The AI prototyping tool built for how AI actually works.
Most "AI prototyping" is a chat window that hands you code to take somewhere else. Prototyper is the somewhere else: your agents build on the canvas, the prototype runs in the workspace, and your team steers by pointing at things.
An AI prototyping tool turns a description of a screen into something you can show people. The useful question is what comes out the other end. Most AI prototype generators produce one of two things: a picture of an interface, or a block of code you have to carry somewhere else before it does anything. Prototyper produces the third thing, the one you actually wanted. You describe the screen, an agent builds it in real React while you watch, and the result runs on the canvas in front of you. Click it, type in it, hand it to a user.
That difference decides what a prototype can teach you. A picture can settle a layout argument. Code in a transcript can pass a review. Only a prototype that runs can fail honestly under a real person's hands, and honest failure is the entire point of prototyping.
What an AI prototype generator should give you
Strip the category to its essentials and three requirements fall out.
First, the input should match how ideas arrive. Sometimes you have a sentence: “a billing settings page with a plan card and an invoice table.” Sometimes you have a marker sketch. On Prototyper's canvas both work. You can describe a screen to an agent, or draw rough boxes and let the agent build from the sketch. If you want to start at the rough end on purpose, the AI wireframe generator page covers that entry point.
Second, the output should be real. Prototyper's agents write React and Tailwind, and the app compiles and runs inside the workspace with a live preview you can operate. There is no separate export step where the prototype turns back into a picture. The running screen is the artifact.
Third, the prototype should live somewhere. A chat thread is a place code scrolls past; a canvas is a place work accumulates. On Prototyper the brief, the sketch, three candidate versions, and the winning build sit next to each other on one surface, and everyone on the team sees the same thing.
Visual prototypes you can actually operate
Two search phrases circle this space, and they name different needs. A visual prototype answers “what will it look like”: the arrangement, the hierarchy, the feel of the screen at a glance. An interactive prototype answers “what happens when someone uses it.” Classic tools forced you to pick a lane. Design tools made convincing visuals that faked interaction with linked hotspots; coded prototypes behaved honestly but cost engineering time nobody wanted to spend on a throwaway.
That trade collapsed when agents learned to write production-grade interface code in minutes. The working version now costs about what the facade used to, so the sensible default level of “interactive” has risen to “it runs.” Our guide to interactive prototypes walks the whole spectrum, from clickable facades to working software, and where each still earns its keep.
On the canvas you get both reads at once. Zoomed out, the prototype is visual: windows arranged spatially, versions side by side, stickies and notes around them. Zoomed in, it is fully interactive: forms accept input, state holds, empty and error states exist because the code that produces them exists. Nothing was mocked, so nothing lies to you in a user test.
A prototyping session, start to finish
Here is what the loop looks like in practice, from first sentence to shipped screen.
- 01
Start from a sentence or a sketch.
Drop a brief on the canvas, or describe the screen in the composer. Rough is fine; the agent will ask the canvas, not you, for context it can see.
- 02
Watch the build happen.
The agent works in the open. A window appears on the canvas, code streams into it, and the screen assembles in front of the team rather than behind a spinner.
- 03
Operate the result.
The moment it compiles, the prototype is live. Type real data into the form. Paste the ugly product name. Resize it. This is the honest test a static mock can never give you.
- 04
Branch instead of debating.
Exploring an alternative costs one sentence, so ask for three takes and compare them side by side. Keep the version that wins the argument. This is what makes rapid prototyping rapid in practice.
- 05
Steer by pointing.
Select the header that feels heavy, leave a sticky on the empty state, and the agent sees exactly what you see. No paragraph of re-prompting to relocate context a canvas holds for free.
- 06
Ship the one that wins.
The code that survived your user test is the code you take to production. There is no rebuild stage, because there is nothing to rebuild.
Where the alternatives stop
The honest comparison is about where each tool's output ends up. Chat-first generators such as v0, Lovable, and Bolt are genuinely good at the first minute: prompt in, plausible app out. Their limit is structural. The output lands in a thread, one version at a time, priced per generation, and steering means describing your intent again in words. Design tools run the opposite trade: Figma's prototype mode gives you precise visuals and fast hotspot wiring, but the interactivity is a facade and the handoff to engineering still waits at the end. We keep an honest side-by-side on the Prototyper vs Figma page.
| Prototyper | Chat-first generators | |
|---|---|---|
| Output runs in the workspace | Yes | In a preview pane, per thread |
| Canvas to compare versions side by side | Yes | No |
| Steer by pointing at the running screen | Yes | No, re-prompt in words |
| Bring your own agent and subscription | Yes | Their model, their meter |
| Same code continues to production | Yes | Export, then reassemble |
Prototyper's bet is different from both: an AI prototyping tool built as one surface, where the prototype is born, tested, revised, and shipped, with agents as participants rather than vending machines. Bring the agent you already pay for. Claude Code, Codex, Cursor, and Copilot all connect over MCP, and the Claude design page shows what that looks like end to end. For the thinking behind the workflow, the prototyping knowledge base is the long-form version.
The short version
Test your idea the day you have it
Describe the screen or sketch it; the agent builds it in real React while you watch.
Put it in front of users the moment it exists
What you learn is real because the prototype is.
Explore three directions at once
Branching costs a sentence. Keep the take that wins.
Keep the subscription you already pay for
Claude Code, Codex, or Cursor works on your canvas over MCP.
Ship the prototype instead of rebuilding it
No export cliff. The code that ran in the test is the code you take to production.
Frequently asked questions
- What is an AI prototyping tool?
- Software that turns a description or sketch into a working prototype using AI. The good ones produce real, running interfaces you can test with users, rather than images of interfaces or code you have to assemble elsewhere.
- What is the difference between a visual prototype and an interactive prototype?
- A visual prototype shows how a screen looks; an interactive prototype responds when you use it. Historically you chose one because working code was expensive. On an agent canvas the same artifact is both: arranged visually on the surface, fully operable the moment it compiles.
- How is Prototyper different from v0 or Lovable?
- Those are chat interfaces that produce outputs you take elsewhere. Prototyper is the shared workspace where the output lives, runs, and keeps evolving: a canvas for comparing versions, a team steering by pointing, and your own agent doing the building.
- Do I need to know how to code?
- No. You describe the outcome, the agent writes the code, and you steer by reacting to the running result. The code stays inspectable for anyone on the team who wants to read or edit it.
- Which AI agents work with Prototyper?
- Bring your own agent: Claude Code, Codex, Cursor, and Copilot connect over MCP on the subscription you already pay for. Prototyper is the workspace, not the model, so you are never metered per generation.
- Can I actually ship what I prototype?
- Yes. The prototype is real React running real logic, so shipping is a decision about scope rather than a rebuild. That is the whole case for an AI prototyping tool that runs its output: the version your users tested is the version you deploy.
Try it on the canvas.
Free to start, no credit card. Bring the agent you already have.