September 10, 2025 • 33 mins
OVERVIEW
Cody Stephenson, the Education Program Manager at TrainingPeaks, is back on the podcast to talk about the current state of artificial intelligence in cycling coaching and how TrainingPeaks' developers are using models to improve the accuracy and usability of athletes' training data.
TOPICS COVERED
- A.I.'s current and future role in cycling coaching
- How auto-updates of FTP work and when to pay attention to them
- About TrainingPeaks' Fueling Insights Tool
- TrainingPeaks Virtual: Ultimate Indoor Cycling App
- What's coming next from TrainingPeaks
ASK A QUESTION FOR A FUTURE PODCAST
Guest Bio – Cody Stephenson
Cody grew up racing mountain bikes in Durango, Colorado where he developed a passion for endurance sports, science, math and technology. He switched to the road and track while racing for Fort Lewis College, where he also managed to get a couple of science degrees. Now he gets to write and talk about his favorite topics every day as Education Program Manager at TrainingPeaks. When he’s not helping coaches learn to leverage technology to reach their goals he’s trying to become as good of a mountain bike racer as he was when he was 13 years old.
Resources:
- Cody Stephenson LinkedIn
- Articles: https://www.trainingpeaks.com/coach-blog/how-to-coach-athletes-who-arent-racing/
- CP W’ vs FTP alone
- Analyzing FTP by Joe Friel
- Power Training with WKO:
- Why Train Submaximally? WKO Case Study - Targeting Specific PDC Improvements
- Learning More about LLM’s and AI
HOST
Adam Pulford has been a CTS Coach for nearly two decades and holds a B.S. in Exercise Physiology. He's participated in and coached hundreds of athletes for endurance events all around the world.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:07):
From the team at CTS.
This is the Time Crunch Cyclistpodcast, our show dedicated to
answering your trainingquestions and providing
actionable advice to help youimprove your performance even if
you're strapped for time.
I'm your host, coach AdamPulford, and I'm one of the over
50 professional coaches whomake up the team at CTS.
In each episode, I draw on ourteam's collective knowledge,
(00:30):
other coaches and experts in thefield to provide you with the
practical ways to get the mostout of your training and
ultimately become the bestcyclist that you can be.
Now on to our show.
Now on to our show.
(00:50):
Welcome back, time Crunch fans.
I'm your host, coach AdamPulford.
Picking up where we left offfrom last week, I am back with
Cody Stevenson of Training Peaksto discuss how best to utilize
your data in platforms likeTraining Peaks and maybe a sneak
peek of future enhancements tolook at into the future.
So, cody, welcome back.
Speaker 2 (01:09):
Glad to be back.
Speaker 1 (01:11):
All right, so maybe just like a quick recap from
last week is that we comparedFTP and FRC to critical power
and W prime, explaining thatthese are similar systems
insofar as they both determinehigh aerobic threshold point and
an anaerobic measurement whichhinges off of that threshold, so
to speak.
The former is more of a fieldand practical based, while the
(01:34):
latter is the more like researchand lab based, and either
system is completely fine to use.
You just need to know howyou're actually going to use it
and use the data within it tomake the best decisions for your
training decisions.
So now, if you're going to relyupon that like some sort of
like machine learning or AIpopulated things, to make those
(01:58):
training decisions for you, youneed good data, good, clean data
, as well as the knowledge ofhow the system works, because,
in my opinion, bad data inequals bad data out, and if your
model is bad, so will yourtraining.
Cody, would you agree with that?
Speaker 2 (02:13):
Yeah, yeah, definitely All right.
Speaker 1 (02:18):
Well, let's, let's pick up right where we left off,
which was talking about AI andCody.
I asked you is AI going to takeover this endurance coaching
space, yes or no?
And you said it might take somejobs.
Let's talk about that.
Speaker 2 (02:37):
Yeah, I think.
Well, I guess I'll start withthe jobs and I'll steal a saying
not mine, everybody's probablyheard it from every industry is
that you're not going to loseyour job to ai, but you're.
You might lose it to somebodywho's using ai better than you.
So it's, it's going to be auseful tool.
It's going to take care oftedious tasks, repetitive tasks,
(02:58):
tasks that um might be prone tohuman error, and so you can't
ignore it.
But taking over the wholeindustry, I, I, I don't think so
, mostly because one of the mostimportant lessons I learned
when I came from being anathlete to working at training
peaks you know, I was a high, Iwanted to be a high performing
athlete.
I cared about results.
I cared about and I was okaydoing it alone, like I liked
(03:21):
training alone.
I didn't work with a coach.
All that was fine.
It was when I started trainingpeaks.
It took me a long time to learnthat I was in the minority with
that.
Most people just want to be apart of something, and so one
thing they get out of endurancesports, even if they're pretty
high performing is relationships, and so that's a really
(03:44):
important part of what coachesdo, like I mean every coach out
there listening knows that youaren't just the guy who writes
the training plans or the girlwho writes the training plans.
You are the therapist, theSherpa, the tire pressure
advisor, everything else that anAI can't.
And a lot of times you justbecome their friend and that's
(04:10):
just like a piece that AI can'tdo.
