I’m training for Ironman Cozumel this November, and lately, I’ve been experimenting with something new: AI as part of my training routine.
Like most endurance athletes, I already have plenty of data at my fingertips. Between Garmin, Zwift, my Oura Ring, and other training tools, I can track just about everything.
The interesting question is what to do with all that information.
Recently, my triathlon coach, Hunter Allen, introduced me to several AI-powered training platforms that are attempting to bridge the gap between athletes and coaches. One of them is called Ride with Dave, and I’ve started playing around with it.
It’s still early, but the possibilities are pretty fascinating.
From Tracking Workouts to Understanding Them
After one of my recent cycling workouts, Ride with Dave automatically analyzed my performance and sent me feedback. It recognized my cadence, commented on the elevation, and asked what I was trying to accomplish with the ride.
There was one problem: it thought I’d climbed a particularly steep hill.
In reality, I was riding indoors on Zwift, and the elevation was simulated. My legs were tired from a previous workout, so I’d switched out of ERG mode and finished with an easy spin.
I explained that to the AI, and it immediately adjusted its interpretation. Instead of treating the session as a demanding climbing workout, it recognized that I’d been focusing on recovery. That exchange got my attention.
We’re moving toward a point where technology can do more than collect performance data. It can have a conversation with an athlete about what actually happened during a workout.
The Accountability Factor
Another aspect I’m interested in is accountability.
Because the platform can access historical training data, it has the potential to recognize patterns across workouts.
For example, if I consistently fade during the final miles of my long runs, it may be able to identify that pattern and suggest adjustments to my pacing.
Traditionally, that type of analysis requires time. You finish the workout, review the numbers, compare previous sessions, and discuss your performance with your coach.
AI has the potential to make that feedback available almost immediately.
Instead of spending hours reviewing workouts and trying to identify patterns, athletes can get a clearer picture of their performance while the workout is still fresh.
For endurance athletes, that’s an exciting development.
Can AI Replace a Human Coach?
Of course, there’s another side to this conversation.
Hunter mentioned that several athletes had returned to him after trying AI-only training plans and experiencing injuries. That’s an important reminder that a training plan is only as useful as its ability to account for the person following it.
Fatigue, recovery, competing priorities, and the countless variables that influence athletic performance don’t always fit neatly into a spreadsheet. A good coach understands the numbers, but also understands the athlete.
I’m interested in seeing how AI can support that relationship by making information more accessible and helping coaches respond more efficiently.
Where Do We Go From Here?
I’ve only just started experimenting with these tools, so I’m not ready to declare AI a game changer for my own training.
What interests me most is the possibility of getting more value from information I’m already collecting.
As I continue preparing for Cozumel, I’ll be paying attention to whether these tools actually help me make better training decisions, recognize patterns, and stay accountable.
Because ultimately, having more data doesn’t automatically make you a better athlete. What matters is what you do with it