> There are other aesthetics my brain associates with AI, like beige/cream colors, orange accents, and serif typefaces
Something to consider regarding the narrow space AI-created designs align on: LLMs are trained to write consistent code. This makes sense for something like a billing or a backend function - you want that code to be consistent. The problem though is that LLMs write code to represent designs as well, which means you get consistent designs. You end up aligning on a generic mean because of it, which is often why you see these repeated aesthetics.
It was something I saw when I was working on AI tooling over at Figma. It was very hard to get creative, unique outputs out of LLMs.
One thing I'd recommend if you're trying to avoid this is try a diffusion model as a starting point. Gpt-image-2 is a VERY capable designer, and Opus and Fable are fantastic at converting images to webpages. Starting with images will let you sidestep a lot of the uniformity of output that LLMs have. I'm heavily biased here as this is what I left figma to build (https://news.ycombinator.com/item?id=48995754), but even starting with gpt-image-2 to give you a general sense of the look/feel will heavily differentiate you on the design front.
Here are some examples of image->webpage outputs I've been playing with:
For Tarot, did you generate base-color, roughness and normal maps? How do you make sure something like the roughness map doesn't deviate slightly from the base-color?
But basically diffui's build step provides an API to create normal/roughness/depth maps from images. It's essentially an interface to fal.ai's Patina model, which does a really good job at creating those.
The one thing that's missing with it though is metalness maps (Patina can theoretically output them, but they only have a ~10% success rate I've found). I'm trying to train my own diffusion model now to help generate those so the reflectivity isn't fully uniform. I just posted very, VERY early results here - right now my model has around a ~25% succes rate: https://x.com/pwnies/status/2082980850120163756
Ha! Totally fair. 13 cents is 0% margin, which is what I'm targeting for individual plans.
I literally just got my SOC2 compliance complete an hour ago, and I'm gonna roll out team plans/enterprise plans next week (unified billing + shared brands). For teams I'm gonna charge a flat 25% margin on API costs, and for enterprise I'll have a 50% margin + minimum spend.
I think I'm going to keep the individual plans at 0% though. Realistically until my own diffusion models I'm training are the main model I'm using for generation, I'm just an API wrapper + harness. At the individual level I want to be competitive with going directly to the api and coding your own harness.
I am curious though - what would you pay per image?
A few layers to it. When you prompt on my product I expand out that prompt into a semantic json blob that represents the style, theme, color palette, and subjects on the screen. I then feed that blob into the diffusion model itself.
The reason I feed in the json blob is it lets me better preserve subjects across multiple screens (ie you probably want to carry over the header exactly as it is in one image to another image).
The example sites above though were pretty simple. I think they were something like
"A tarot card website with an inky, painted artistic style, with rich illustrations on a card featured on the left, and a button to draw cards on the right"
> The problem though is that LLMs write code to represent designs as well, which means you get consistent designs. You end up aligning on a generic mean because of it, which is often why you see these repeated aesthetics.
The funny thing is that looking like everyone else was once considered the definition of good UI design, because it helps users understand a new interface. Then mobile apps came and suddenly UI design was about “expressing your brand” or whatever.
I think it's important to separate patterns from aesthetics. Patterns help us understand a new interface for sure, but aligned aethetics start to look mundane. That's why I was specifically calling out the color usage and typefaces.
I actually think the other things that Jim mentioned, such as the async task gradient / standard sidebar for agents are good things.
I think that if the images were replaced by human made (you can take photos of real things if you don’t want to draw or hire an actual artist) perhaps the design could be more passable
An irony to this is that the front-ends generated by older models are gonna end up looking distinctive. If you rock a Claude Sonnet 3.7 (or was it Sonnet 4) mid-2025 purple gradient background forever you've set yourself well apart
There's definitely a lot of AI-generated websites, especially for dev tools & SaaS, that love to have dark backgrounds, cool colors (purple especially is making a resurgence it seems), and tons of fancy UI widgets.
A lot of these things are continuations of previous trends too. The shimmering text effect is strongly reminiscent of skeleton UI, only repurposed for chat interfaces. As always, design is more continuous evolution than discrete shifts.
Interesting observations. It's fascinating how a handful of companies' design decision can quickly spread to the entire industry. I still remember when everyone was emulating Stripe or 37signals before that.
The defining "AI" aesthetic is the TUI, for better or worse.
The real question is what the post-AI aesthetic will be, and at a guess it will bifurcate into obsessive recreations of earlier happier pre-AI times, and some sort of opposite extreme of videos of Chinese cities covered in LEDs.
Perhaps amongst coders, but I doubt most users are interacting with TUIs - my retired mother uses ChatGPT most days, but I suspect it'll be a while before she downloads Claude Code.
Is the "'shimmering text' for waiting" thing really that recent? I feel like that is a bit older, but maybe I am wrong. I have more and more difficulty remembering how long things have been around as I get older.
The tiny icons are good. There was a touch device fad that surfaced, and is subsequently dying, now that people realise that using laptop screen realestate more efficiently helps those doing actual work.
How could an article on the AI aesthetic not mention the curiously anatomical company logos?
On a more serious note, I like the tiny icon trend as depicted in the article. Those little icons next to menu text are pretty ornamental, and don't need to be as big as they usually are.
