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The Evolution of Testing: Continuous AeT
2 Playsin 1 hour
Steve House and Will Zittlau pull back the curtain on Continuous Aerobic Threshold, a new feature inside Uphill Athlete's Training Groups dashboard that automatically calculates an athlete's AeT each week using a four-week moving average of their training data — no field test required. Steve explains the core problem: athletes can do the work consistently and still be uncertain whether they trained at the right intensity, because a missed AeT quietly shifts aerobic sessions into glycolytic territory and derails the adaptation they were after. To validate the algorithm, Steve blind-scored 65 athlete files by hand and found the tool lands within an average of 0.1 beats of his coaching judgment — though that average masks a wider spread, with 62% of athletes falling within five beats and outliers as far as 17 beats off, a gap the team attributes largely to data quality. The episode is candid about where the tool still falls short and what they're doing to close it: improving filtering (wrist-based HR and mountain bike data are particularly noisy), building data-hygiene habits in the community, and targeting 99% of athletes within five beats of coach-level accuracy by year's end.
And join us Tuesday, June 30th
YouTube Livestream: Continuous Aerobic Threshold Monitoring and Training Zones
Join Steve House and Will Zittlau for a live walkthrough of the Uphill Athlete Training Dashboard that is available to our Training Groups Athletes. Learn about continuous heart rate monitoring and how you can set your training zones with confidence. If you've ever wondered whether your training zones are right, this is a discussion you won't want to miss. REGISTER >>
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Transcript
The Core Issue in Training: Effort vs. Uncertainty
00:00:00
Speaker
The problem has not been effort, it's been uncertainty. And this is just one tool that we're developing to help close that uncertainty gap.
Upcoming Live Session on YouTube: Training Zones and AET Monitoring
00:00:17
Speaker
Join me live on our YouTube channel on June 30th, where I'm going to talk about continuous AET monitoring and how you can set your training zones with confidence. If you've ever wondered whether your training zones are right, come join me.
00:00:30
Speaker
The link is in today's show notes. Every endurance athlete who trains with a heart rate monitor has had the same experience. You head out for your easy aerobic run, you settle into what you think is the right effort, and you finish the workout maybe not sure that the work you did matched the work you were meant to do.
Introducing Pill Athlete's New Tool for Aerobic Threshold
00:00:51
Speaker
You had a number, but you just weren't sure if the number was right. Today, we're going to talk about how we're trying to close that gap. We built a tool inside a Pill Athlete that reads your training every week and tells you where your aerobic threshold actually is based on the training you've done and not on a special test. And then we did something equally important, which was we tested it against ourselves. And we basically ran a statistical analysis of the the programmatic way of determining aerobic threshold, the manual way of doing it as a coach versus the having the athletes do it themselves. So going to tell you exactly what we found.
00:01:30
Speaker
including the parts that maybe aren't that flattering.
Development and Purpose of the New Tool
00:01:32
Speaker
And I'm joined today by Mr. Will Zitlau. Will led the build of this on the software side. He's an uphill athlete himself and a technical project manager by trade. Will, thanks for being here.
00:01:43
Speaker
Yes, Steve. Thanks for having me. I'm excited to talk about this. It'll be fun. I think it's a pretty important problem that we're we're solving because the problem is sort of the basis for so much of of what we do. And it's something I've been working for a long time. I've been working towards this for a long time and it's pretty, pretty fun to finally have the first parts of this be visible to people.
00:02:10
Speaker
So one of the insights that I've had from my You know, in the last 10 years at Up To Athlete is that athletes do care about the work that they do. They put in the training. They put in the long, slow distance. They're consistent. They're patient.
