Vibe Coding Tutorial: Ship Your First App

Vibe coding is shipping software primarily by directing AI tools rather than writing every line yourself. The phrase implies a looser, prompt-and-iterate workflow vs. traditional careful engineering. This tutorial walks through shipping your first vibe-coded app from idea to live URL in one weekend.

The audience: founders, designers, product people, and developers who haven't tried AI-first coding yet. By the end, you'll have a working web app you can show to real users.

Before you start: pick the right tool

Three tools dominate vibe coding in 2026:

• Lovable - full-stack web apps with built-in Supabase. Best for a working SaaS-shaped product.
• v0 - UI-focused; ships beautiful pages fast. Best for marketing sites or single-screen apps.
• Bolt - similar to Lovable; runs entirely in browser, more stack flexibility.

For your first vibe-coded app, Lovable is the easiest start. It handles auth, database, and deployment. You'll have a working URL within 30 minutes.

If you want maximum control over the codebase, skip the all-in-one tools and use Cursor or Claude Code to build directly in a Next.js + Supabase project. That's a steeper learning curve but the resulting app is more maintainable.

For this tutorial, we assume Lovable. The principles transfer to the other tools.

Step 1: pick what to build

This is the part that breaks more vibe-coding attempts than the technical work. Three rules:

Build something specific, not something general. "Build me a CRM" → vague output. "Build me a contact tracker for solo consultants who want to log every conversation with a client" → focused output that's actually useful.

One clear user, one clear job. The user types a name + note, the app saves it. That's the whole MVP. Don't add reminders, integrations, dashboards in v1.

You should be the user. Vibe coding works best when you can immediately tell whether the output is right. If you're building for an audience you don't understand, you'll prompt vaguely and get vague results.

Good first vibe-coded apps:

• Personal CRM / contact log
• Reading queue with Tailscale-style features
• Habit tracker for one specific habit
• Internal tool you'd actually use weekly
• Simple invoicing app for your own consulting

Step 2: write the seed prompt

A good seed prompt has three parts:

1. What it is: "I'm building a [thing] for [audience] who want to [job]."
2. Core feature list: 3-5 must-have features in plain English.
3. Stack preferences: "Use Next.js, Supabase for auth and DB, Tailwind for styling."

Example seed prompt:

I'm building a contact tracker for solo consultants who want to log every conversation with a client.

Core features:

• Sign up with email + password
• Add a client (name, email, company)
• Log a conversation under a client (date, notes, follow-up date)
• View all conversations for a client
• Mark conversations as needing follow-up

Stack: Next.js, Supabase for auth and database, Tailwind CSS, deployed to Vercel.

Paste this into Lovable. It generates a working app in 30-60 seconds.

Step 3: iterate, don't rebuild

The temptation: when something doesn't look right, regenerate the whole app. Don't. Iterate in small prompts:

• "The 'Add Client' form is missing the email field"
• "Make the conversation list show the most recent first"
• "Add a button to mark a conversation as 'needs follow-up'"

Small prompts produce predictable, debuggable changes. Big prompts ("redesign the whole UI") produce surprises that break things.

Cadence: prompt, look at output, decide if it's right, prompt again. 5-10 small prompts gets you a useful app.

Step 4: the security pass that nobody tells you about

The single biggest gotcha with vibe-coded apps: default Supabase RLS is permissive. When Lovable generates auth + DB, it usually creates tables without proper Row Level Security policies. That means any authenticated user might be able to read or write any other user's data.

This is the #1 vulnerability in shipped vibe-coded apps. Before launching to real users:

1. Open your Supabase dashboard
2. For every table, enable RLS
3. Add policies that scope to the authenticated user (e.g., auth.uid() = user_id)
4. Test by creating two accounts and verifying each can only see their own data

Tools like vibeappscanner.com audit this automatically. We recommend running any vibe-coded app through it before launch.

Other common vibe-coded vulnerabilities:

• Exposed API keys: client-side code accidentally containing keys that should be server-only
• Missing rate limits on expensive endpoints (LLM calls, image generation)
• Unsanitized user input rendered into HTML
• Direct DB access from client that bypasses RLS entirely

These are all fixable; you just need to know to look.

Step 5: deploy

Lovable deploys to Vercel automatically. You get a your-app.lovable.app URL within minutes.

For real users, point a custom domain at the Vercel deployment. Add a privacy policy and terms (Lovable can generate basic ones). Set up basic error tracking (Sentry's free tier).

Step 6: get real users

The technical part is the easy part. Getting users is the hard part. Three paths from your shipped app:

1. Twitter / X build-in-public. Post the app, screenshots, what you learned. The first 100 users come from people watching you build.

2. ProductHunt launch. Coordinate hunt + launch day Twitter. Top-of-the-day apps see 1-3K signups.

3. Specific community. Find the 1-2 communities where your audience hangs out (subreddit, Discord, Slack). Be present, mention the app when relevant.

This is the same playbook covered in SaaS marketing guide - the rest of the marketing strategy.

Common vibe-coding mistakes

The five we see most:

Treating it as no-code when it's actually low-code. You'll need to read the generated code at some point. If you're not comfortable reading code, you're going to get stuck.

Skipping the security pass. See above. The single biggest production gotcha.

Building the same thing as everyone else. "AI todo list" was novel in 2023; now there are 500 of them. Build something specific to your audience.

Over-prompting in early iterations. Long, detailed prompts produce surprises. Short, focused prompts produce predictable changes.

Shipping to real users with no analytics. Even basic Vercel Analytics or Plausible tells you what's working. Skipping analytics means flying blind.

What to do next

If your app made it to a real URL: nice work. The next problems are marketing and production hardening. SaaS marketing guide covers marketing. Spring Code handles production hardening if you'd rather have help.

If you want to go deeper on tools: best AI coding tools covers the full landscape, Cursor vs Claude Code covers the heavy-user pair.