Like many of you, I spend a lot of time on Intervals.icu analyzing power curves, decoupling, and training load. It’s an incredible platform for diagnosing what happened in past workouts.
However, as a self-coached rider balancing training with work and family, the hardest part is often the forward-looking decision: what to do when a week gets derailed by overtime, poor sleep, sudden fatigue, or bad weather?
I am conducting research into how self-coached endurance cyclists manage plan disruptions and make compensatory decisions (e.g., when to push through vs. back off, how missed interval sessions are rescheduled, and what recovery metrics matter most).
If you have 3-5 minutes, I would greatly appreciate your input in this anonymous survey:
Just out of curiosity, could you add a disclosure, if it is an indirect advertisment for yet another AI app? (Sorry if it‘s not the case, but then it also would be nice to know who is doing research)
Personally I don‘t get the idea of AI coaching - if a key workout is missed, reschedule it. If an easy workout is missed, skip it. If rescheduling is not possible, then this is also not the end of the world.
Fair question, and completely understandable skepticism.
To be 100% transparent: no, this is not a stealth promo for “yet another AI coach” app. In fact, I largely share your skepticism - I don’t believe in delegating training decisions to an autonomous AI, primarily because AI fundamentally lacks the necessary context. An algorithm or LLM doesn’t genuinely understand the nuance between systemic work stress, an impending viral infection, poor sleep, or actual physiological overreaching, and usually just serves generic, ungrounded advice.
Your rule of thumb (key workout missed → reschedule, easy workout missed → skip) is solid common sense. The goal of this research isn’t to build a black-box “AI coach” to replace human judgment. It’s to understand where self-coached cyclists actually experience friction - whether that’s the blind spots of classic metrics (like scalar TSS ignoring durability or non-training stress), dealing with multi-day schedule domino effects, or the cognitive overhead of interpreting conflicting data.
I’m a fellow self-coached cyclist and software engineer researching real workflow gaps and decision-making friction, not selling an automated “AI magic button.” Appreciate the direct feedback!