00:02:26
Speaker
But what they often can't do on their own is know whether the effort they put in is the right effort. Right. The one number this whole thing turns on is your aerobic threshold, which we call the AET. And that's the point, just a little refresher, where your body's reliance on fat as a fuel source starts to give way to carbohydrate. Your aerobic and your glycolytic systems, as we sometimes call them, are always working together. There's no switch that flips hard from one system to the other. But what changes as you go harder
00:03:01
Speaker
train harder, run harder, climb harder is the balance. Below your aerobic threshold, aerobic fat oxidation is dominating and lactate production and clearance are in balance. And when you're training in that zone, you're building the adaptations that make this long, slow endurance possible. If you go into the glycolytic or into the the carbohydrate burning where the carbohydrate has taken over as a dominant fuel source, lactate starts to outpace the clearance and the fatigue starts to build faster than it did at a lower heart rate. So here's the problem we set
Challenges in Setting Aerobic Thresholds
00:03:35
Speaker
out to solve. We
00:03:37
Speaker
You want to do a workout that builds your aerobic engine. But if your aerobic threshold number is not set correctly, especially if it's set too high, the easy workout that you thought was building your aerobic system is actually pulling you into anaerobic metabolism. And so you're actually doing stimulating your body in a different way. you and that has a different recovery cost and you didn't train the part of your physiology you intended to, that you believe you did. And that whole system is off balance because of this one fundamental miscalculation. So
00:04:12
Speaker
The problem isn't effort, it's this uncertainty. And we've solved this in the past with lab testing, aerobic heart rate drift tests, like the MAF system the the that week ah that it was developed by Phil Maffetone that we've had out here on the podcast.
00:04:33
Speaker
And for years, I've been wondering if there's a better way to solve this. And and you helped me to do that. Yeah. And I mean, echoing what you said, i think so everyone kind of knows like upper zone two is maybe ah an approximation that people use for that. But depending on how often you're also updating your heart rate zones in whatever health metrics platform you're using, that can be out of date.
00:04:59
Speaker
And like you said, it's super important to nail because you want to get that aerobic, especially if you've um subscribed to the uphill athlete like training methodology you all know that you're spending a lot of time in those lower zones and so you want to make sure that you're actually doing that accurately and so this is kind of where that problem came up is like how do we close the gap on that uncertainty Yeah, and I think it's important to to pause there for a moment and say it doesn't matter in a way if you're using rpe or if you're using strict zone-based training, you still need to figure out at what exertion level you're running,
00:05:39
Speaker
aerobic and what you're running when you start to become more glycolytic or more anaerobic. And again, it's a continuum. It's not a, it's not a black and white situation.
00:05:50
Speaker
And so this was the gap that, you know, as a coach, I, had for a long time filled by simply going into athletes training files and looking at places where they are ah are aerobic and just extrapolating their aerobic thresholds from workouts as they go because as you said like the aerobic threshold changes over time as you get fitter the heart rate or that goes up. This is where RPE actually really shines is your, your RPE doesn't change. It still feels like you're running at an RPE of two or three, but you're going faster because your heart is beating faster and your aerobic metabolism is. So that's one of the advantages of that system. With
00:06:38
Speaker
having to avoid the aerobic threshold test that you do by going and running around a track, then figuring out your pace versus heart rate and whether that's decoupled or not.
00:06:51
Speaker
And for each of those tests, you have to paper a little bit. You need to fuel properly. you need to have a good day. You need to be in a particular environment. And then you need to, you know, do it again every six or eight weeks to change it. And so this is going to kind of take care of all that and make all that a thing of the past.
00:07:09
Speaker
Will, I want to turn this over to you. You're an athlete in the system, not just the person who helped build it. Before any of this existed, what was this and uncertainty actually like for you?
00:07:21
Speaker
Totally. um This definitely hits home. Last summer, i was training for my first 100 so... a lot of time in zone one and two. And as a part of that, I had the opportunity to hike the g r five across the Alps with my partner, which was awesome. um Hiking with a heavy pack, lots of like lower zone one and two work, I'd say. But, you know, that was a month, couple hundred kilometers, 30,000 meters vert.
00:07:46
Speaker
And I came out of that trip with a lot more fitness than I came into it. And that's kind of right where my big volume weeks started to build. And to be honest, I was kind of just guessing like back to having to do these controlled tests.
00:08:00
Speaker
um i I had an idea of where my AET was, but to be honest, I was just going off of RPE and and kind of just winging it for those big volume weeks. So Having something like this that I could have checked and seen that progression would have been awesome to then hit that transition because sometimes you do those really big build periods and you come out of it and you feel you have a lot more fitness, but you don't actually know how that translates. Yeah, I think that this is spot on. The problem isn't that people aren't doing the training. The problem is that people are uncertain whether or not they're training at the right intensities.