But some of the parts that werepretty important for coaches 10
, 15 years ago, even now, aregoing to be done more and more
by AI.
Speaker 1 (04:19):
Yeah, yeah, no, I completely agree with all that,
and I would also say that whenI'm talking with my athletes,
when I'm, when I'm learningabout people and we learn this,
even like through COVID, rightit's just like the person to
person interaction is still sopowerful that, yeah, I don't, I
don't think it's going to go,yeah, I don't think AI is going
(04:40):
to take over and take every youknow coach's job and that kind
of stuff.
But, yeah, I think that thepeople, the athletes, the
listeners here that want thebenefit of kind of that
data-driven AI sort of you knowquicker sort of strategy, or
kind of you know kind of moreaccuracy, more consistency,
(05:02):
whatever AI is going to help uswith, yeah, they'll want to
coach that deals in thatcategory.
You know that works in thatspace, and so, um, there'll
probably be a delineation ofcoaches, um, in that way.
But I still know some coachestoo that are using Microsoft
Excel and they're great coaches,right, and they talk with their
athletes and they interact withtheir athletes Great.
So it's like you don't evenneed the data-driven approach
(05:24):
necessarily to do to be a goodcoach yeah, that that's the
thing is, most people mostlyamateurs, but even, to some
degree, pros.
Speaker 2 (05:33):
They aren't limited in their performance
improvements by a lack of dataor lack of exploiting data.
Amateurs are mostly limited bytime, like, yeah, you would just
get a lot better if you couldtrain 14 hours a week instead of
seven hours a week, but that'sjust not practical.
They're limited by body weight,like it's just like it can be
hard to maintain a good bodyweight with a modern lifestyle.
(05:55):
And they're limited by badsleep or just a million other
things.
That isn't necessarily like allthe science in the world Well,
I shouldn't say all the rest ofthe science in the world beyond
like the science that tells youthat sleep is important and that
not drinking beer will helpyour performances.
That's where the gains aregoing to be made, not like
(06:15):
having a you know billionparameter neural net telling you
how to, you know, win a cat torace better.
It's probably not going to movethe needle.
Speaker 1 (06:26):
Yeah, no, that's it entirely.
And I think too, the humanapproach is going to be able to
cut through the BS, uh, and say,hey, cody, you know what?
Let's not have three beerstonight.
You know that kind of thing.
Good thing, you're not my coach,but that's right, that's why,
that's why I'm not, but yeah, soI think like in that way, I
mean I, you know, I, I I don'twant the listeners to think that
(06:49):
I am just like Mr Data anddon't care about anything else I
think it's super cool, I reallythink it's going to enhance
this industry and there'sthere's some great stuff coming
out, uh, in training peaks andother platforms too, like, uh,
vecta you and I talked aboutthat as well as oh, intervalsicu
you and I had talked about thatkind of in our, in our pre talk
(07:11):
to a lot of this.
So you know, there's there'sdefinitely more than just
training peaks out there, and Ithink that that is healthy too,
because competition drivesinnovation and what we're seeing
out of, you know a lot of theseplatforms is being is better
because there's more game outthere in the field.
So, with that said, and kind ofwith that backdrop of
(07:34):
understanding how these systemswork and why they work a lot
with the automatic generation orauto updates and stuff, one of
the things in training peaks issomething that you've had for
years, which is an auto ftpupdate.
So let's have that as kind of alaunching pad of sorts.
Why would an auto update of ametric be useful and keep in
(07:58):
mind, like the ftp updatingthat's going to change all the
training zones and it's alsogoing to change, you know, ctl,
build, ramp rates, um and form,fatigue and all this kind of
stuff.
So it's an important one, whichis why I focus on it.
But why would it be helpful tohave an auto update and why
wouldn't it be helpful?
Speaker 2 (08:15):
yeah, and that's a perfect example of kind of a pre
and post like.
If you create a historicalpoint in time for like before ai
and after ai.
Like that's a good example,because the way it works in
training peaks now is verypre-AI.
It's been around, like you said, that was probably been around
in training peaks.
Since training peaks have madeit's very algorithmic, it's
(08:36):
really simple, it's prettyrudimentary and it'll just look
for power data or running dataor heart rate data and say, see,
like we talked about 95% timesyour 20 minute peak power.
It'll just look for that everyworkout and if you set a new
higher 95% of 20 minute peakpower, it'll update your
(08:57):
threshold.
Or you can set it to notify youthat, like this happened and
maybe you should update yourthreshold, which I think is a
better way that, like thishappened and maybe you should
update your threshold, which Ithink is a better way, like you
have to have a lot of faith in asystem to issue changes on your
behalf without alerting you.
So I would say like, yeah, getthe alert and double checking
and everything, but that's theonly thing.
It'll look for 60 minute powertoo.
(09:19):
So it'll look for two thingsand update your threshold based
on that.
But good coaches know likethere's a lot of other things
that might indicate thresholdchanges.
So it's really useful for likea coach or an athlete that has
like a system in place wherethey trust their power meter and
they know it's kind of going towork correctly for them.
Speaker 1 (09:37):
Perfect, because I was going to say I mean, there's
a lot of things that kind of gointo that from the coaching
standpoint, which you wouldn'twant that to automatic update.
