How much should an AI fitness product remember about the user?
I’ve been thinking a lot about the difference between personalization and real adaptation in fitness software.
A profile with age, goal and experience level is useful, but it still treats each workout request almost like a new session.
A more interesting model is longitudinal: remember what the person actually completed, which movements and muscle groups were trained recently, how difficult the exercises felt, what restrictions exist, and how nutrition has looked over the previous days.
Then the next recommendation is based on that history instead of starting from zero.
The hard part is finding the right balance. Too little memory makes the product repetitive and generic. Too much poorly structured data can create noise and false precision.
For people building AI or health/fitness products: which user signals have actually made personalization meaningfully better in your experience, and which turned out to be unnecessary?
Replies
Nutrition could help a lot but I'd be careful not to pretend messy data is priecies.
How much nutrition history is actually useful before it becomes noise? i would imagine the last few days matter more than trying to remember everything.
Promomix
Do you think perceived effort is more useful than completion data? someone can finish a workout but still be completely wiped afterwards.
for me, workout difficulty is a big one because the same plan can feel very different week to week.
Buffup.AI
I would rather have 5 reliable signals than 50 noisy ones.
Bababot
I have used fitness apps where I entered a bunch of information once and then it basically disappeared into a database. the real test is whether that history actually changes what i get recommended next.
I would probably remember preferences separately from facts. Doesnt like running is useful; ran twice last month might not be meaningful forever.
I wonder if the best system would also know when not to personalize. sometimes a users recent behavior is an excepion rather than a new preference.
Promomix
If you had to keep only three signals for the AI to remember between sessions which three would you choose? i am guessing completed workouts would make the list but curious what else you have found useful.
I’d split memory into three layers: an immutable event log (completed workout, load, rest time), a derived state that decays (fatigue/readiness), and explicit user constraints that never decay without consent (injury, equipment, accessibility). Then require every remembered field to answer: which next decision can this change, and for how long? That makes retention testable instead of defaulting to ‘store everything.’ Sensitive nutrition or health data should also be visible, editable, and deletable by the user.