00:08:35
Speaker
And that's what we're we're trying to to help them fix. So let's talk about what we actually built. You want to give us a walkthrough of what continuous aerobic threshold is and what it's doing each week?
Continuous AET and Its Benefits
00:08:49
Speaker
Maybe you could pull up the yeah dashboard and training groups and give us a little piece tour there. So ah what you're seeing here, if you're a member of training groups, this is the training groups dashboard that you get to see. And right front and center, we've put those thresholds that we've talked about. So AET being the dominant one of this conversation so far. But we also have the ANT and then your AET, ANT Delta.
00:09:15
Speaker
The goal there is to actually show your progression as opposed to anyone that's done fitness training knows ah it can be like you can go weeks without feeling like you're making any progress.
00:09:27
Speaker
And then one day, you know, you stick with it and a ah flip switches and suddenly that workout starts to feel easier. Well, we're hoping that this bridges the gap and you can actually see that progress, even though you might not, you know, small, subtle changes week over week, you might not notice physiologically, but we're hoping we can pick that up and actually show you that trend line of your fitness growing, basically.
00:09:48
Speaker
So that's what continuous AET is. It's going to be a four week moving average and just showing you that progression over time based on the workouts you're uploading. ANT on the other side, ah this a lot of fitness platforms will show you this number.
00:10:02
Speaker
and It's a bit easier to calculate, but ANT is going to be the upper end of your zone three, um you know, that threshold heart rate. And then the third value that we're showing is the actual AET ANT delta.
00:10:14
Speaker
um which has some interesting implications that Steve can talk to a bit more. Yeah, thanks, Will. I think that this has been the vision I've had for a long time, is to be able to make the aerobic threshold visible to people.
00:10:31
Speaker
And you know you've helped me make realize that. We, we could actually calculate a T on a daily basis, but there's a few reasons that we don't do that or don't want to do that.
00:10:44
Speaker
And what no one is that it it, it changes a little from day to day, depending on your rest and fatigue and hydration, dehydration, um heat altitude, all kinds of variables could affect your, your heart rate and your, your ah ro threshold that day. And we got have to remember like so many of these models, when we've talked about this from day one of Uphill Athlete, like you have to remember we're not inventing anything new. We're just taking what is conventional endurance training, understanding and translating it for non-conventional sports. And since we're not running around a track where we can...
00:11:28
Speaker
easily use pace to to measure. We're not riding bikes where we can easily use watts to measure. We need to, we need this tool to ah make our fitness progress visible. And if we look at it every day, it's going to drive us crazy. And we're going to give it just by default, like that, because we're humans,
00:11:50
Speaker
we're going to give it too much importance. So we need to be a little bit fuzzier on purpose ah so that we're not like over obsessing about the the number and how it's changing from day to day or whatever. Cause it's not the reality of how our bodies ah behave and react and respond to training.
00:12:10
Speaker
So Steve, i mean we've talked a lot about a and what it is and what we're trying to do with it, but how would athletes actually get this value before like with your coached athletes? What are you prescribing for them to update this manually?
00:12:23
Speaker
Well, with some athletes will go and do a test in a lab. That's still going to be the best. You know, we're not replacing that accuracy, but in a way we're, we're doing that on purpose. I want to make that, that point. What we want is like ah a field test and the going out and doing the heart rate drift test is while it works and it's good and you can still do it, what we found was when people were doing, I'll talk about the, we're going to talk about the statistics in a minute, but this is really interesting. In training groups, people use ah the heart rate drift test and then they set their own zones. They set their own training zones from that. I went in and hand-
00:13:08
Speaker
and calculated, i think is the best word, hand calculated training zones for people and including looking at the heart rate drift tests. And in, in my experience, they were consistently four to six beats too high for what they decided their, their top of zone two was. And so this, this points out the problem that it's, that it's just hard and it's just complicated to do and it's not easy.
00:13:34
Speaker
And so I wanted to, you know, find, ah you know, again, find another way to to do this, to make this less difficult. If you've been wondering whether one-on-one coaching is the right next step for your training, this is the month to find out.
00:13:49
Speaker
Sign up for coaching and receive a free 30 minute call with one of our specialists. Visit uphillathlete.com to learn more. Now back to that show.
