The internal AI tool that’s transforming how Stripe designs products | Owen Williams

May 4, 2026

AI Summary

5 min read

At Stripe, design manager Owen Williams found himself sitting in design reviews where prototypes built with AI tools like V0 looked wrong. The fonts were off. The navigation was odd. The dashboards had that generic “blurple slop” that comes from an AI that doesn’t know your design system. So Williams spent eighteen months building an internal tool called Protodash — a highly opinionated prototyping environment that bundles Stripe’s design system components, cursor rules, and an MCP server so that anyone (designer, PM, or otherwise) can generate realistic, on-brand dashboards from a browser. The result: prototypes that look so convincing that Williams sometimes can’t tell if he’s looking at the real product or a fake.

The problem with AI prototypes and design systems

The core friction Williams identified is that general-purpose AI coding tools like V0 or Cursor have no awareness of a company’s internal design system. A designer can prompt a dashboard, and the AI will produce something that looks plausible — but the nav will be wrong, the fonts will be off, and the components won’t match the production experience. “It’s very immersion breaking,” Williams says. At Stripe, where the quality bar is high, bringing a sloppy prototype to a design review undermines the whole point of prototyping: to test and communicate ideas clearly.

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What you'll learn

1 (00:00) **The Core Problem: Generic AI Prototypes** - Owen introduces the challenge of designers getting AI-generated prototypes that look like generic "blurple slop" because the AI doesn't know Stripe's design system.
2 (04:00) **Protodash: The Internal Prototyping Solution** - Owen built an internal tool called Protodash that bundles cursor rules and React to let anyone create realistic Stripe-like dashboards quickly.
3 (05:38) **The Engineering Background as a Superpower** - Owen explains his unique path from engineering to design management and how that technical foundation made Protodash possible.
4 (07:37) **V1 Architecture: Rules, MCP, and Design System** - The first version combined a router, design system components (SALE), an MCP server, and bundled rules to teach Cursor how to build properly.
5 (09:04) **From Local to Cloud: Dev Boxes** - Owen solved the problem of running prototypes locally by leveraging Stripe's dev box infrastructure for instant, shareable URLs.
6 (10:46) **The Data Dashboard Prototyping Nightmare** - Claire highlights how painful it is to prototype data-heavy dashboards in Figma, and Protodash solves this by working with real data and states.
7 (14:49) **V2: ProtoDash Studio - Browser-Based Vibe Coding** - Owen built a web-based layer so users can prototype entirely in the browser without needing Cursor or a local setup.

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Show Notes

Owen Williams is a design manager at Stripe who built Protodash, an internal AI-powered prototyping platform that lets designers and PMs create high-quality Stripe dashboard prototypes without writing code. What started as a bundle of Cursor rules and React components evolved into a full web-based prototyping studio that runs in dev boxes, complete with design review modes, variant testing, and AI-powered iteration. Surprisingly, PMs now use Protodash just as much as designers, fundamentally changing how Stripe approaches prototyping, design reviews, and engineering handoffs.

What you’ll learn:

How Stripe built an internal AI prototyping tool using Cursor rules, MCPs, and their design system
Why “blurple slop” happens when designers use generic AI tools—and how to fix it
The architecture behind Protodash: React router, design system components, and MCP integrations
How Stripe prototypes in dev boxes so designers never have to worry about local setup
Why “demos, not memos” transformed Stripe’s design review culture
How Stripe built design review modes, variant testing, and AI annotation directly into your prototyping tool
Why internal tools don’t need to be production-grade to be transformative

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Brought to you by:

Celigo—Intelligent automation built for AI

Cursor—The best way to code with AI

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In this episode, we cover:

(00:00) Welcome and intro to Owen Williams

(02:19) The “blurple slop” problem with AI design tools

(03:50) Protodash: an internal vibe-coding tool for Stripe prototypes

(05:26) Why an engineering background helped Owen lower the bar for designers

(07:55) The Cursor rules that taught the Stripe design system

(09:04) Running prototypes on dev boxes vs. locally

(10:30) “Demos, not memos” and rewiring design reviews at Stripe

(14:50) Building Protodash Studio: a browser-based wrapper for prototyping

(19:04) Live demo: variants, line charts, and remixing prototypes in browser

(21:02) Self-testing prototypes that take screenshots and check their work

(23:20) Multiple variant features

(26:08) The annotate-for-AI button for in-canvas feedback

(27:21) Design review mode: comments, summaries, and AI follow-up

(29:39) Why building internal tools beats buying off-the-shelf

(32:50) PMs as the surprise power users of Protodash

(35:20) Live demo: a Black Friday/Cyber Monday pet store dashboard

(42:03) Lo-fi modes, monospace fonts, and “Comic Sans for WIP” at Shopify

(44:45) Quick recap

(45:35) The Radar prototype that changed engineering hand