Oh, huh. I was focused on the scale but you’re right, they are kind of wispy. That reminds me of the anorexic typography trend from ~2013. It’s probably intended to convey sophistication.
Another AI-ism is the use of the word "grain" in technical contexts. I'm confident the OP is human-written, but everything in my AI-supported codebase is about grains, seams, tracer bullets, and load-bearing components now.
I'd barely heard some of these words before, and now they're everywhere. It's like everyone suddenly has a friend who speaks in the same idiosyncratic way, and we're all picking up their vocal stims.
This has been a growing problem with humans for a while. Go back ten years and use "guardrails" or "top of mind" in a conversation and you'll get baffled looks. For whatever reason the fad based enthusiasm for semi jargon is a widespread affliction.
In the english speaking world the political sides are even becoming unsubtly linguistically distinct. You can tell which way someone votes by their choice of vocabulary.
There are like 43 tiny icon libraries and frameworks for web design. AI didn't start this trend at all. This article is just "put AI in the title and it will get attention" and apparently it works.
Something to consider regarding the narrow space AI-created designs align on: LLMs are trained to write consistent code. This makes sense for something like a billing or a backend function - you want that code to be consistent. The problem though is that LLMs write code to represent designs as well, which means you get consistent designs. You end up aligning on a generic mean because of it, which is often why you see these repeated aesthetics.
It was something I saw when I was working on AI tooling over at Figma. It was very hard to get creative, unique outputs out of LLMs.
One thing I'd recommend if you're trying to avoid this is try a diffusion model as a starting point. Gpt-image-2 is a VERY capable designer, and Opus and Fable are fantastic at converting images to webpages. Starting with images will let you sidestep a lot of the uniformity of output that LLMs have. I'm heavily biased here as this is what I left figma to build (https://news.ycombinator.com/item?id=48995754), but even starting with gpt-image-2 to give you a general sense of the look/feel will heavily differentiate you on the design front.
Here are some examples of image->webpage outputs I've been playing with:
https://html.non.io/tarot/
https://html.non.io/neonRamen/
But basically diffui's build step provides an API to create normal/roughness/depth maps from images. It's essentially an interface to fal.ai's Patina model, which does a really good job at creating those.
The one thing that's missing with it though is metalness maps (Patina can theoretically output them, but they only have a ~10% success rate I've found). I'm trying to train my own diffusion model now to help generate those so the reflectivity isn't fully uniform. I just posted very, VERY early results here - right now my model has around a ~25% succes rate: https://x.com/pwnies/status/2082980850120163756
I literally just got my SOC2 compliance complete an hour ago, and I'm gonna roll out team plans/enterprise plans next week (unified billing + shared brands). For teams I'm gonna charge a flat 25% margin on API costs, and for enterprise I'll have a 50% margin + minimum spend.
I think I'm going to keep the individual plans at 0% though. Realistically until my own diffusion models I'm training are the main model I'm using for generation, I'm just an API wrapper + harness. At the individual level I want to be competitive with going directly to the api and coding your own harness.
I am curious though - what would you pay per image?
The reason I feed in the json blob is it lets me better preserve subjects across multiple screens (ie you probably want to carry over the header exactly as it is in one image to another image).
The example sites above though were pretty simple. I think they were something like
"A tarot card website with an inky, painted artistic style, with rich illustrations on a card featured on the left, and a button to draw cards on the right"
and for the other it was something like,
"A cyberpunk inspired ramen cart website"
The funny thing is that looking like everyone else was once considered the definition of good UI design, because it helps users understand a new interface. Then mobile apps came and suddenly UI design was about “expressing your brand” or whatever.
I actually think the other things that Jim mentioned, such as the async task gradient / standard sidebar for agents are good things.
First, they took my em dash. Now, they’re taking my neutral background with orange accents.
(Randomly, I love the Solarized colour schemes, so anything similar is great, vibe-coded or not.)
Speaking of this, GitHub replaced theirs with a pancake emoji.
Maybe related to the stacked pull-requests announcement earlier today.
[0]: https://github.github.com/gh-stack/
The real question is what the post-AI aesthetic will be, and at a guess it will bifurcate into obsessive recreations of earlier happier pre-AI times, and some sort of opposite extreme of videos of Chinese cities covered in LEDs.
It generally stood for either:
- fireworks (combined with other firework emojis,)
- birthdays/festivals (next to the birthday cake and "party popper" thing emoji,)
- magic (next to the wizard or wand, which features almost identical sparkles)
It was pretty festive. Now it's just AI, lol.
The bubble in tech is pretty strange but I digress
On a more serious note, I like the tiny icon trend as depicted in the article. Those little icons next to menu text are pretty ornamental, and don't need to be as big as they usually are.
I'd barely heard some of these words before, and now they're everywhere. It's like everyone suddenly has a friend who speaks in the same idiosyncratic way, and we're all picking up their vocal stims.
In the english speaking world the political sides are even becoming unsubtly linguistically distinct. You can tell which way someone votes by their choice of vocabulary.
Midjourney has a definite aesthetic.
Minimax has one. Stable Diffusion definitely (ugly, but free )
Sora everything is rendered in Octane lol
If it’s cartoon or animated it’s Ghibli.
I have not noticed “orange” as a particular AI trend.