00:14:02
Speaker
I think the important thing to talk about is just how we validated this. Once we developed this algorithm
Algorithm Validation and Reliability
00:14:09
Speaker
and we needed to test it, what did that actually look like in the validation process? Steve, I know you did a lot of manual calculations on your end, so maybe just run everyone through how we actually validated our work.
00:14:22
Speaker
It's a great question. You know, there's a pretty long history that I won't get into. I'm happy to tell people if they're ever interested, but I just don't think people are interested. It took us about, I've been working on this for almost two years from now. And so before you came on the scene, I'd been working on this for a year and had like the calculation piece sort of figured out using ah a bunch of our exist athlete techniques.
00:14:48
Speaker
data and and kind and figuring out like ah basically ah a way to calculate this and and what the filters are and different things like that. But I wanted to figure out a way to replicate how I would score athletes if I sat down with their data myself. So again, to the point about the lab testing, you know, there is lab testing. There's ventilatory threshold work that we've talked about, especially in training for the new alpinism, like the first ventilatory threshold, like being able to speak while you train and so on. There's well-run field tests like the heart rate drift test. They can all give you good data, but
00:15:29
Speaker
Coach judgment is the closest thing we have to what the athlete is actually experiencing. and so that's what I wanted to test it against was the actual coach judgment.
00:15:40
Speaker
Yeah, once we had this in place, we pulled the training data for 128 of the training group's athletes and ran this continuous AET against six months of that data. ah Steve then sat down with 65 of those files and hand scored them in a blind test. So he didn't actually know any of the scoring coming into it.
00:15:58
Speaker
He was just provided with the data and does what a coach does and ah validated his own AET approximation based on what he was seeing. And I think it's important to make make a couple points. One, I didn't do all of them because it just takes a really long time. ah And we got to about halfway through the data and statistically we had enough to to make this work.
00:16:22
Speaker
And there is there is some some learnings in there that we'll talk about in a second. I, again, want to say that, you know, the hand scoring is a better yardstick, in my opinion, than a laboratory number, not because it's more accurate, because it's it's more, like, ah timely, because the problem with, you know, you unless you're a professional athlete, you're not going to be able to get lab tested every week every two weeks or every month. That's just unrealistic. So we want to keep this based in like the lived reality of being an athlete and being an uphill athlete. I want to talk about the numbers a little bit and we'll link to the blog that I wrote about this and people that want to can go and and see the actual data and the the all the all the math behind this.
00:17:13
Speaker
and the Of the 65 athletes that hand scored, the average difference between the tools number and the number that I chose was one 10th of a beat per athlete. So, you know, that means that if the average, uh, so that did almost zero, like it was basically the same as what i scored on average. So as a group, that the tool isn't running systematically high or running low on average. It's centered right on top of where a coach lands. But there's an important caveat here, and I want to be transparent about this.
00:17:51
Speaker
There not all the data is equal. Some of the data was actually quite poor. Some of it was pretty good and some of it was high quality data. And so what I ended up having to do, and I didn't foresee this, but it just became a natural part of the process is I ranked each athlete if they had low, medium or high quality data.
00:18:15
Speaker
And then when We split the athletes out according to how clean or how high quality well recorded another way to put it and well organized their data is.
00:18:27
Speaker
There was a couple different stories that came out for the 34 athletes whose data was clean enough for me to score with a very high confidence that I scored their data was was was clean and really good.
00:18:39
Speaker
The tool read two heart rate beats lower than my number. So I had said the aerobic threshold was 130, tool would have said 128 average those 34. For the 17 athletes whose data was sparse like, you know, the poor quality
00:18:58
Speaker
you know the the poor quality data The tool read about six beats per minute higher than mine, which kind of makes sense that, you know, the formulaic approach when the data is a little more,
00:19:13
Speaker
variable, let's say, ah it just, it doesn't produce as good of a result. So garbage in, garbage out. And of course, the sort of mixed data athletes were in between. People can see that. But on average, those two errors sort of cancel out. But for an individual athlete, they don't.
00:19:32
Speaker
And I think that the direction of this matters. And um and we've also seen this in reality. And, well, you and I have both had a bunch of messages about this from athletes in the training groups, because they've been using this for a while now, as when you get to actual athletes, the people who have...