I was just having thisdiscussion with another one of
my athletes because because hedid have like a peak all time,
uh, 20 minute power, and I said,well, let's not put it there
just yet, let's be conservativewith it.
(09:59):
Why?
Well, because I'm going toguide you through some workouts
where we're going to try torepeat a similar power or you
know, just under, to see howrepeatable you are there.
Because if we just go with that, you know the highest power
that you've done in your wholelife and then create all the
zones based on that, you'regoing to get blown out intensity
wise for or you could at leastright over intensify the athlete
(10:22):
.
So you're better off to be alittle bit more conservative,
because my general approachapproach is I would rather under
train you by 10% than overtrain you by 1%, because I will
get a better result in the longrun.
And so now you layer that withyou know bad data or somebody
that doesn't understand thesystem that is getting auto
updates on something asimportant as FTP, and if you
(10:44):
throw in FRC and all these kindof things, it's like you can
start to see pretty clear howspider webby and like confusing
and terrible it could be with atraining program that is based
on bad data.
Speaker 2 (10:56):
Yeah, so that kind of leads into like what the future
of that system would be, islike we didn't even talk about
it last time.
But ftp we talked about asbeing like a really simple,
practical thing.
But ftp and wko is a littlemore sophisticated because it's
modeled and estimated based on awhole range of data.
So it's looking at your entirepower curve, but especially
(11:18):
anywhere from like 12 minutes to60 minutes, and updating FTP
based on that, instead of just a20 minute power.
That's not AI, but it's moreyou know, kind of like you're
talking about.
It's more inclusive.
It's looking at like oh, didyou get really anaerobically
strong and that falselycontributed to this 20 minute
(11:40):
power reading?
It can account for that a lotbetter.
Or even just practical thingslike oh, you have an athlete who
has a perfect 18-minute longstretch of road to do a time
trial.
Well, that would work better.
It can collect race data In thefuture.
If we got something like thatinto Training Peaks as an
automatically updating FTP, amore modeled FTP based on all of
(12:02):
the data, that's when it getsreally, really useful because
you have less need for superprecise testing, less need for
specific dur races and thenhaving that whole like kind of
high dimensional data foreverybody sets the groundwork
(12:25):
for a more like ai based toolfor uh indicating these changes
yeah, well, not not to put youon the spot, but I mean, is that
, is that a future thing that'scoming out in the training peaks
uh online platform anytime soon?
Anytime soon.
Uh, I can't say um, probably,cause I don't know.
(12:46):
But um, what I can say is that,like training peaks had other,
we've been working on a lot ofother stuff for the past few
years.
You've seen strength like goodstrength training is more
important than ai, and so weknew we had to build a strength
builder.
First, convenience for coachesefficiency for coaches is more
(13:07):
important than ai metricestimation.
So we had to, like it wouldhave been very foolish of us to
put wko stuff and modeledmetrics into training peaks
before we let you automaticallyplan a recurring workout Like
that would have been silly.
So now that we've got a lot ofthose convenience things built
in, we have a lot of engineerswho are really excited and
(13:28):
really capable looking atplaying around with WKO, and
then also a lot of really smartproduct people looking at like
what are the most useful partsof WKO?
And some of these like otherlike kind of cutting edge
modeling systems.
What parts are kind of likemaybe falling flat?
For the majority of athletesthey only work in specific
situations that don't reallywork at all.
It's kind of a testing ground.
(13:49):
So what pieces can we pull out?
Speaker 1 (13:51):
And so, um, we are the most active in looking at
bringing those things intotraining peaks that we've ever
been in looking at bringingthose things into training peaks
that we've ever been, yeah,yeah, and you know, shout out to
everybody at training peaks um,because they think in that way,
right, rather than just beingum, super cool with all the data
(14:12):
or overly engineered orsomething like this, which I
mean.
Some of these other platforms,like, again, intervalsicu I've
really liked it, but there's alot it's, there's a lot of
engineering, ish type stuffthat's going on there, and so I
don't think an amateur personwould be able to just pick that
up and, and you know, fly withit as quickly as somebody like
(14:33):
Cody or myself or somebody whoyou know, who knows data well,
you know that kind of thingWhereas whereas training piece
it's much more like iphone,right, you can pick it up and
start using it pretty quickly ifyou're tech savvy, and so I
think that it's super smart ontheir end and, um, they, they
put they don't put the coaches.
(14:53):
Well, you can tell me if I'mwrong, but they put the coaches
and the athletes kind of like touh on the same meaning, like
how would a coach need to worktheir business to run quickly
with this and how can an athletetake this software and run
quickly with it, as opposed togetting bogged down into the
(15:14):
data.
It seems like that's what youguys do.
Speaker 2 (15:17):
Correct me if I'm wrong it seems like that's what
you guys do.
Correct me if I'm wrong.
Yeah, that's always been likekind of the driving principle is
like let's enable a coach andathlete to do their thing kind
of on their own as easily aspossible, and it's a good thing.
Other people are making thosedecisions, because I would have
fallen on the other side of like.
I see intervals, too, or I seeother apps and I'm like that's
really cool.
We should work on that nowExactly.
