Hi WHOOP Team,
I’m a long-time WHOOP member, and I’d like to share an idea that I believe could make WHOOP one of the most intelligent and personalized wearables on the market.
Personal AI Event Training
I would love to see a feature that allows each user to teach WHOOP to recognize their own custom activities.
For example:
- I tap “Train New Event”.
- I give it a name (Shower, Phone Before Bed, TV, Reading, Meditation, Gaming, Walk, etc.).
- During that period, WHOOP records all available sensor data (HR, HRV, motion, skin temperature, accelerometer data, and any other available signals).
After several labeled sessions, an AI model trained only on that specific user’s data learns the pattern and automatically recognizes that activity in the future.
Why this matters
Every person has unique daily habits that cannot be captured by predefined Journal options.
I’d love to understand how my own behaviors affect my health and performance.
For example:
- Does reading before bed improve my sleep?
- Does watching TV reduce Recovery?
- Does phone usage before sleep lower my HRV?
- Which daily habits increase my stress?
Instead of only analyzing predefined events, WHOOP would gradually learn each member’s personal lifestyle.
Why this could be unique
Most wearables analyze data.
WHOOP could become the first wearable that learns from each individual user.
Every member would build their own personalized library of activities, making insights far more accurate and meaningful over time.
Possible implementation
- Training should be per-user only, not global.
- Start with a limited number of custom events.
- Keep the training process simple.
- Let the AI improve naturally as more labeled data is collected.
I believe this would be a major step toward truly personalized health tracking and would further differentiate WHOOP from every other wearable platform.
I also have several additional ideas related to AI personalization, habit recognition, and intelligent behavior analysis that could make WHOOP even more powerful in the future.
Thank you for taking the time to read this.
I’d love to hear what the community and the WHOOP team think.
— Aziz Sadullaev