Vibe coding is the practice of building software using AI tools by describing what you want in natural language rather than writing the code yourself. You prompt, the AI generates, you refine, you ship. The main tools are Lovable, Bolt, Cursor, and Replit. This guide covers how to do it, what to watch out for, and the validation step that most vibe coders skip, which is why so many vibe-coded apps launch to crickets.
Vibe coding is a term that originated with Andrej Karpathy in early 2025, describing the practice of "going with the flow" of AI-generated code without necessarily reading or understanding every line. You describe what you want. The AI writes the code. You refine the output by describing what needs to change. You repeat until you have something that works.
The term has expanded to cover any approach where the primary mode of software creation is natural language prompting rather than traditional coding. It's become a real workflow for a meaningful number of founders, PMs, and designers who can now build working products without a full engineering team.
It's not magic. You still need to know what you're building. You still need to debug, test, and iterate. But the barrier to creating working software has dropped significantly.
Lovable: Best for building full-stack web apps from a prompt. You describe your product, Lovable generates a React + Supabase application with real-time preview. Deploy with one click. Strong for founders who want to skip the technical setup entirely.
Bolt (bolt.new): Full-stack generation in the browser with more code access. If you're comfortable reading generated code and want more control over the output, Bolt gives you a full development environment without local setup. Supports multiple frameworks.
Cursor: An AI-powered IDE built on VS Code. Unlike Lovable and Bolt, Cursor is designed for developers who want AI assistance within an existing codebase, not full generation from scratch. Best for semi-technical founders who know what they're building and want AI to accelerate the development.
Replit: Browser-based collaborative coding with AI built in. Strong for Python, collaborative prototypes, and quick deployments. A large community and template library make it easy to start from something that already works.
For most beginners: start with Lovable or Bolt. For technical founders who want to stay close to the code: Cursor.
Vibe coding doesn't start with a prompt. It starts with clarity about what you're building and why.
Before you open any tool, write down:
- What does this product do?
- Who is it for?
- What's the one most important thing a user does in it?
- What does success look like for a user in their first session?
The more clearly you can articulate this, the better your initial prompts will be. Vague inputs produce vague outputs.
Your first prompt should describe the full product at a high level. Be specific about:
- The type of application (web app, dashboard, tool, marketplace)
- The core user workflow
- The main data entities involved
- Any specific design preferences
"Build me a project management app."
"Build a web app for freelancers to track client projects. Users should be able to create projects, add tasks to each project with due dates and status (not started, in progress, done), and see a dashboard showing all active projects and their completion percentage. Clean, minimal design."
You won't get it perfect on the first attempt. That's expected. The process is iterative.
After your first generation, you'll have something that's roughly right but needs refinement. Work through it methodically:
Each iteration gets you closer. Most vibe coders report that 3 to 5 rounds of refinement on each major feature is typical.
Vibe coding has real limits:
- Complex business logic is hard to express in natural language
- Data modeling errors can compound as the codebase grows
- Integrations with third-party services often require manual intervention
- Edge cases require explicit description to handle correctly
When you hit a wall, be specific in your prompt about what the edge case is and what the correct behavior should be. If the AI can't solve it in two or three attempts, it might be a case where human-written code is the right solution for that piece.
Lovable and Bolt both have one-click deployment. Replit deploys automatically. If you're using Cursor, you'll need a deployment target; Vercel, Netlify, Railway, and similar services work well with the generated code.
Once deployed, share the link with a small group of people before any public launch.
Here's where most vibe-coded products fall over.
You built something fast. It works. You deployed it. You're excited about it. You share it with a few friends who say it's great. You launch.
Then real users arrive. They can't find the main feature. They don't understand what the app is for. They click somewhere unexpected and get confused. They leave.
The problem isn't the code. The problem is that your prompt reflected your mental model of the product, and your mental model isn't the same as your users'.