Thankfully, there's morepractical, practical people who
have coached 40 athletes at onceand understand how important
(15:39):
like real world stuff is and itpushes us to get those things
done fast, so then we can try tomove on to like not move on to,
but then like spend some timeon the cool stuff.
Speaker 1 (15:49):
Yeah, no, speaking of cool stuff, one of the things
that I've been involved with, uh, with y'all over at training
peaks and I know that there'sother I mean, there's a ton of
other coaches that are as wellbut the fueling insights tool
has been something that I gotreally excited about because, um
, uh, working with uh variouspeople to uh build a tool that
(16:11):
estimates kilojoule expenditureor calorie expenditure in order
for a workout, a race orwhatever you're doing in order
to get a better fueling plan forthe athlete, is essentially
what this tool does.
Can you tell us a little bitmore about that?
And I don't even know if it'slike, deployed to everybody just
yet or how much can we talkabout that?
Speaker 2 (16:34):
It should be.
I believe it's in everybody'saccount.
No, it might not be enabled bydefault, but you should be able
to go into your account settingsif you're a premium or a coach
and look for a data field on theworkout card that says fat
calories and carbohydratecalories instead of just total
calories for a workout, andthat's really.
It's just two little datafields that sit there.
(16:54):
But, like you said, kind of thebig thing we all know over the
past couple of years has beenlike the amount of fuel that
people take, Like it.
It boggles my mind.
Like you and I are kind of fromsimilar eras of racing.
It was it used to be one gel anhour and that was a kind of
like 25 gram gel, a 25 grand Joe.
Yeah, like, oh, a hundredcalories an hour of gel, you
have got glycogen, you'll befine.
(17:15):
And now I'm like reading abouthow much people are eating now,
and it's just a logisticalbattle, for how do you carry or
hand somebody that much food andthen how does your gut handle
it?
So, yeah, when you're talkingabout 100, 150, 200 grams an
hour of carbohydrate, and thenon the flip side, on the ultra
side, uh, fat at fat adaptationhas kind of like fallen out of
(17:38):
popular discourse, but I stillthink it's really important and
something to keep in mind islike oh, how much fat are you
burning?
How much fat could you beburning?
How much carbohydrate are youburning?
So, like a tool to like showyou a better estimate of that is
what this tool has been and wewanted to.
It took us a long time.
This was the kind of thingwhere if you just came up with
like an estimation algorithm,say like what some companies
(18:01):
will use for VO2max, you justcome up with an equation that's
pretty close, you know, see ifit's, check a regression against
it with real data and then plugthat in and it'll give you a
number which you could have donewith like, oh, everybody, once
they get to 60% of VO2 max or50% of threshold, that's where
they're going to be startburning more carbohydrate.
(18:22):
We could have done that, butinstead Inigo San Milan has been
doing a lot of research,collecting a lot of data.
He kind of had this inkling thatit's not consistent enough
among everybody, among everybody, and so his kind of big idea
was that and this is part of theconfiguration and training
peaks for it is that it'sgrouped based on, like kind of
(18:43):
your level in the sport and yoursex as well.
So those are both settings thatgo into this is, if you're a
beginner versus competitive,versus world class, the, the
ratio of carbohydrate and fatthat you burn at a given
intensity is actually prettydifferent among those groups.
So so we have to account forthat.
So there's a lot more data toput in, a lot more like cleaning
(19:03):
and picking that apart andfiguring out a good, clean way
to implement that with realworld data.
So that's what it's doing, kindof behind the scenes, and he's
written some blog articles forus Like, if you want to get in
the nitty gritty, he posts aboutit on.
I think he posts about it onhis own social media.
He's done a podcast with usabout it, so there's a lot more
(19:24):
information.
He could speak to better aboutit, but that's what it's doing
is like starting to help usunderstand nutritional, a good
estimation of nutritionaldemands for events.
Speaker 1 (19:29):
Yeah, yeah, that's absolutely it, and I want to get
them on this podcast to talk alittle bit more about that once
everything is, you know up andrunning and going.
But to kind of recap this forour listeners, it's you know the
kind of soup to nuts of it is.
It's like we know you'reexpending a lot of uh calories
while training.
When you're doing, um,endurance, uh sport with a lot
(19:53):
of intensity, it's morecarbohydrate.
When it's ultra stuff going allday, it's more fat.
Right.
So we can build the intensity,we can build a model to show how
much calories from carbohydrateyou're burning, how much from
fat you're burning, and thendevelop a fueling strategy on
that carbohydrate in particular,and then we just kind of lump
in like some sustenance.
That happens with, you know,the fat and some of the protein
(20:15):
that you're coming, but it'sgoing to be driven primarily
through carbohydrate and it's.
It's not like it hasn't changedwhat I'm doing as a coach, but
it's helped me to show it betterand I think that that's what's
so important, which, which iscrazy to me that you guys have
probably spent like yearsdeveloping this and working with
one of the greatest likecoaches and physiologists out
(20:38):
there right now to do this thing, where I'm just like, oh yeah,
it doesn't do anything different, like it doesn't change what I
do, but it validates what I do,which I think is powerful yeah,
yeah, that's I mean.
