AI Cycling
Self-coached intermediate-to-advanced UK road, gravel and time-trial cyclists who already train with a power meter and Strava, intervals.icu or Zwift, and want to know which AI coaching tools, models and prompts actually hold up against their own ride files.
- Guides
- 12
- Articles
- 27
- Words
- 76,132
What this site covers
6 sections, 6 supporting pages and 27 articles. Every one is free and complete.
- AI Coaching Platforms, Tested
ai cycling coach app
3,167 words 1 supporting 4 articles
- Analysing Ride Data With LLMs
analyse strava data with ai
2,358 words 1 supporting 6 articles
- FTP Estimation And Fitness Models
ai ftp detection accuracy
2,939 words 1 supporting 5 articles
- Recovery, HRV And Readiness Scores
hrv guided cycling training
2,701 words 1 supporting 4 articles
- AI Route Planning And Race Pacing
ai cycling route planner
3,206 words 1 supporting 4 articles
- Build Your Own Training Tools
strava api python training analysis
2,643 words 1 supporting 4 articles
Latest writing
- Reviewing A Whole Season With A Long-Context Model 1,740 words Demonstrates a summarise-then-reason pipeline over 300 rides, arguing the useful output is pattern detection across blocks, not commentary on individual sessions.
- Build A Personal Training Dashboard With Streamlit In An Evening 1,693 words Argues a 200-line local dashboard answers your three recurring questions better than any subscription, with the full code for load, power curve and decoupling views.
- Wind-Aware Pacing: Building A Race Plan Around The Forecast 2,075 words Shows how yaw-angle and headwind segments change optimal power distribution, and argues AI tools that ignore forecast wind give you a plan for a course that doesn't exist.
- Whoop, Oura Or A Chest Strap: Which HRV Source Survives Scrutiny? 1,555 words Compares simultaneous overnight and morning measurements, arguing the device matters less than sampling window consistency — but that optical wrist data is noisiest for lean cyclists.