TrainerRoad AI announcement and differences

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// TOPICS COVERED

(00:00:00) Welcome + SFR training overview

(00:00:33) TrainerRoad AI announcement

(00:02:05) Why TrainerRoad AI ≠ chatbot coaching

(00:06:03) What SFR training is

(00:09:15) Force vs cadence & muscle fiber recruitment

(00:14:16) Why the research is mixed

(00:15:18) Study: Low cadence maximal intervals (Paton 2009)

(00:18:06) Study: Low cadence climbing & TT transfer

(00:19:53) Study: Low cadence HIIT in female cyclists

(00:22:21) Studies showing no added benefit

(00:26:02) Injury risk & knee stress considerations

(00:29:09) When and how to use SFR safely

(00:33:08) Key takeaways & final advice

In this special episode, Coach Jonathan digs into SFR or low cadence, high torque training, explaining where it came from, why elite cyclists still use it, and why the research around its benefits remains mixed. He walks through the underlying physiology, reviews studies that both support and refute performance gains, and explains why any potential upside appears small, highly context dependent, and often linked to higher intensity work. Coach Jonathan also highlights the real risks, especially knee and joint stress, and offers practical guidance on if, when, and how to experiment with SFR safely, emphasizing that it is a marginal gains tool best suited to base training and never worth compromising power targets or consistency. The episode opens with a major TrainerRoad update, previewing TrainerRoad AI, the company’s biggest release ever, which replaces Adaptive Training with new in house AI models designed to deliver better workout selection, fewer misses, and more FTP and power gains, setting the stage for a new era of data driven coaching.

// RESOURCES MENTIONED

- TrainerRoad’s Instagram: https://www.instagram.com/thehannahotto 

- TrainerRoad AI Blog Post: https://www.trainerroad.com/blog/trainerroads-biggest-update-ever-is-coming-%f0%9f%91%80/ 

- TrainerRoad AI Forum Post: https://www.trainerroad.com/forum/t/trainerroad-s-biggest-update-ever-is-coming/107205/26 

- Paton, et al., 2009 Study: https://pubmed.ncbi.nlm.nih.gov/19675486/ 

- Nimmerichter, et al., 2012 Study: https://pubmed.ncbi.nlm.nih.gov/21479957/ 

- Hebisz, et al., 2024 Study: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0311833 

- Kristoffersen, et al., 2014 Study: https://pmc.ncbi.nlm.nih.gov/articles/PMC3907705/pdf/fphys-05-00034.pdf 

- Hansen, et al., 2017 Study: https://pubmed.ncbi.nlm.nih.gov/28095074/ 

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