Speaker 2 (20:49):
Yeah, putting real numbers on helps.
And one thing we've seen whereit is changing people a lot is
people coaching very newathletes that like lowest group,
the most like entry level orlike least trained group.
It was surprising to all of us,to the point where we kind of
doubted it, like we, we kind ofdouble and triple check the data
that they hardly burn fat.
And that was kind of surprising.
(21:10):
Is that even at really lowintensities, yeah, so that is
starting to change.
Like you think like, oh, if yougo as a new athlete and weight
loss is part of your goal, like,oh, it actually could be harder
than you think, because as soonas you're at 30% of threshold,
which is really like not a realtraining level, you're already
burning almost entirelycarbohydrates.
(21:30):
So it's like oh, that can helpset expectations or change
fueling strategies for that typeof athlete.
Like oh, you're probably notgoing to, you're going to have
to rethink parts of this.
For that type of athlete.
Like oh, you're probably notgonna, you're going to have to
rethink parts of this for that.
And that was that was kind ofopening to some of us.
But yeah, then at the upper endit was like just putting solid
numbers on it and validating itto athletes.
Speaker 1 (21:49):
Yeah, no, totally agree with that, and so follow
up question to that for you,because I don't know.
This is, is, is is the feelinginsights tool available to
self-coached athletes on premiumsubscription to training things
it should be.
Speaker 2 (22:05):
I believe it is.
Speaker 1 (22:06):
I'm like 90, sure it is okay okay, we will confirm
that and put a link into becausethere are some articles out
there, we'll put a link into it.
Um, I just want to be sure thatI'm accurate in stating that
because, again, this is a newtool and for those who are
curious and they're self-coachedathletes, I would definitely
use this because, like Cody said, it's like if you're new to the
(22:27):
sport, this can.
This is another tool, anotherlayer to help guide you in the
stuff that's super hot right now, which is fueling, fueling your
body to meet the demands of, uh, whatever you're doing out
there, you know ultras, crit,racing, cross, whatever it is.
So, um, cody, we're kind ofgoing long here, but I I
(22:47):
definitely want to mention TPvirtual.
This is another tool that youguys have been rolling out.
I was on the original stuff.
Uh, I will say it was like coolbut buggy and lacking a couple
things and like recently, asI've been like utilizing it more
, it keeps on blowing my mindbecause of the enhancements to
it, because of how it works, butI think goes back to how you
(23:10):
like, how everybody at trainingpeaks kind of thinks with, like
the coach and the athlete herethey can pick it up and run with
it and also customize and letthe coach go do their thing with
it by building community.
Can you talk a little bit aboutTP Virtual, what it is and why
people listening should maybe gotry it?
Speaker 2 (23:26):
Yeah, tp Virtual is like our virtual training and
racing platform with kind of,like you said, two or three kind
of different pillars that Ithink make it kind of unique and
exciting One.
You talked about like communityand branding.
Other virtual platforms dopretty good with community too.
We have lots of like custombranding, so like if you as a
(23:47):
coach want to set up your ownteam kit and club kit, you send
us like a.
We have a format file, you sendus your kit, we set it up.
We're moving into more and morelike race branding, so like if
you set up a race series, thefinish banner and the things on
the side of the road can be yourclub or your events company or
your coaching company or justthe name of the series.
(24:08):
So you can like do a lot ofcustomization, get athletes,
like I said, a lot of athletesjust want to be a part of
something so they can feel like,oh, I'm in this group and then
like for the coach-athleterelationship, like a spectating
and coaching mode, and we'restill working on more stuff with
that so you can just like watchyour athlete race without
having to be like try to set upand be riding at the same time,
(24:29):
if you don't want to be Easierways to like watch racing for
like, if you have a whole squador a group of people riding.
And then to me, me the coolestpart but is it's got a high
focus on realism, especially forlike, how does road racing work
in the real world?
Can we make it as realistic aspossible in this world?
(24:50):
So the physics modeling is real,pretty realistic, as realistic
as any, but then also realisticcornering and drafting physics,
especially the cornering part.
So if you try to pedal through acorner, we can't make you crash
, but instead we can.
There's a penalty, there's alike a power and speed penalty,
so it'll slow you down comparedto somebody who coasts, knock
you out of the race line andthen your trainer will kind of
(25:13):
like, create resistance that youhave to pedal out of it, create
resistance that you have topedal out of it.
So it's like, oh, if you're acoach, coaching tactics,
coaching like cornering dynamics, can be hard to do in the real
world.
Especially, say, you haveathletes in the Midwest or
someplace cold, you could set upa weekly 45 minute race series
with all of your athletes spreadaround the world and like,
watch them do it and it's.
(25:34):
You know it's not perfectcompared to the real world, but
it's 20 hours of practicing,like having people work on their
team tactics together, becausethose aspects of the physics are
(26:02):
more realistic yeah, well, I Ido want to say there's nothing
wrong with staring at a wall andpedaling your bike when you
need some me time.
Yeah, oh so training peaksvirtual also has a zen mode and
and I can't remember the name ofthe other mode, I think it's
incognito mode or something zenmode turns off the display, so
(26:24):
all you see is like your workoutdata, and the other one removes
all of the other people so youcan ride alone.
