The athlete is not an average
Population research can inform Tyzle, but the athlete's own evidence matters most. Personalization must be earned by data, not asserted by branding.
Philosophy
Tyzle is built around a simple hypothesis: the athlete should be understood before training is optimized.
Population research can inform Tyzle, but the athlete's own evidence matters most. Personalization must be earned by data, not asserted by branding.
Work, family, travel, sleep, illness, equipment, motivation, and available time are not exceptions to training. They are part of the model.
If evidence is limited, Tyzle should say so. False certainty is less useful than a clear explanation of what is known and what remains unresolved.
Tyzle can support decisions, but the athlete is the final decision-maker. Consent, override, and clear boundaries matter more than automation.
The Three Laws of AIM
1
Historical observations should remain intact. New evidence can change current understanding without rewriting what happened.
2
Important guidance should be explainable through reasoning, beliefs, measurements, and supporting evidence.
3
The goal is to reduce uncertainty honestly as evidence accumulates, not to produce confident-sounding answers before they are justified.
How that shows up
Activities and provider artifacts are kept traceable so future methods can reinterpret them without losing historical integrity.
A belief is Tyzle's current explanation, not an absolute fact. Better evidence should improve or revise that explanation.
Current-state understanding should reflect the athlete today. Historical evidence still matters, especially for context and era detection.
Athletes should understand what Tyzle observed, what it inferred, what remains uncertain, and why a future recommendation is justified.