app?"
- Debugging: "Why is this returning undefined?"
- Refactoring: "Make this code cleaner and more efficient"
- Learning: "Explain React hooks with examples"
- Testing: "Write tests for this function"
The more context AI has, the better:
"I'm building a recipe app for beginners.
I have a Recipe model with title, ingredients, and steps.
Create an API endpoint to search recipes by ingredient.
Use Express and return JSON. Include pagination."
The Builder Pattern
1. "Create a basic [thing]"
2. "Add [feature] to it"
3. "Now add [another feature]"
4. "Refactor to make it cleaner"
The Debugger Pattern
1. "Here's my code: [paste]"
2. "It should [expected behavior]"
3. "But it's [actual behavior]"
4. "What's wrong and how do I fix it?"
The Learner Pattern
1. "Show me a simple example of [concept]"
2. "Now make it more complex with [feature]"
3. "Explain the differences"
4. "When would I use each approach?"
Try these with your AI assistant:
"Create a personal dashboard with:
- Current time and date
- A todo list that saves to localStorage
- A random motivational quote
- Dark mode toggle"
"Build a simple app that:
- Lets users enter any public API URL
- Fetches and displays the data
- Formats JSON nicely
- Handles errors gracefully"
"Create a number guessing game where:
- Computer picks a random number 1-100
- User gets hints (higher/lower)
- Tracks number of guesses
- Has a play again button"
❌ "Make it better" ✅ "Add input validation, error messages, and a loading spinner"
❌ "Build a full e-commerce site with payments" ✅ "Start with a product listing page, then we'll add features"
Always test each addition before moving on!
Don't just copy-paste. Ask:
- "What does this line do?"
- "Why did you use this approach?"
- "What happens if I change this?"
- Start asking for explanations
- Request multiple solutions
- Ask about best practices
- Learn to debug with AI
- Provide more context upfront
- Ask for architectural decisions
- Request performance optimizations
- Use AI for code reviews
// Starting a new feature
"Create a [feature description] that integrates with my existing [context]"
// Debugging
"This code produces [error/unexpected behavior]: [code]. Expected: [what you want]"
// Improving code
"Refactor this for better [performance/readability/maintainability]: [code]"
// Learning
"Explain [concept] with a practical example I can run"
// Planning
"What's the best approach to implement [feature] considering [constraints]?"- You don't need to memorize syntax - AI remembers for you
- Focus on what, not how - Describe the outcome you want
- Iterate fast - Small changes, quick tests
- Stay curious - Always ask "why" and "what if"
- Have fun - If it's not fun, you're doing it wrong!
- Open your ai-starter-project
- Start Cursor
- Press Cmd+K and type: "Add a /api/time endpoint that returns the current time in multiple timezones"
- Run the code
- Ask: "Now add a simple HTML page that displays these times and updates every second"
Welcome to the future of coding! 🎉