Speaker 1 (26:29):
So I'm going to use that anyway.
So we don't need to get intothe psychology of coach AP right
now, but you can see everybodylistening, hopefully you can.
You can hear um, that thereit's evolving, right, like
there's, there's cool tech,there's cool stuff, cool tools
that are being pumped out andand and again.
Like this is one of them, right, so go try it, see if you like
(26:53):
it, um, and you know, if it'snot your cup of tea, cool, uh,
move on.
But I think in that way, likepeople who are creating and
innovating, um, you know, jumpinto that community, jump on
that bandwagon because, um, they, they are going to drive um
(27:24):
this this market.
Speaker 2 (27:25):
they're going to drive new things, so new things.
Probably the last two questionshere for you, Cody, Is there
any little?
Speaker 1 (27:28):
teasers of new things more that we can divulge for
our listeners that may be comingout sometime soon from Training
.
Speaker 2 (27:31):
Peaks.
I wish I could contributeWithout getting you fired, of
course, yeah, I wish I couldcontribute more, but almost most
of the really cool things we'reworking on right now Uh well,
there's a cool thing coming outin training peaks virtual soon,
so just pay attention.
I can't say anything about that, but it's, it's pretty, pretty
sweet.
Um, most of them are actuallyjust in flight enough that we've
talked about them.
Fueling insights, you know, notdone.
There's cool stuff gonna.
(27:51):
We don't actually know whatthose cool things are going to
be.
We need to start hearing frompeople using it.
But, like, we see this as abeginning.
Um, new sport types, againgoing back to like, kind of
fundamentals.
If you haven't noticed, we'restarting to add sub sport types,
so like, oh, you can add yogaor you can specify gravel biking
or indoor riding.
Um, again, basic, but really,really, I think, important
(28:12):
because it's been requested forso long.
Um, we talked about, like, weare doing the most research into
getting WKO ideas into trainingpeaks that we've ever done.
Um, so that's, that's exciting.
And, yeah, I guess, tell uswhat kind of things, what else
(28:34):
you want to see cool things thatshould be coming out.
Speaker 1 (28:37):
Yeah, I mean and I will put that to the listeners
In this way, you can write in tous.
I work with Cody, dirk, tony,many others at Training Peaks on
various whenever they reach outand ask stuff, but on various
projects that come up.
So if you're listening to thisand you say, man, it would be
(28:59):
super cool to have XYZ, feelfree to write in to us about it.
You can go to trainrightcombackslash podcast and click on
ask a training question and youjust submit it in to me there.
And when I'm talking with Codyor whoever else, um, I will
mention that in um, some of thecool stuff that we want to see.
I was just actually had ameeting, uh, like three weeks
(29:22):
ago, with um two of the engineer, like platform engineers, and
it was so cool because, like, Iwas definitely talking to people
who were, you know, supremelysmarter than I was, but they
were like asking the questionsof like.
I was definitely talking topeople who were, you know,
supremely smarter than I was,but they were like asking the
questions of like okay, so howdo you use the PD model to do
this?
And I'm like oh, my God this isa great question.
Let me tell you all about it,and I don't know what they're
(29:43):
going to do with thatinformation, but they said it
was really valuable, right?
So in that way, listeners um,kind of giving you a voice with
somebody who is helping to drivethe ship at Training Peaks
write in and tell us what youwant to hear more about.
So and I think that may be agood way to end this, cody is
there anything else that youwant to tell our listeners?
(30:05):
People who are likely usingTraining Peaks or they might be
using something else, are likelyusing training peaks or they
might be using something else.
Um, what do you want to say tothem as it pertains to data
hygiene?
Cool techie stuff.
I want the ai right now and I'mso confused.
Speaker 2 (30:23):
I just want to learn more and go fast on my bike uh,
I think you can cover all mostof the training and coaching
stuff.
I guess I should say one morething on AI.
We kind of alluded to it.
I think the best way to makeprogress with it if you're
already integrating a lot or youare curious about it is to do
some basic learning about howthey work, Especially like right
(30:45):
now.
Ai is such a big thing, but whatmost people are talking about
right now is LLMs and so like oh, can you, even if you're not a
super technical person, look upthe Matchbox neural network or
the Matchbox machine learningmodel.
It was like the first analogproof of concept for how a
(31:05):
neural network can learn and itwas done totally like literally
analog.
There were no electronicsinvolved.
It was about in the 1960s.
Go find a podcast or a 10minute YouTube video about how
that works.
Read a couple articles abouthow these things work and that
can help put you in such abetter frame of reference for
what they do, how they work andthen how you can realistically
(31:26):
use them.
It'll help you understand whattools it will help you, what
things it can help you do reallywell and avoid the things that
like oh, it's, that's how itworks.
It's never going to be able todo X now that I understand that,
so it's worth learning just alittle bit of the basics to like
.
You're hiring an assistant, solearn how they work.
Speaker 1 (31:47):
Wow, that is a great.
That is a great way to end thispodcast.
I think that's a really goodadvice.
I'm going to go do that myselfbecause I've been telling my, my
athletes as well as like onthis podcast like, learn how the
system works before you'recritical, before you you're you
buy it before you jump into it,before you just like learn more
(32:07):
of how it works.
