TrainerRoad · 2017–2020
Adaptive Training
The foundation that made TrainerRoad AI possible. ML system with Progression Levels, Workout Levels, and real-time plan adjustments. Cut athlete workout failure rates by 48%.
Challenge
Athletes fail workouts at a high rate. Not because they lack motivation. Because static plans don't adapt. A workout prescribed three weeks ago has no idea about the cold you had last week or the extra stress at work. The plans treated every athlete the same, and athletes paid the price in failed sessions and lost motivation.
Approach
I led the ML/AI product team from concept through launch. We built Progression Levels, a 1-10 scale that tracks each athlete's fitness across every training zone. We built Workout Levels to rate every workout's difficulty within its zone. Then we layered on difficulty ratings (Recovery, Achievable, Productive, Stretch, Breakthrough, Not Recommended) so athletes always know where a workout sits relative to their ability. The system adjusts the plan after every completed workout and handles real life: missed sessions, time off, great weeks, bad weeks. We added Workout Alternates so athletes could swap for shorter, longer, easier, or harder options without breaking the plan. The tagline was 'The Right Workout. Every Time.' and we meant it.
Impact
Cut athlete workout failure rates by 48%. Athletes completed more of their training, got faster, and stuck around longer. Not a vanity metric. It changed how people experienced the product.
Reflection
The athletes who benefit most are not the most talented ones. They are the ones who show up consistently and let the system work. Same as anything else.