Vibe coding is changing how designers, developers, and product managers work together. I wanted to look at what it changes about prototyping, and which design decisions still need our attention.
What is Vibecoding?
In vibe coding, you describe what you want in natural language and use AI tools to generate and revise code. That can shorten the distance between an idea and a working prototype. You still need to check that the result behaves as intended.
Instead of writing css like display: flex; justify-content: space-between; you say “create a horizontal layout with items evenly spaced” and the AI figures out the CSS.
How is it related to Prototyping?
Before diving into how vibecoding changes prototyping, let’s talk about why we prototype in the first place.
Prototyping is about testing ideas before committing to full development. It’s cheaper to fail early with a prototype than to discover problems after building the real thing. Prototypes help you to:
- Validate concepts with real users before investing time and resources
- Communicate ideas to stakeholders, developers, and team members
- Explore multiple solutions quickly to find the best approach
- Identify problems early when they’re still easy to fix
- Align teams around a shared vision of what we’re building
Without prototyping, you are building in the dark, hoping assumptions are correct. Prototypes give you a way to test those assumptions with minimal investment.
What is fidelity, and how do we use it?
Fidelity describes how closely a prototype represents the intended experience. I find it useful to think in four dimensions, each of which can be adjusted to match what we need to learn. Choosing the right fidelity helps steer people’s attention towards the questions that matter. Choosing the wrong level can invite feedback on the wrong things:
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Too much visual fidelity too early: Stakeholders may focus on colours, fonts, and spacing before the concept is validated. A polished prototype can also make an unfinished idea appear ready to ship, making expectations harder to manage.
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Too high content fidelity too early: Users will get distracted by specific copy, product names, or data details. They’ll comment on “why is this product called X?” instead of whether the layout works.
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Too high interactivity too early: You’ll waste time building complex interactions for ideas that might not even make it past the first round of feedback. That smooth animation you spent hours on? Might be for a feature that gets cut.
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Too low fidelity when you need detail: Presenting a rough sketch to executives who need to see the vision can lead to rejection. They can’t see past the basic wireframes to understand the potential.
Every dimension you make high-fidelity is a signal: “Pay attention to this.” Every dimension you keep low is a signal: “Ignore this for now.”
Four dimensions of fidelity
1. Content Fidelity
- Low: Placeholder text, gray boxes, or lines representing content
- High: Real, live data that matches what users will actually see
2. Technology Fidelity
- Low: Paper prototypes, sketches, or static images
- High: Coded prototypes that run in a browser or app
3. Visual Fidelity
- Low: Wireframes, basic shapes, minimal styling
- High: Polished designs with colors, typography, animations, and pixel-perfect details
4. Interactivity Fidelity
- Low: Static mockups or click-through prototypes
- High: Fully interactive prototypes with real behaviors and transitions
Combining Fidelity
You don’t always need high fidelity in all dimensions. A prototype can be:
- High visual fidelity, low interactivity – A polished static mockup for stakeholder review
- High interactivity, low visual fidelity – A functional wireframe for testing user flows
- High content fidelity, low technology – Paper prototypes with real data printed out
- High technology, low visual – A coded prototype with basic styling for functionality testing
The key is matching each dimension to what you’re trying to validate. Don’t waste time on high visual fidelity if you’re testing information architecture. Don’t build full interactivity if you’re just exploring layout options.
Ask yourself what you’re trying to learn:
- Testing layout? You need visual fidelity, but not necessarily interactivity or real content
- Testing user flows? You need interactivity and technology, but visual polish can wait
- Testing content strategy? You need content fidelity, but visuals might be less important
- Testing the complete experience? You need high fidelity across all dimensions
Before Vibecoding, Iterations might trigger a lot of manual work to adjust prototypes - something we want to avoid by… prototyping. The rise of vibecoding now makes it easier to adjust fidelity in each dimension independently. You can quickly add interactivity without visual polish, or add real content without building the full interface. But the paper prototypes are still up to you… ;)
How Different Types of Vibecoding Can Help
Different approaches to AI-assisted coding support different prototyping tasks. The useful question is which one helps us answer the question in front of us.
Text-to-Code Vibecoding
Best for: Low to mid-fidelity prototypes
Describe layouts and structures in natural language:
“Create a dashboard with a sidebar navigation, main content area, and a user profile dropdown in the header.”
Tools generate basic HTML/CSS structures, wireframes, or component skeletons. Perfect for rapid ideation and exploring layout options.
Visual-to-Code Vibecoding
Best for: Mid to high-fidelity prototypes
Upload a design mockup or sketch, and AI generates the corresponding code. This is great when you have a visual design but need to make it interactive quickly.
Interactive Vibecoding
Best for: High-fidelity prototypes
Describe interactions and behaviors:
“When clicking the card, it should smoothly expand to show details with a fade-in animation. On mobile, cards stack vertically.”
AI generates the JavaScript and CSS for complex interactions, making high-fidelity prototypes much faster to build.
Component-Based Vibecoding
Best for: All fidelity levels
Describe reusable components that can be assembled into larger prototypes:
“Create a form input component with validation, error states, and success feedback.”
This approach builds a library of components that can be reused across different prototypes and fidelity levels.
Which Tools to Use
Here are some practical tools that enable vibecoding at different levels:
Low-Fidelity Tools
- v0.dev – Describe layouts in natural language, get React components
- Figma AI – Generate wireframes from text descriptions
- Builder.io – Text-to-component generation for rapid prototyping
Mid-Fidelity Tools
- Cursor – AI-powered code editor that understands design intent
- GitHub Copilot – Generates code from comments and descriptions
- Replit – AI-assisted development environment for interactive prototypes
High-Fidelity Tools
- v0.dev – Advanced component generation with interactions
- Anima – Converts Figma designs to React/Vue code
- Locofy – Design-to-code with animations and interactions
- Framer – AI-assisted high-fidelity prototyping with code export
General Purpose
- ChatGPT/Claude – For describing designs and getting code suggestions
- Cursor – Full IDE with AI that understands context
- Codeium – AI code completion that works across editors
The best tool depends on your workflow. If you’re in Figma, Anima or Locofy make sense. If you’re coding directly, Cursor or v0.dev might be better.
The Bottom Line
Vibecoding is changing how we prototype, but it doesn’t replace good design thinking. It removes the friction between idea and implementation, letting you focus on what you’re building rather than how to build it.
The key is matching the right vibecoding approach to the right fidelity level. Use text-to-code for rapid low-fidelity exploration, visual-to-code when you have designs to make interactive, and interactive vibecoding for polished high-fidelity prototypes.
Start simple, test early, and only add fidelity when you need it. Vibecoding makes it easier to follow this principle. You can explore more ideas faster, test them sooner, and iterate more effectively.