Right, then go, do and thenkeep on learning, because I
think that is probably thehealthiest approach with any
system that you're pouring yourlife into.
Because, keep in mind I mean youspend 7, 10, 12 hours doing
this training thing.
You want to make sure that it'sactually going to give you the
(32:29):
result that you want.
So learn how the system worksExactly.
Yeah, cool, cody, I appreciateyour time so much.
We got two episodes out of youand a ton of knowledge.
So thank you for your time andplease tell Dirk and everybody
over at Training Peaks thatthank you for letting us steal
you for a little bit and, youknow, maybe this turns into more
(32:52):
podcasts down the road.
Speaker 2 (32:54):
Yeah, thanks for having me.
It was a great time.
Hope to be back.
Speaker 1 (32:57):
All right, Thanks, Cody.
Thanks for joining us on theTime Crunch Cyclist podcast.
We hope you enjoyed the show.
If you want even moreactionable training advice, head
over to trainwrightcombackslash newsletter and
subscribe to our free weeklypublication.
Each week you'll get in-depthtraining content that goes
(33:19):
beyond what we covered here onthe podcast.
That'll help you take yourtraining to the next level.
That's all for now.
Until next time, train hard,train smart, train right.
From the team at CTS.
This is the Time Crunch Cyclistpodcast, our show dedicated to
answering your trainingquestions and providing
actionable advice to help youimprove your performance even if
you're strapped for time.
I'm your host, coach AdamPulford, and I'm one of the over
50 professional coaches whomake up the team at CTS.
In each episode, I draw on ourteam's collective knowledge,
(00:30):
other coaches and experts in thefield to provide you with the
practical ways to get the mostout of your training and
ultimately become the bestcyclist that you can be.
Now on to our show.
Now on to our show.
(00:50):
Welcome back, time Crunch fans.
I'm your host, coach AdamPulford.
Picking up where we left offfrom last week, I am back with
Cody Stevenson of Training Peaksto discuss how best to utilize
your data in platforms likeTraining Peaks and maybe a sneak
peek of future enhancements tolook at into the future.
So, cody, welcome back.
Speaker 2 (01:09):
Glad to be back.
Speaker 1 (01:11):
All right, so maybe just like a quick recap from
last week is that we comparedFTP and FRC to critical power
and W prime, explaining thatthese are similar systems
insofar as they both determinehigh aerobic threshold point and
an anaerobic measurement whichhinges off of that threshold, so
to speak.
The former is more of a fieldand practical based, while the
(01:34):
latter is the more like researchand lab based, and either
system is completely fine to use.
You just need to know howyou're actually going to use it
and use the data within it tomake the best decisions for your
training decisions.
So now, if you're going to relyupon that like some sort of
like machine learning or AIpopulated things, to make those
(01:58):
training decisions for you, youneed good data, good, clean data
, as well as the knowledge ofhow the system works, because,
in my opinion, bad data inequals bad data out, and if your
model is bad, so will yourtraining.
Cody, would you agree with that?
Speaker 2 (02:13):
Yeah, yeah, definitely All right.
Speaker 1 (02:18):
Well, let's, let's pick up right where we left off,
which was talking about AI andCody.
I asked you is AI going to takeover this endurance coaching
space, yes or no?
And you said it might take somejobs.
Let's talk about that.
Speaker 2 (02:37):
Yeah, I think.
Well, I guess I'll start withthe jobs and I'll steal a saying
not mine, everybody's probablyheard it from every industry is
that you're not going to loseyour job to ai, but you're.
You might lose it to somebodywho's using ai better than you.
So it's, it's going to be auseful tool.
It's going to take care oftedious tasks, repetitive tasks,
(02:58):
tasks that um might be prone tohuman error, and so you can't
ignore it.
But taking over the wholeindustry, I, I, I don't think so
, mostly because one of the mostimportant lessons I learned
when I came from being anathlete to working at training
peaks you know, I was a high, Iwanted to be a high performing
athlete.
I cared about results.
I cared about and I was okaydoing it alone, like I liked
(03:21):
training alone.
I didn't work with a coach.
All that was fine.
It was when I started trainingpeaks.
It took me a long time to learnthat I was in the minority with
that.
Most people just want to be apart of something, and so one
thing they get out of endurancesports, even if they're pretty
high performing is relationships, and so that's a really
(03:44):
important part of what coachesdo, like I mean every coach out
there listening knows that youaren't just the guy who writes
the training plans or the girlwho writes the training plans.
You are the therapist, theSherpa, the tire pressure
advisor, everything else that anAI can't.
And a lot of times you justbecome their friend and that's
(04:10):
just like a piece that AI can'tdo.
But some of the parts that werepretty important for coaches 10
, 15 years ago, even now, aregoing to be done more and more
by AI.
Speaker 1 (04:19):
Yeah, yeah, no, I completely agree with all that,
and I would also say that whenI'm talking with my athletes,
when I'm, when I'm learningabout people and we learn this,
even like through COVID, rightit's just like the person to
person interaction is still sopowerful that, yeah, I don't, I
don't think it's going to go,yeah, I don't think AI is going
(04:40):
to take over and take every youknow coach's job and that kind
of stuff.
