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.
Building a desktop site generator and thinking about the pricing model. Are people still willing to pay a one time fee for desktop software in 2026, or is everyone just used to subscriptions now? What s your take?
While building an AI coach, we ran into an interesting problem: memory is useful, but some things shouldn t just be remembered - they should become rules.
If someone says, avoid overhead pressing, asking for a harder workout later shouldn t erase that constraint.
It made me wonder: what information in your AI product should survive every follow-up, no matter what?
