How to build prototypes that actually look like your product | Colin Matthews

How to build prototypes that actually look like your product | Colin Matthews

How I AIJun 30, 202532m

Claire Vo (host), Colin Matthews (guest)

Component-library-first prototypingScreenshot-to-components extractionForking to protect baselinesBrand/design-system consistency vs pixel-perfectMagic Patterns Chrome extension (DOM/HTML capture)Component versioning and “upgrade to latest”Prompting discipline and debugging without coding

In this episode of How I AI, featuring Claire Vo and Colin Matthews, How to build prototypes that actually look like your product | Colin Matthews explores aI prototyping with component libraries for brand-consistent product-like mockups fast Claire Vo and Colin Matthews demonstrate a workflow that makes AI prototypes look and feel like the real product by starting with a component library rather than generating full pages from scratch.

AI prototyping with component libraries for brand-consistent product-like mockups fast

Claire Vo and Colin Matthews demonstrate a workflow that makes AI prototypes look and feel like the real product by starting with a component library rather than generating full pages from scratch.

Colin shows how to capture UI elements from screenshots (e.g., Airbnb) to generate a reusable set of components, then “fork” a project to assemble new screens (home, detail pages) using those components for visual consistency and fewer errors.

They then demo Magic Patterns, including a Chrome extension that can select an element directly from a live website (e.g., ChatPRD) and convert the underlying HTML/styling into reusable components that can be versioned and upgraded across prototypes.

The conversation closes with team adoption tactics (empathy, positioning prototypes as communication artifacts), practical workflow discipline (checkpoints/versions/forks), and a debugging prompt pattern: ask the AI to explain what’s happening before writing code.

Key Takeaways

Start with components, not full screens.

Instead of prompting an AI tool to recreate an entire view, first force it to generate a library of primitives (logo, nav, cards, buttons). ...

Get the full analysis with uListen AI

Use screenshots to bootstrap a brand-consistent UI kit quickly.

Colin repeatedly feeds screenshots and prompts “continue adding components,” extracting recurring UX patterns. ...

Get the full analysis with uListen AI

Forking separates “design system assets” from “prototype experiments.”

Keep a master project as the component library, then fork it to build specific flows. ...

Get the full analysis with uListen AI

Aim for “recognizable fidelity,” not pixel perfection.

The goal is to avoid distracting stakeholders with unfamiliar UI, not to match every icon or image exactly. ...

Get the full analysis with uListen AI

Extracting from a live site can replace costly design-engineering help.

Magic Patterns’ Chrome extension lets you click a UI element on your site, capture its HTML/styling, and convert it into a reusable component—reducing dependence on engineers to manually package design-system code for prototyping tools.

Get the full analysis with uListen AI

Versioned components compound leverage across prototypes.

When components are published and reused, you can refine them over time and “upgrade to latest” in older prototypes. ...

Get the full analysis with uListen AI

Debug AI prototypes by forcing an explanation step first.

When the agent won’t behave (e. ...

Get the full analysis with uListen AI

Notable Quotes

The concept here is actually pretty simple… creating these components first, rather than starting with your views.

Colin Matthews

It is still a little challenging… The goal is typically to represent the product in a way that doesn't make people feel like you're talking about a different topic.

Colin Matthews

Don’t think about improving the composed application, actually think about improving the components, and then the composed application can follow downstream from that.

Claire Vo

When you've got something that works, the number one mistake is to keep vibe coding without a checkpoint or a commit or a version.

Claire Vo

Explain to me why this is happening. Don’t write any code.

Colin Matthews

Questions Answered in This Episode

What exact prompt structure do you use to consistently force “components only” (and prevent the model from recreating full views)?

Claire Vo and Colin Matthews demonstrate a workflow that makes AI prototypes look and feel like the real product by starting with a component library rather than generating full pages from scratch.

Get the full analysis with uListen AI

How do you decide the “minimum viable component set” before you stop extracting screenshots and start composing new flows?

Colin shows how to capture UI elements from screenshots (e. ...

Get the full analysis with uListen AI

What’s your process for stripping business logic from captured website code so components remain reusable in prototypes?

They then demo Magic Patterns, including a Chrome extension that can select an element directly from a live website (e. ...

Get the full analysis with uListen AI

In Magic Patterns’ Chrome extension workflow, what breaks most often (complex CSS, dynamic rendering, nested components), and how do you mitigate it?

The conversation closes with team adoption tactics (empathy, positioning prototypes as communication artifacts), practical workflow discipline (checkpoints/versions/forks), and a debugging prompt pattern: ask the AI to explain what’s happening before writing code.

Get the full analysis with uListen AI

How should teams handle governance/ownership: who maintains the component library, reviews changes, and decides what becomes “baseline”?

Get the full analysis with uListen AI

Transcript Preview

Claire Vo

Can you show us how you get these prototyping tools to prototype your product?

Colin Matthews

So here's our component. All I have to do is click Convert to Component, throw it into my ChatPRD library, and now it's going to import basically all of that styling and structure and regenerate it as, like, a proper component. So you can see the prompt here is basically all of the code from your website.

Claire Vo

You used to have to know how to code or get really good at Figma, and now we have unleashed the product manager with these chat-based prototyping tools. You have this prompt that lets you extract those components out of a screenshot.

Colin Matthews

So I'll say, "Create a homepage for Airbnb," and basically assemble a homepage using those components. You want to match your existing design with a screenshot, you can paste that in to start, then you add your new AI feature on top or whatever you want.

Claire Vo

Oh, look at this! It's Airbnb.

Colin Matthews

These tools can be used by anyone on the team. Your operations team could prototype something and then send it to you, or customer success could use these tools. There's no limit on who's allowed to have ideas. [upbeat music]

Claire Vo

Welcome back to How I AI. I'm Claire Vo, product leader and AI obsessive, here on a mission to help you build better with these new tools. Yeah, yeah, the word of the year is vibe code, but if I had to pick a close number two, it would be prototype. That's why I'm excited to have on Colin Matthews, who's gonna show product managers and designers how they can take screenshots and turn them into component libraries for your favorite prototyping tool to use, use a Chrome extension to rip your exact code to pull in to integrate with AI tooling, and how to use a fork to bring some sanity to your AI prototypes and designs. Let's get to it. This episode is brought to you by WorkOS. AI has already changed how we work. Tools are helping teams write better code, analyze customer data, and even handle support tickets automatically. But there's a catch: these tools only work well when they have deep access to company systems. Your copilot needs to see your entire code base. Your chatbot needs to search across internal docs, and for enterprise buyers, that raises serious security concerns. That's why these apps face intense IT scrutiny from day one. To pass, they need secure authentication, access controls, audit logs, the whole suite of enterprise features. Building all that from scratch, it's a massive lift. That's where WorkOS comes in. WorkOS gives you drop-in APIs for enterprise features, so your app can become enterprise-ready and scale upmarket faster. Think of it like Stripe for enterprise features. OpenAI, Perplexity, and Cursor are already using WorkOS to move faster and meet enterprise demands. Join them and hundreds of other industry leaders at workos.com. Start building today. Colin, thanks for being here.

Install uListen to search the full transcript and get AI-powered insights

Get Full Transcript

Get more from every podcast

AI summaries, searchable transcripts, and fact-checking. Free forever.

Add to Chrome