Vibe Coding Tutorial: Build Web Apps with Copilot, Cursor & Antigravity
1. Introduction: What Is Vibe Coding and Why It Matters 1.1 From Autocomplete to Autonomy: How AI-Assisted Programming Has Evolved A decade ago, AI assistance i...
1. Introduction: What Is Vibe Coding and Why It Matters
1.1 From Autocomplete to Autonomy: How AI-Assisted Programming Has Evolved
A decade ago, AI assistance in programming meant little more than autocompleting a variable name. Then came chat assistants that could explain code and suggest fixes. Now we've entered the era of agentic coding tools—AI systems that don't just suggest lines but plan, edit multiple files, run commands, and verify their own work.
This shift changes the developer's role. Instead of writing every line, you direct intent: you describe what you want, review what the AI produces, and refine iteratively. In 2025, this workflow has matured enough that beginners can ship real, working applications in a fraction of the time it once took.
1.2 Defining Vibe Coding: A Practical Working Definition
The term "vibe coding" was popularized by Andrej Karpathy to describe a style of programming where you describe your goal in natural language and let AI generate the implementation, reviewing and steering as you go.
The core loop is simple:
- Describe what you want
- Generate the code
- Review the output
- Refine through follow-up prompts
What vibe coding is not: it isn't "no-code" (you still work in real codebases), and it isn't blind trust (you must read and verify output). Vibe coding is collaborative, not passive.
1.3 Meet the Toolchain: Copilot vs. Cursor vs. Antigravity
| Tool | Type | Strengths | Best For |
|------|------|-----------|----------|
| GitHub Copilot | IDE extension | Fast inline completions, chat, wide IDE support | Quick edits, learning syntax |
| Cursor | AI-native editor | Codebase-aware context, agent mode, .cursorrules | Full-feature app development |
| Antigravity | Agent-first IDE | Browser control, artifact verification, task planning | Debugging and end-to-end testing |
1.4 What You'll Build in This Tutorial
You'll build a full-stack task manager: a React + Vite frontend, a Node/Express API, and a SQLite database. Along the way you'll learn prompting, context engineering, and how to debug with AI agents.
Prerequisites: Node.js 20+, Git, and accounts for Cursor, GitHub Copilot, and Antigravity.
2. Setting Up Your Vibe Coding Environment
2.1 Installing and Configuring Cursor
Download Cursor from its official site, install it, and on first launch choose Import VS Code Settings to bring over your extensions and keybindings. Sign in and select a model (Claude Sonnet is a strong default for coding).
Enable these settings:
- Agent mode: allows multi-file edits
- Auto-run: lets the agent execute terminal commands (use cautiously)
.cursorrules: a project-level rules file
2.2 Setting Up GitHub Copilot Alongside Cursor
Copilot and Cursor's built-in AI can coexist. Use Copilot for quick inline completions and Cursor's agent for larger, multi-file tasks. Install the Copilot extension, then in settings disable Cursor's Tab autocomplete to avoid conflicts.
2.3 Getting Started with Antigravity
Install Antigravity and open your project folder. Familiarize yourself with two views:
- Agent Manager: plan and dispatch tasks
- Editor: review generated artifacts
Connect your browser so the agent can navigate and test your running app automatically.
2.4 Project Scaffolding: Your First Prompt
Open Cursor's chat and paste:
Scaffold a React + Vite task manager with a Node/Express API and
SQLite database. Use TypeScript. Separate client and server folders.
Include a basic README with run instructions.
Review the generated structure, then commit the baseline:
git init
git add .
git commit -m "chore: initial scaffold"
Committing first means you can always roll back if an AI edit goes wrong.
3. Core Vibe Coding Techniques: Prompting That Works
3.1 The Anatomy of a Good Coding Prompt
A strong prompt has four parts: context + intent + constraints + expected output.
Bad prompt:
"Make a form."
