Where the AI Look Comes From
Ask AI to whip up a page and nine times out of ten you get the purple-gradient, frosted-glass, centered-headline trio. That sameness has a mathematical reason—once you see it, you know how to dodge it.
Below is a typical AI-generated landing page. It hides five high-frequency AI-look tells—tap them one by one. Each hit explains why that tell became AI's default move.
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The AI look had an older academic name. In About Face 4 Chapter 17, Cooper calls this stuff visual noise: extra visual elements that yank attention off what actually carries information. He lists seven forms. This "team weekly admin" hits all seven—check them off against the list.
Among the seven noises, "too many colors" has a proper name. About Face 4: colors crowded like a palette overwhelm users—that's the carnival effect. Max out saturation and the noise doubles, stealing the scene from content. Same weekend-market flyer, two palettes—tap the one people can actually read.
When AI generates design, it picks the high-probability region of training data—the "average" of web design. Same mechanism as language hallucination: in conversation, fluent beats true; in design, common beats good. It ships the purple-gradient trio the way it invents a nonexistent book title with a straight face: both pick the answer that "most looks like it belongs here."
Good news: the mechanism leaves a door open—the probability distribution shifts with input. The more specific your description, the narrower the model's options. Narrow enough, and you pull it off the average.
Same brief, three levels of specificity—watch the output change.
The AI look has a source: models default to high-probability training regions—the average of web design. The purple-gradient trio is that region's storefront.
Visual noise has a pathology list: over-decoration, info-free 3D, heavy separators, crowded elements, dense color/texture contrast, too many colors, weak hierarchy—seven from About Face 4. Colors jammed like a palette even have a name: the carnival effect.
Same mechanism as hallucination: in chat, fluent beats true; in design, common beats good. Wherever you gave no instruction, it fills in the most common answer.
The fix is cranking specificity: a reference plus checkable hard constraints (one primary color, no gradients). Each notch pulls output farther from the default look. Next time before AI generates a page, put these five tells on a ban list.
Source: Original to Xiaoshan Academy's Taste Engineering series; some design principles adapted from About Face 4, Chapter 17.