00:19:51
Speaker
let's say clean data, they're they're they're recording it, they're marking everything correctly, they're they're using either a chest strap or an armband, or if they're using a a wrist-based monitor, they're getting good readings from it. Not everybody does.
00:20:07
Speaker
If they're following these basic good data hygiene protocols, they're they're getting pretty good results. it's the people who are switching between different modalities a lot, especially, unfortunately, like cycling, especially mountain biking, you know, really that we've had to just rule out. We just don't look at mountain bike data, for example, because, know,
00:20:32
Speaker
Think about it like the mountain bike data is completely the inverse of what we want. You know, it's, it's the heart rate is the highest when people are going the slowest. Right. And it's the lowest when they're going with the fastest are going downhill on an easy downhill. Right. So like there's, there's, there's some things that we learned around the process of, of improve that helped us improve our filtering. And ah it taught us a lot and improved a lot. But I want to be very clear, it's still very much a a process.
Real-World Feedback and Tool Improvement
00:21:01
Speaker
We're still working out working it out. There's still a ton of edge cases. And I'm also confident that, you know, it's just going to get better over time as we continue to work on it.
00:21:10
Speaker
Yeah, 100%. I think it's good to be clear that we're not claiming we've solved this problem outright, right? Like we're going to continue to learn. And as you said, our our process is going to continue to evolve.
00:21:21
Speaker
um I think once we got it in the wild and actually got user feedback as opposed to just, you know, datasets that we were running our own experiments against. um It's been good to see the general feedback. And i think, like as you mentioned, that that data filtering, um I knew that was going to be an area of challenge. But ah in real world use, there's so much variety, right? The real world is very dynamic. And so it's hard to have a one size fits all solution, but we're trying to get there to fit the average athlete, right?
00:21:55
Speaker
um The biggest problem that we' we're seeing really is like heart rate drop off in the middle of a workout or big spikes. um If you use a wrist based watch, that's a lot more likely to happen. So um back to the data cleaning, you know, things like a chest strap heart rate monitor, that's going to give cleaner data,
00:22:11
Speaker
um depending on the workout you're doing, like obviously running on a track or on a road is going to be more representative than a trail run, potentially just because of terrain variations and that can skewing ah stats. I mean, your heart rate is going to reflect, but you know, there's just, once again, the real world is very dynamic. And yeah,
00:22:32
Speaker
solving that from a data perspective has been a fun challenge and something that like every week we we learn more, get more feedback and revisit it and say, actually, we need to look at this direction or adjust this. So um I do expect it to get more accurate over time, obviously.
00:22:48
Speaker
Yeah. And when I first saw, when I first did the statistical analysis, I, and I came back that the average was only 0.1 beats different than what my hand scoring was. I was, I was flabbergasted. I was at first overjoyed, but my, my confidence was short-lived because when I actually kind of got into it, another way to break this down is that 62% of the athletes had a number within five beats of my hand score.
00:23:15
Speaker
So, and 77% were within 10 beats. So that's actually, to be honest, for me, it's not that great. Like it's, it's, it's the right direction. Like we're going to get there, but I want, I want 99% of the athletes to be within five beats of my hand score. you know I think that that's ultimately where we want to go. And we're seeing some anomalies like people 17 beats up or down from my hand score from the thing. And and that's just not reliable. like that's That's not actionable. So one of the reasons we're
00:23:49
Speaker
utilizing this in the training groups with real world athletes is it's a, it's a big enough group. We have statistical relevance, but it's a small enough group that we can really still communicate with them. And I can really still go in and hand score athletes from time to time and help figure out like where they're off. And it's been, it's really helped inform our improvements, right? Like how our, our, especially filtering, I think the data filtering is one of the places where it's a really useful athlete. And teaching the group, I mean, I hate to say it, but we're kind of having to teach the group some data hygiene as well.
00:24:23
Speaker
Yeah. And ah for anyone that's confused, because I know we led saying that we were within one tenth of a beat per minute, that's the average. And then obviously that disagreement range is going to be a lot wider per athlete. So that is taking into account positive or negative variance.
00:24:40
Speaker
When you take the average, it's actually one tenth, which is awesome. But then on a single athlete, you know, plus or minus five, that would give you an average of zero. But both of those athletes were off, right?