The fix is five people, one task, one afternoon of reviewing recordings. That's prototype testing: giving real users a specific task to complete in your app and watching what they do. Asana cut their research cycle from 2 weeks to 2-3 days doing exactly this kind of testing, which tells you how tight the feedback loop can get when it's built into your workflow. You'll learn more about your app in two hours of watching user sessions than in two weeks of building, and you'll learn it before your launch, when you can still do something about it.
Trying to build too much at once. Start with the smallest useful version of your product. One core workflow, done well. Add everything else later. If you're still picking tools, our breakdown of the best vibe coding tools in 2026 covers the tradeoffs between Lovable, Bolt, Cursor, and Replit. Stack-specific testing guides: Lovable, Bolt.
Shipping without testing with users. The app working for you is not evidence it works for users. You have too much context. Strangers don't.
Fighting the AI instead of guiding it. When the AI produces something you don't want, resist the urge to edit the code directly (unless you're in Cursor and comfortable doing so). Describe what you want instead. Editing generated code manually creates drift between the code and the AI's model of what it's building.
Not saving progress. Before a major prompt, commit your current state or save a backup. Prompts can sometimes break things that were working.
Trusting the AI's database decisions. When you describe an app, the AI silently makes structural choices about how your data is stored: what fields exist, how users and their stuff relate to each other, what happens at scale. Those choices often work for the 3 demo rows in your prompt and break when real users show up. Before you launch, load the app with a realistic amount of fake data (hundreds of users, thousands of records) and see what still works. The stuff that falls over is what you need to fix.
Once you have a working app, before any public launch, run it through a quick usability test.
Five participants. One task: the most important thing a user does in your app. Thirty minutes each.
Great Question's unmoderated prototype testing works with live URLs. You can link directly to your deployed app, set a task, recruit participants from your own network or from Great Question's external panel, and get session recordings back within hours.
The recordings show you where users get stuck, where they click when they're confused, and whether they can complete the core task at all. The AI synthesis surfaces the patterns across all five sessions in minutes.
If you're building in Cursor, Great Question's MCP integration lets you create study types, add participants, and query research findings without leaving your IDE.
What is vibe coding?
Vibe coding is the practice of building software by describing what you want in natural language, using AI tools to generate the code. The builder prompts, the AI generates, and the process repeats until the app works as intended. Main tools include Lovable, Bolt, Cursor, and Replit.
Do you need to know how to code to vibe code?
Not necessarily. Tools like Lovable and Bolt are designed for non-technical founders. You need to know what you want to build and be able to describe it clearly. The AI handles the code. That said, some technical literacy helps when things go wrong and you need to understand what the AI generated.
How long does it take to build an app with vibe coding?
For a simple app with one core workflow: hours to a day. For something more complex with multiple user types, integrations, or data models: days to a week of prompting and iteration. Vibe coding compresses development time significantly, but complex requirements still take time to express and refine.
What are the best vibe coding tools for beginners?
Lovable is the most beginner-friendly for full-stack web apps. It handles the full stack, has a real-time preview, and deploys with one click. Bolt is a close second with more code access. Replit is strong for Python or collaborative use cases.
What should I do after building my app with vibe coding?
Test it with real users before launching publicly. Five users, one task, an afternoon of reviewing recordings. This is what catches the usability issues that you can't see because you built the app. Great Question's unmoderated prototype testing is the fastest way to do this.
Vibe coding is real, it works, and it's getting better every month. The tools will handle more and more of the technical complexity. What won't get easier on its own is building something that actually works for users. That part is still on you, and it takes less time than you think.
Validate your vibe-coded app before you launch. Start with Great Question →
Related: How to validate your vibe-coded app with real users · Best vibe coding tools in 2026 · Prototype testing: the complete guide for product builders · How to test your Lovable app with real users
Tania Clarke is a B2B SaaS product marketer focused on using customer research and market insight to shape positioning, messaging, and go-to-market strategy.
