Notes from building an AI design collaborator · part 8
How do you teach an AI your taste?
· 3 min read
You can write down a design system. You can write down your process. You cannot write down your taste, which is annoying, because taste is most of what makes a designer a designer.
Taste is the thing that goes "no, not like that" without always being able to say why in the moment. It's the reason two designers with the same brief and the same components hand back different work. So when I started leaning on an AI for real design work, this was the part I was sure it would never get. And mostly it didn't. It would do something slightly off, I'd correct it, and next week it would do the exact same slightly-off thing again, cheerfully, like we'd never met.
The correction that evaporates
That's the real problem. Not that the AI has bad taste. It's that your corrections evaporate. You fix the same thing forever because nothing you say sticks past the session.
So I built a feedback loop. Two ways in. One is passive, it just watches what I accept and what I throw out and quietly notes the pattern. The other is me saying it out loud, "no, we always do it this way," when I catch something.
Each of those becomes an entry in a profile. Not a global rule for everyone, a profile per designer, because my taste and my teammate's taste genuinely differ and pretending otherwise flattens both.
The part I almost got wrong
Here's the trap I walked into. The first version turned every offhand comment into a hard rule instantly. I muttered one thing about spacing on a bad day and the AI treated it as law forever after. That's worse than no memory, because now it's confidently wrong in my name.
So a preference doesn't become a rule the first time I say it. It starts as a candidate. Only when the same thing shows up again, when it's clearly a pattern and not a mood, does it get promoted to something the AI actually follows. Say it once, it's noted. Say it twice, it counts.
That one guard is the difference between an AI that learns your taste and one that over-fits to your worst Tuesday.
Taste can't be specified up front, but it can be accumulated. The move is to capture preferences as rules you can promote, not corrections you repeat, and to make the AI earn a rule before it trusts it. Do that and the thing slowly stops doing the slightly-off version. Which is about as close to "it learned my taste" as I need it to get.
Part of a series on building an AI collaborator for our design team at Xflow. Each post stands on its own.
- ai
- design-craft
The rest of Notes from building an AI design collaborator
- 1. I stopped describing my product to AI. I just gave it the HTML.
- 2. I gave the AI my design process, not my design decisions
- 3. I turned my design process into a dozen small skills, not one giant prompt
- 4. I built a free tool that gives your AI your real product
- 5. I taught the AI to push designs into Figma. Then it quietly stopped.
- 6. We rebuilt our Figma design system out of the code, not the other way round
- 7. We ran our design process on itself, and it broke in useful ways
- 9. It worked great on the smart model. Then I ran it on a cheaper one.
- 10. The AI told me our brand colour with total confidence, and it was wrong
- 11. A screen list lies. I found a whole feature I didn't know we shipped.
- 12. Our documentation updates itself, because updating it is the AI's job
- 13. I sat down to turn my workflow into a swarm of agents. Most of it refused.
- 14. Every modal in our app shared one URL. Our analytics couldn't tell them apart.
- 15. My AI's rules only worked because one tool bothered to read them
- 16. Six designers, one GitHub account, and a script that saves us from ourselves
- 17. "Out of scope" usually means "we'll repaint this in six months"