Good prompt:
"In
src/components/TaskForm.tsx, create a React form with fields for title (required), due date (date picker), and priority (low/medium/high). Use controlled components and TypeScript. Return the component only."
The second version tells the AI where, what, how, and what to return.
3.2 Context Engineering: Feeding AI Your Codebase
In Cursor, use references to give precise context:
@file— a single file@folder— a directory@codebase— semantic search across the project
Attach error logs, docs, or screenshots when relevant. Keep context small and focused: ten relevant files beat a hundred irrelevant ones.
3.3 Iterative Refinement: The "Small Diffs" Principle
One giant prompt usually produces a mess. Ten small prompts produce clean, reviewable changes. Build a form field-by-field:
- "Add a title input."
- "Add validation: title is required."
- "Add a due-date picker."
- "Add a priority dropdown."
Use Cmd+K (inline edit) for tiny changes, chat for questions, and agent mode for multi-file work.
3.4 Writing Rules Files for Consistent Output
A .cursorrules file encodes your conventions. Example:
- Use TypeScript strict mode
- Prefer functional components with hooks
- Name files in PascalCase for components, camelCase for utils
- Handle errors with try/catch and return typed results
- Write a test for every new API route
Now every generation follows your style automatically.
4. Building the App: A Step-by-Step Walkthrough
4.1 Step 1 — Designing the Data Model with AI
Prompt:
Design a SQLite schema for tasks with tags, due dates, and priority.
Include indexes on due_date and priority.
The AI might propose:
CREATE TABLE tasks (
id INTEGER PRIMARY KEY AUTOINCREMENT,
title TEXT NOT NULL,
due_date TEXT,
priority TEXT CHECK(priority IN ('low','medium','high')),
completed INTEGER DEFAULT 0
);
CREATE INDEX idx_due_date ON tasks(due_date);
CREATE INDEX idx_priority ON tasks(priority);
Critique it—ask for a tags join table—then generate migration files.
4.2 Step 2 — Generating the Backend API
Prompt:
Create Express routes for /tasks with full CRUD. Validate input with zod.
Return JSON. Add error handling middleware.
The AI generates something like:
router.post('/tasks', async (req, res) => {
const parsed = taskSchema.safeParse(req.body);
if (!parsed.success) return res.status(400).json(parsed.error);
const task = await db.createTask(parsed.data);
res.status(201).json(task);
});
Follow up with: "Add Jest tests for each route."
4.3 Step 3 — Building the React Frontend
Generate components one at a time: TaskList, TaskForm, FilterBar. For drag-and-drop:
Add drag-and-drop reordering to TaskList using dnd-kit.
Persist the new order to the API.
Then style it: "Style this with a clean, modern dark theme using Tailwind."
4.4 Step 4 — Wiring It Together and Debugging with AI
When you hit an error, paste it directly into chat. For example, a CORS issue:
- Paste the browser console error.
- AI suggests adding
corsmiddleware. - If it persists, ask Antigravity's browser agent to reproduce and inspect.
Three prompts, one fix—far faster than manual debugging.
5. Advanced Vibe Coding Techniques
5.1 Using Agent Mode for Multi-File Refactors
Agent mode can touch many files at once. Ask: "Refactor all API calls into a shared api.ts client and update imports." Review the diff carefully before accepting.
5.2 Automated Testing with Antigravity's Browser Agent
Point Antigravity at your running app and say: "Test the task creation flow and report failures." It clicks through the UI and returns a report.
5.3 Guardrails: When to Stop Trusting the AI
Always review: security-sensitive code, database migrations, and anything touching auth. Keep commits small so you can revert quickly.
6. Conclusion
Vibe coding isn't about replacing developers—it's about amplifying them. By combining Copilot for fast completions, Cursor for codebase-aware agents, and Antigravity for autonomous testing, you can build full-stack apps faster than ever. Start with small prompts, engineer your context, and always review the output. Your first app is one prompt away.