Sounds solid. Start with a lightweight sensor stack—wearable heart‑rate, GPS, maybe a micro‑spike in skin temperature. Feed that into a predictive model; a small LSTM could roll up the last minute of data and output a set of possible next‑minute states—pace, fatigue, recovery threshold. Then map each state to a recommended exercise intensity or rest cue. The key is real‑time feedback loop: the app should be able to tweak the plan on the fly, so the user never over‑exerts or under‑works. Keep the interface minimal—just a clear “now” recommendation and a brief “why” note so the user stays engaged. And don’t forget data privacy; encrypt everything and give the user granular control over sharing. That’s the sweet spot between science, strategy, and user trust.