00:24:51
Speaker
I think that that's that's where we're trying to continue to improve and continue to run this in the real world with real athletes and and figure it out. So, yeah, we're still we've still got some ways to go. I think it's... ah We've had a really great response from the training group. Athletes are really engaged with it. And several of them are really, truly geeking out ah ah with with us, right, on the data and how to how to filter it and how to calculate it, all that stuff. And that's been really, really fun. But we're going to get there. And ah and we've actually like made huge um improvements in in a really short time. So I'm pretty excited about it. Anybody who wants to look at the statistics, the full write-up is in the blog post. will be linked to from from this podcast episode. And there's going to be the the full you know numbers there.
00:25:44
Speaker
And so once we have this data computed, is this just being applied to athletes? Or what's the vision there? So, okay, the system has found this value. Then what?
00:25:55
Speaker
It's great question. So this is actually very fundamental to our whole approach with data within Uphill Athlete is that the the program suggests that the athlete always gets to decide. or ah Ultimately, if we're able to get this good enough, that it's useful for one-on-one coaching as well, where we you know it is very, very, very precise and coaches can can rely on it.
00:26:21
Speaker
it's in that case also going to be very much a suggestion to the coach or additional data point it's not going to ever replace them and i think that that's super important you can accept uh this and then adjust your zones or you can and we've we've done this like did this with two training group athletes just today said like hey you know what that number is not good i don't think that number is accurate i think you should use something else. And then, and then we build our zones off of that. And, you know, that's, and then along the way we're, we're learning what all these edge cases are. Um, so I think that that's the the right approach. I think a wrong approach, right. Is just to have like too much confidence in this. It's not, it's not magic. It's it' still just, uh, still just a process that we're implying.
00:27:09
Speaker
Definitely. And I think we both fundamentally agree on that. like I think as software development evolves and gets potentially easier to coordinate vast amounts of data, um at the end of the day, there's still decades of expertise under each of your coaches. And these tools should be used to surface insights, but not necessarily be used deterministically.
00:27:31
Speaker
And I think that that's kind of fundamental to the whole a philosophy we have towards data as a coaching team as well. So one of the things that I think some of you have foreseen is that you could...
00:27:48
Speaker
have your training zones calculated and basic for you basically, because now you're going have your aerobic threshold suggested. You're to have your anaerobic threshold suggested from training peaks or Garmin whoever's originating that number. And then you can build your whole zone system and then you can convert that to RPE if you wish, or you can stick with the training zone, the heart rate zones. And yeah, That is like just kind of the next step. And we are working on that. And we talked about it in the live stream last week. So it's not a secret. There is still more to do. And I think it's still really interesting to work on this, but we still have to be very realistic about how accurate this is. And that's one of the reasons we just want to be transparent. about, hey, this is working, it's working really well, and it's going to continue to get better and better over time. So my prediction is by the end of this year, we're in territory where it's very accurate, we're very confident in it, and we'll be able to show that through these kind of statistical analyses.
The Importance of Visibility in Aerobic Development
00:28:59
Speaker
Yeah, I'm excited for it. And so, I mean, just to close off, like, what does this mean for the average athlete if you don't have access to those lab tests, as you've mentioned? um What does this really unlock?
00:29:10
Speaker
Because you mentioned you've wanted this for quite a long time. Yeah, I think it unlocks a lot. um You know, once we have continuous aerobic thresholds suggesting to you every week what your AT is, you can adjust your zones, you can, you know, suggest and you could adjust your new zone too, and you could trade that way. It's important to understand that at the end of the day,
00:29:37
Speaker
when you When you go into a training block, let's take a week, for example, you're what you're trying to do most weeks, except for the recovery periods, you're trying to sort of embarrass your system and just a little bit, just enough to show it like, hey, you can't quite do this. This is what I want you to do. And so by having continually updated aerobic thresholds, you're more able to kind of be nudging that up that aerobic threshold up and just embarrass your system, so to speak, just a little bit more every week. So you're going to actually just be more effective in your training.
00:30:10
Speaker
And then you're going to have this sort of visual tracker of your aerobic development. You could see because this doesn't happen from day to day. And it's not like strength training where you can notice that you can lift five pounds more this week than you did last week or last month.
