How to turn an idea into a prototype with AI

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February 14, 2025

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How to turn an idea into a prototype with AI

Imagine being able to take an idea, explore different design possibilities, and create a working prototype—all within an hour. Not just a simple visual draft in Figma, but a fully functional, code-powered prototype. And what if you could achieve all of this with minimal coding experience?

In this article, I’ll walk you through a step-by-step experiment where I did just that. The process involved drafting the requirements, generating wireframes, building a prototype, and making necessary revisions—all with the help of AI tools.

Defining the Requirements

To kick things off, I asked Claude AI to generate a simple product requirement document. The goal was to create a platform where users could:

Write and publish notes

Browse notes from other users

Interact with content through likes, reposts, and comments

View user profiles

Sort notes by categories

While the generated PRD was quite thorough, it was more complex than I needed. So, I simplified it, fine-tuning the details to keep the project manageable.

Using AI like Claude or ChatGPT to generate prompts can be a great starting point. However, copying and pasting responses directly into other AI tools isn’t always the best approach. Instead, pick the relevant parts, simplify them, and tailor them to your specific needs. This gives you more control and helps optimize token usage.

Generating Wireframes

Rather than jumping straight into prototyping, I decided to explore some design options first. While Claude could generate basic wireframes, it wasn’t ideal for creating detailed, usable designs. Instead, I used UX Pilot, a tool I had previously explored.

I broke the simplified PRD into sections, feeding each page’s details into UX Pilot one at a time. For example, my homepage prompt included navigation tabs (Following, Discover), a category filter bar, and post cards with author details, engagement metrics, and timestamps. Using UX Pilot’s Figma plugin, I generated three design variations per page, refining them as needed.

While UX Pilot’s web platform offers features like auto-generating full user flows and exporting wireframes to Figma, these were behind a paywall. To work around this, I generated wireframes page by page in the plugin.

Creating a Prototype

With the wireframes ready, it was time to turn them into a working prototype. While Claude can handle some basic prototyping tasks, I needed a more specialized tool. I chose Bolt, an AI-powered platform that transforms text prompts into full-stack applications.

Built on StackBlitz, Bolt allows you to:

Install and run npm libraries

Deploy applications directly from the browser

Share projects via a simple URL

This eliminated the hassle of local setup and installation, which I had dealt with in previous projects.

First Attempt

I asked Bolt to generate a prototype based on my wireframes. It initially used NativeScript to build a mobile app and provided a QR code for previewing it. However, I preferred a web-based version for easier accessibility. Upon request, Bolt switched gears and rebuilt the app using React and Vite.

Refining the Prototype

Bolt’s first version was functional but had some missing details, visual inconsistencies, and lacked interactivity. Instead of manually fixing these issues in code, I refined the prototype using natural language instructions:

Design tweaks: Fix layout inconsistencies, add a floating button, and adjust the tab bar.

Interactive elements: Enable the “like” button to change states when clicked, and make the “+” button trigger an add/edit drawer that closes when clicking “x.”

Although I had to iterate on these details one by one, the process was smoother than expected. I even used screenshots from the wireframes to visually guide Bolt in refining the design.

Bolt provides 200,000 free tokens daily. Depending on your project’s complexity, you might use them up quickly. To maximize efficiency:

Start with a detailed initial prompt to minimize revisions.

Specify upfront whether you’re building a web or mobile app.

Use snapshots for precise visual references.

Combine multiple revision requests into one message.

Even after reaching the token limit, I could continue working using Bolt’s code editor with Claude’s assistance.

This experiment showed how AI-powered tools can drastically streamline the product development process. From ideation to a functional prototype, what once took weeks can now be done in hours. However, efficient prompt engineering, tool selection, and token management are key to getting the most out of AI-driven workflows.

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