Recently I've seen more people calling out how AI-designed sites all look the same (meaning ugly?). I decided to dig into why that's happening.

Models learn patterns, not design rules

Vibe coders are trained on huge datasets of HTML, CSS, and screenshots. They don't learn taste or visual hierarchy, only what repeats most often. If purple gradient buttons show up in a lot of examples, those become the "safe" choice. Same with glowing cards, gradient headlines or rounded corners.

The model doesn't understand when to use those things. It only learns that they are popular. So when it generates a page, it stacks everything that scored high in the data. The result looks busy, loud, and artificial, even if each part came from real aesthetic designs.

It's like an intern who goes to Pinterest, finds the best-looking pieces, and uses them all at once, because they all look great. Separately. On different pages. Or even different projects.

Knows structure, not restraint

These models understand structure fairly well. They know a landing page has a header, a hero section, a list of features, maybe testimonials and a footer. That's easy to learn because those elements appear in a predictable order.

What they don't learn is visual restraint. They can build the bones, but they don't know that only one part of the layout should attract attention. They can place a hero section correctly, but they don't know that background and cards shouldn't all fight for focus at once.

Training data favors flashy components

A big part of the sameness comes from what's easy to scrape. Dribbble, Behance, and UI showcases are full of isolated components with strong colors, gradients, shadows, and motion. Those are clean, easy to parse, and labeled. Real websites are harder to process and often more restrained, so they don't appear as clearly in training data.

The model ends up focusing too much on flashy standalone components. It learns from what looks exciting on a single card, not from what works on a big picture. When you ask for a full layout, it combines all the shiny pieces it knows instead of understanding how they visually balance each other.

Prompting acts as a design filter

Since the model doesn't come with taste, prompts act as guardrails. A vague instruction like "modern, vibrant startup website" usually results in the typical purple gradient soup, spiced up with shadows, rainbow icons, and corners that are either too sharp or too soft.

A more precise prompt like "minimal layout, one accent gradient on the CTA, flat neutral background" forces the AI to stay within limits.

Prompt templates exist because the model can't manage style consistency on its own. They're how you apply design rules — until the tools learn to do it better.

Let's not be too judgmental or demanding. It's still early days for all this tech. Remember the early Midjourney images? Yeah. I think AI vibe coders are somewhere around the happy people with six fingers stage right now.

Could this be fixed inside the model

Yes, in theory. It would require training on complete, labeled websites, not just fragments. The system would need to learn relationships between sections, visual hierarchy, and when repetition hurts clarity. That kind of dataset barely exists right now, and it would take real human annotation to build.

Until then, the only way to get coherent results is to guide the model with clear constraints. Guardrails inside the model will come eventually, but for now the designer's direction still matters more than the generator.