How Layer recommendations adapt over time

Tell Layer how an outfit felt so future recommendations can lean toward you.

Layer starts with the weather and the run you have planned. Your post-run feedback helps it lean toward how those conditions feel to you.

Tell Layer how the run felt

After an eligible logged run, Layer asks for a five-point comfort read:

  • Too cold
  • A bit cold
  • Just right
  • A bit warm
  • Too warm

Layer also asks what you wore. It uses a comfort read only when it has enough evidence that the outfit recorded for the run matches what you wore and the conditions stayed close enough to make the answer useful. If it cannot verify that, your answer can stay in the log without changing your calibration.

Changes are gradual

One unusual run should not swing every recommendation. A repeated pattern matters more than a single answer, so changes appear gradually across similar conditions.

Layer may show a short personalization line that describes the direction it is leaning. It does not show confidence scores, internal thresholds, or a progress meter because those are not decisions you need to make.

What does not teach the recommendation yet

Imported Strava history does not currently train Layer's outfit recommendations. Learning comes from the post-run comfort feedback you give inside Layer.

Your learned comfort calibration currently stays on that device. It is not included in CloudKit sync, so it will not return after deleting and reinstalling the app.

Still need help? Email help@layertoday.com.