AI builds my screens in minutes. Design taste is still the slow part. The five calls I make myself, with real examples from my shipped AI experiments.
The design taste AI can't copy is the judgment that tells you which of ten good-looking options is right for this product, these users and this moment, and what to remove. It is the part of the job that did not get faster. Claude can build a screen from my Figma frame in minutes, and a video model can animate it, but neither one knows when the result is generic, when the motion lands two percent off, or when a "swipe up" feels cheap in the hand. I wrote it this way in a post on X after shipping my experiments: "The taste is still the slow part. Good. That's the part that's ours." This post is about what that slow part looks like in practice, the five calls I still make myself, and how a designer can train them.
"What is design taste" is the most searched version of this question, and most answers stay abstract: a sense of beauty, a refined eye. I think that definition is too soft to be useful once AI is in the room.
Here is the version I work with. Design taste is a series of small decisions you can defend:
AI changed the cost of everything around those decisions. It did not make the decisions. In my AI design workflow from idea to App Store, the first build takes minutes. Making it feel right takes the evening. That evening is taste.
These come straight from how I build the projects on my AI design experiments page. Each one is a moment where the model gave me something reasonable, and the right answer was something else.
I do not start in Figma. I start by collecting: Dribbble and Behance for the feeling, real products and Mobbin for how things should work, and AI images for the world the product lives in. For the Hywith forest landing page, I generated the forest first, with light rays, moss and little flowers, and only then designed the product on top of it. As I put it on X: "When the world exists first, the UI has somewhere to live." An AI can generate a thousand forests. Picking the one that makes the product feel calm instead of decorative is the call.
Every project I shipped this year has one moment people remember: water pouring into a glass in Pulse Health, a glass ball that fills under your thumb in Rare Box, a character whose eyes follow your cursor in Jane Noah. I design that moment first, and the rest of the screens support it. A model will happily give equal weight to every screen. Deciding where the weight goes is taste.
In Figma, the Rare Box said "swipe up to open." Then I had it on my phone, and swiping felt cheap. So I asked for hold instead. Now a glass ball appears under your finger, fills while you hold, dives into the box, and the card bursts out. No frame in the file told me that. Only using it did. In the old handoff days, that change would have died in a ticket. Now I can feel it the same evening and change it.
On one landing page, the video model made a beautiful sky, and then quietly added raindrop rings to the lake. On a sunny day. On another project, a model re-rendered every clip about 2% zoomed, so the whole design jumped the moment the video started over the still frame. You only catch that if you stare at it like a designer. My fix both times was a rule, not a prompt: keep the clip where it is good, and build the rest in code.
"Skip the thinking and you get the same generic page everyone else gets." That line from my first X post on shipping instead of handing off still sums it up. The model's default is the average of what it has seen: a centered hero, a gradient, three cards. Taste is noticing that the result is average even when nothing is technically wrong, and pushing past it.
| Step | What AI does well now | Where taste decides |
|---|---|---|
| References | Generates endless moods and worlds | Picking the one that fits the product and its users |
| Layout | Builds screens from Figma frames through the Figma MCP | Which screen carries the wow moment, what to remove |
| Motion | Video models animate between a first and last frame | Spotting drift, odd pacing, things nobody asked for |
| Interaction | Writes the gesture, the physics, the states | Whether it feels right on a real device |
| Sound | Generates SFX and music on demand | When sound helps, and when silence is better |
| Shipping | Deploys a live link in minutes | Deciding it is ready, and what not to ship |
Models are getting better at the surface of taste. They pick nicer type pairings than they did a year ago, and they follow a strong reference well. But taste is not a style. It is a judgment tied to a context: this user, this product, this constraint.
At ViewStats, the creator platform built by the team behind MrBeast, the biggest insight was that creators were not asking for more charts, they wanted confidence about what to make next. "People rarely want more information. They want clarity." No reference board would have told you that. It came from interviews, onboarding analytics and the Discord community. The full story is in the ViewStats creator tools case study. That is taste too: knowing which problem the interface should solve before deciding how it looks.
So my honest answer: AI can imitate the results of taste when you show it good references. It cannot yet decide what matters for your users. That is still the designer's job, and I think it is the most valuable part of it. I made a similar argument in will AI replace product designers.
The good news: AI makes taste easier to train, because you can see more versions faster. A few habits that work for me:
None of this is a magic prompt. People ask me for "the prompt" all the time. There is no such thing. There is a proper design first, a clear idea of how each piece should behave, and a lot of small, boring fixes.
It is knowing which option is right for a specific product and user, and what to leave out. Taste shows in the choices you can explain, not in a style you repeat.
Not today. AI can produce many good-looking options and follow strong references. It still needs someone to decide which option fits the context, and to notice when the result is generic or subtly wrong.
Look at a lot of real products, collect references with a reason attached, build things and use them on a real device. AI helps here: you can try ten versions of a moment in an evening and learn why one works.
Apps built from default prompts already look the same. Apps built from a clear design, a chosen mood and one strong moment do not. The gap between those two groups is getting wider, not smaller.
I am curious about your side of this. Which part of your work got faster with AI, and which part still feels slow in a good way? If you want that slow part applied to your product, you can work with me as your product designer.
If you have a web or mobile app idea in mind or you need some advice about product design, feel free to get in touch ✉️