Koop AI, Unboxed

KoopCast

We reveal how Koop AI turns 25 years of coaching into an adaptive, terrain-aware training system for trail and ultra runners. We share why we built it, what it does today, where it falls short, and how we’re improving it with real race data.
• why serious runners wanted expert validation without elite pricing
• the three pillars of coaching we modeled: prescribe, analyze, communicate
• onboarding that pulls real history, constraints, and race demands
• dynamic plan changes for travel, missed runs, and time budget shifts
• NGP-based feedback for trail intensity instead of raw pace
• race specificity: course demands, heat, altitude and future prompts
• features live now: chatbot tied to Koop’s content, calendar, swaps, block moves, cross-training, volume trends
• limits we own: early-stage feedback, UI/UX, depth of “why,” and NGP-driven plan adjustments still shipping
• how we validate against coach standards and major races like UTMB
• long-term mission to make top coaching accessible to everyone
Sign up: https://www.koopai-endurance.com/app/

챕터

1. Setting the Stage: Why Coop AI (00:00:00)

2. Origins, Fear, and Embracing Tech (00:03:00)

3. Meet the Team and Roles (00:08:45)

4. Turning Coaching into Math (00:13:30)

5. Three Pillars: Prescribe, Analyze, Communicate (00:19:00)

6. Chatbot, Plans, and Feedback (00:23:30)

7. Onboarding and Dynamic Adjustments (00:27:30)

8. NGP, Trails, and Real-World Nuance (00:32:00)

9. UI, Features, and Race Specificity (00:38:00)

10. Limitations, Roadmap, and Iteration (00:43:30)

11. Validation at UTMB and Beyond (00:49:00)

12. Access, Pricing, and How to Join (00:54:30)

13. Mission, Standards, and Closing Reflections (00:59:30)