00:30:26
Speaker
it It takes longer to and it's and it's harder to see. So making this visible, I think, is is going to be really, really important. And think that the if we if we zoom out on that, this feature is just kind of one visible piece of what's going to become a visible larger arc where we're trying to scale clear science-based human coaching to more athletes than one-on-one coaching can reach without diluting the one-on-one coaching. And there's sort of three layers to this system is in my vision. One is...
00:31:02
Speaker
the the coaching, the high touch, the one-on-one where it's like ah ah ah a, a, a one-to-one relationship in terms of determining what is best for a given athlete, you, that given day, that given week, that given training cycle.
00:31:19
Speaker
And versus a kind of a one to many, system where it's, what we have in, in training groups and the training groups is. In a lot of ways, I see it as a continuity layer. Like people go and they want to train typically for three, four months and they go into, they do their climb or they run their race.
00:31:38
Speaker
And then they want to continue and and at least maintain, if not continue to improve, but they maybe don't need that full, like one-on-one dedicated high attention. Plus it's sometimes a lot of pressure and and they can kind of drop back into training groups and have that continuity. And then we're building a tool we called Maria, which is,
00:31:56
Speaker
what I think of as the connective intelligence layer that supports all of that and helps us understand what athletes need and when they need it and helps the coaches to better support our athletes. And it holds together kind of the uphill athlete methodology. It holds the context of training and it's always in a proposal role. It's never in a deciding role. And ah whether you're in training groups, you're in,
00:32:23
Speaker
the governor of your own numbers and accepting suggestions. And if you're a coach, then you're the one that is is getting the suggestions. And then your work is able to be made faster, more accurate. And i think that the principle under all of this is that just as what we've always done with training, we just, as we get new tools those better tools should make us better athletes and better coaches help us scale human expertise help us protect that kind of one-on-one relationship that mentorship that happens and just you know provide more structure with less uncertainty for more people 100 i think it's a really exciting time to be an athlete right now actually with all the new tools and data that we have access to these days yeah
00:33:09
Speaker
Yeah. And I'm so grateful. I just want to say I'm so grateful for the training group athletes because they are so, I mean, I was a little hesitant. It was like, oh man, they're going to feel like guinea pigs or whatever. It's been the opposite. They feel like they're on the cutting edge of something really exciting and they're fired up and they're really contributing and, uh,
00:33:28
Speaker
And, you know, if it wasn't for them out the field doing their workouts every day and, us and you know, adjusting their training zones in some cases every week as their aerobic threshold changes and and so and they continue to progress, like we wouldn't have this this laboratory in which to build this. So it's really grateful for them.
00:33:48
Speaker
100%. know it's only been a couple of months, but the community you've built working alongside them has been awesome. Everyone's just been so great to deal with and and talk to. So um it's pretty cool. Yeah.
00:33:59
Speaker
Oh, thanks. I appreciate i appreciate all them. So any training group members listening, hats off to you guys. So if there's one thing that kind of captures all this that I just want to close on, it's this, one of the key things I keep coming back to is the problem has not been effort.
00:34:16
Speaker
It's been uncertainty. And this is just one tool that we're developing to help close that uncertainty gap. And we want to also be transparent. We want to show our work while we do it. so Again, the full analysis with all the numbers and all the parts, including those that are not so flattering, are on the blog. We'll link to it in the show notes. If you want to see the dashboard yourself live, we're doing a live walkthrough on YouTube on June 30th, which is seven days after this will drop.
00:34:45
Speaker
And we can show you then. And if not, come join us in training groups. We'll have a sign-up link here in the show notes. It's a really dynamic community, and we're just making it better basically every week at this point. So... Hey, Will, thank you so much for all your work on this. You know, couldn't have brought this to life without you, that's for sure. Yeah, thanks, Steve.
00:35:07
Speaker
Word to come. Thank you, everyone.
00:35:26
Speaker
Hey, real quick before you go, everything we publish, the articles, new podcast episodes, and the live webinars are announced first in our newsletter.
00:35:37
Speaker
You can elect to receive between one and three newsletters a month they're written by myself and the coaching team. And if you want them, sign up at UphillAuthy.com.
00:35:48
Speaker
Thanks for listening and we'll see you in the next one.