Wore Instead
“Wore Instead” is the most informative type of feedback you can give. Instead of just saying “no” to a suggestion, you show the AI exactly what you chose to wear. This captures the “not this, but that” pattern that a simple reject can’t express.
The wore-instead flow is now powered by Outfit Studio, which turns your actual outfit into a real, saved, reusable outfit rather than a throwaway picker selection. The full details of that flow live on the Outfit Studio page.
How It Works
When giving feedback on a suggestion, one of the options in the first step is “I wore something else instead.” Selecting this opens Studio seeded with the rejected suggestion’s items so you have a starting point to modify, and with a link back to the original suggestion set automatically.
Swap items to match what you actually wore, then save. The new outfit is recorded as your wear for the day and feeds into the learning engine.
Why This Matters
A rejected suggestion tells the AI “this wasn’t right.” A wore-instead tells it “this wasn’t right, and here’s what was.” The system can then identify swap patterns.
Examples of what it learns:
- You often swap the suggested trousers for jeans when the occasion is casual.
- You consistently choose a different jacket than the one suggested on cold days.
- On office days, you prefer the structured blazer over the cardigan the AI keeps suggesting.
These patterns get extracted and fed back into the recommendation prompts, so future suggestions start steering toward what you actually reach for.
Wore Instead in the Outfits Tab
In the calendar view of the Outfits tab, outfits created through wore-instead appear on the day you wore them, marked with a replaces link back to the original suggestion. The card shows the items you actually wore, not the rejected suggestion.
This makes your history more accurate. Instead of a feed full of “rejected” outfits, you get a record of what you actually wore each day, regardless of whether you started from a suggestion.
Building Better Recommendations
Wore-instead data is one of the strongest ways to improve suggestions quickly. If you consistently tell the app what you chose, it builds up a clear picture of your real preferences rather than just knowing what you didn’t like.
The more wore-instead data you provide, the faster the suggestion quality improves. See Style Learning for how this data appears in your profile.
Mobile: The wore-instead picker is a full-screen wardrobe browser. Tap items to select them, then tap “Done” to save the selection. Multi-item selection works the same as on web.