Maarten Boon

Co-founder of Uiprobe. Writes about visual QA and the gap between design and build.

Maarten Boon is a co-founder of Uiprobe, a visual QA tool that compares Figma designs against live webpages and reports property-level differences as findings.

Before Uiprobe he co-founded We Adapt, a data-driven video platform acquired by Bynder in 2020. Earlier he worked in post-production and at the creative studio Minivegas, where his interactive work was recognised at Cannes Lions, Eurobest, and the Webby Awards.

He writes the Uiprobe /learn articles and Help Center documentation.

Articles written by

Maarten Boon

Visual QA

Pixelay alternatives for Figma design QA in 2026

Pixelay alternatives for comparing Figma designs against live pages. Overlay tools, property-level comparison, and visual regression options compared.

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Visual QA

Design-to-code

Why Shopify themes drift from their Figma designs

Shopify themes drift from their Figma designs because the theme architecture sits between the design and the browser. Every layer in that system introduces places where the implementation can diverge.

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Design-to-code

Visual QA

How to check spacing differences between Figma and your browser

Spacing differences between a Figma design and a live page are the most common type of visual drift. They're also the hardest to catch by eye.

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Visual QA

Visual QA

Pixel-based vs spec-based design QA: how they differ

There are two fundamentally different approaches to comparing a Figma design against a live web page. Pixel-based comparison looks at what the page looks like. Spec-based comparison looks at what the page is made of.

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Visual QA

Design-to-code

How to compare your Figma design against a Shopify store

You can compare a Figma design against a live Shopify store the same way you'd compare against any other website.

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Design-to-code

Design-to-code

How to verify AI-generated frontend code against a Figma design

AI coding tools generate frontend code from Figma designs using MCP, but the output is not accurate by default. LLMs take shortcuts, approximate values, and drop design details when context runs long.

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Design-to-code
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