Generating Beautiful UIs May 08, 2026

With contributions from Sherif Cherfa and Halley Chang There’s an intuitive skepticism we have toward AI-generated work. We see it clearly in writing, where the patterns have gotten familiar and punctuation (the em dash — ) has become a universal signal that AI has been used. Design has lagged behind writing, but it’s catching up. Recent models can produce better UIs, yet it still requires heavy hand-holding and prompt “band-aids.” Overall, AI-generated designs often lack that feeling of deep satisfaction, joy, or whimsy that human designers create. Basic prompts produce boring outputs Media theorist Marshall McLuhan is often credited for his beliefs on the co-evolution of humans and tools: “we shape our tools, and thereafter our tools shape us.” Although AI can create superficially “beautiful” designs, they’re often shallow. When you give a model a generic prompt, you get a generic output. When your intentions lack direction, so will the result. For example, here’s a basic prompt we used: "Hello! I want you to build me a website for my computer parts recommendation business, it should look nice, use dark mode." What we get is boring and predictable: - Classic dark background - Overuse of cards - Side shadows on boxes - Interfont - Hero section with gradient text - Feature section with three columns - Classic footer with social icons that we never asked for We see patterns in AI outputs much like we see patterns in writing. There are even guides, Signs of AI Writing that flag it. While testing generic prompts, we similarly developed a checklist of common AI-design “tells”: - Everything becomes a dashboard There's a chronic let's make everything look like an AI SaaS dashboard even if it's not supposed to be one. That every single AI model seems to have. And even if you are trying to build a landing page for a bakery or a portfolio website, if you squint hard enough, you can almost always mistake the website for a dashboard. And the reason is mostly statistical for why we constantly get SaaS dashboard specifically. A lot of the modern web and UI training data is heavily biased towards SaaS products, dashboards, component libraries, and startup landing pages - Cards inside cards One of the most reliable, obnoxious tells. The AI wraps content in a card, then realizes it needs to organize content inside that card, so it adds more cards. The result is nested containers all the way down. See the example prompt: ‘Build me an email client for children’ - Over-coding and unwanted refactors Perhaps one of the most frustrating things is when your design is 99% of the way there and you need a small tweak. Ask for a simple button change and the AI refactors the entire component tree. Ask for a simple API call and it rewrites unrelated error handling or adds types you didn't ask for. This is one area where fast and scoped models like Codex-Spark (1200 tokens/second on Cerebras) shine. It tends to do…