01
Concrete example
When the data shows that a demanding session does not fit the current state, YOUB does not react to one metric alone. The coach compares training history, subjective feedback, calendar pressure, and the next goal before suggesting an adjustment.
02
Data inputs
Depending on connected sources, YOUB can use completed sessions, duration, intensity, heart rate, sleep, recovery signals, availability, and goal dates. No single value decides the plan on its own.
03
Decision logic
A session can be moved, shortened, replaced, or intentionally kept. The decision is whether the change protects the long-term training goal while respecting real-life constraints and recovery.
04
Limitations
YOUB provides coaching suggestions, not diagnoses. Pain, illness, injury, and medical questions belong with qualified medical professionals rather than an automated training decision.
05
Weekly planning practice
For A TrainerRoad alternative: an AI cycling coach you can talk to, the next workout is only one part of the decision. YOUB looks at the whole week: hard stimuli, recovery, long sessions, and calendar commitments need to fit together so the plan stays understandable and does not collapse after the first schedule change.
06
What appears in chat
YOUB turns adaptations into a clear recommendation with a reason: why the session still makes sense, which risk is being reduced, and which alternative best supports the goal. The result is an understandable coaching dialogue, not an anonymous plan change, including a short follow-up question when the data or real-life context is not clear enough.