But, yeah, I think that thepeople, the athletes, the
listeners here that want thebenefit of kind of that
data-driven AI sort of you knowquicker sort of strategy, or
kind of you know kind of moreaccuracy, more consistency,
(05:02):
whatever AI is going to help uswith, yeah, they'll want to
coach that deals in thatcategory.
You know that works in thatspace, and so, um, there'll
probably be a delineation ofcoaches, um, in that way.
But I still know some coachestoo that are using Microsoft
Excel and they're great coaches,right, and they talk with their
athletes and they interact withtheir athletes Great.
So it's like you don't evenneed the data-driven approach
(05:24):
necessarily to do to be a goodcoach yeah, that that's the
thing is, most people mostlyamateurs, but even, to some
degree, pros.
Speaker 2 (05:33):
They aren't limited in their performance
improvements by a lack of dataor lack of exploiting data.
Amateurs are mostly limited bytime, like, yeah, you would just
get a lot better if you couldtrain 14 hours a week instead of
seven hours a week, but that'sjust not practical.
They're limited by body weight,like it's just like it can be
hard to maintain a good bodyweight with a modern lifestyle.
(05:55):
And they're limited by badsleep or just a million other
things.
That isn't necessarily like allthe science in the world Well,
I shouldn't say all the rest ofthe science in the world beyond
like the science that tells youthat sleep is important and that
not drinking beer will helpyour performances.
That's where the gains aregoing to be made, not like
(06:15):
having a you know billionparameter neural net telling you
how to, you know, win a cat torace better.
It's probably not going to movethe needle.
Speaker 1 (06:26):
Yeah, no, that's it entirely.
And I think too, the humanapproach is going to be able to
cut through the BS, uh, and say,hey, cody, you know what?
Let's not have three beerstonight.
You know that kind of thing.
Good thing, you're not my coach,but that's right, that's why,
that's why I'm not, but yeah, soI think like in that way, I
mean I, you know, I, I I don'twant the listeners to think that
(06:49):
I am just like Mr Data anddon't care about anything else I
think it's super cool, I reallythink it's going to enhance
this industry and there'sthere's some great stuff coming
out, uh, in training peaks andother platforms too, like, uh,
vecta you and I talked aboutthat as well as oh, intervalsicu
you and I had talked about thatkind of in our, in our pre talk
(07:11):
to a lot of this.
So you know, there's there'sdefinitely more than just
training peaks out there, and Ithink that that is healthy too,
because competition drivesinnovation and what we're seeing
out of, you know a lot of theseplatforms is being is better
because there's more game outthere in the field.
So, with that said, and kind ofwith that backdrop of
(07:34):
understanding how these systemswork and why they work a lot
with the automatic generation orauto updates and stuff, one of
the things in training peaks issomething that you've had for
years, which is an auto ftpupdate.
So let's have that as kind of alaunching pad of sorts.
Why would an auto update of ametric be useful and keep in
(07:58):
mind, like the ftp updatingthat's going to change all the
training zones and it's alsogoing to change, you know, ctl,
build, ramp rates, um and form,fatigue and all this kind of
stuff.
So it's an important one, whichis why I focus on it.
But why would it be helpful tohave an auto update and why
wouldn't it be helpful?
Speaker 2 (08:15):
yeah, and that's a perfect example of kind of a pre
and post like.
If you create a historicalpoint in time for like before ai
and after ai.
Like that's a good example,because the way it works in
training peaks now is verypre-AI.
It's been around, like you said, that was probably been around
in training peaks.
Since training peaks have madeit's very algorithmic, it's
(08:36):
really simple, it's prettyrudimentary and it'll just look
for power data or running dataor heart rate data and say, see,
like we talked about 95% timesyour 20 minute peak power.
It'll just look for that everyworkout and if you set a new
higher 95% of 20 minute peakpower, it'll update your
(08:57):
threshold.
Or you can set it to notify youthat, like this happened and
maybe you should update yourthreshold, which I think is a
better way that, like thishappened and maybe you should
update your threshold, which Ithink is a better way, like you
have to have a lot of faith in asystem to issue changes on your
behalf without alerting you.
So I would say like, yeah, getthe alert and double checking
and everything, but that's theonly thing.
It'll look for 60 minute powertoo.
(09:19):
So it'll look for two thingsand update your threshold based
on that.
But good coaches know likethere's a lot of other things
that might indicate thresholdchanges.
So it's really useful for likea coach or an athlete that has
like a system in place wherethey trust their power meter and
they know it's kind of going towork correctly for them.
Speaker 1 (09:37):
Perfect, because I was going to say I mean, there's
a lot of things that kind of gointo that from the coaching
standpoint, which you wouldn'twant that to automatic update.
I was just having thisdiscussion with another one of
my athletes because because hedid have like a peak all time,
uh, 20 minute power, and I said,well, let's not put it there
just yet, let's be conservativewith it.
(09:59):
Why?
Well, because I'm going toguide you through some workouts
where we're going to try torepeat a similar power or you
know, just under, to see howrepeatable you are there.
Because if we just go with that, you know the highest power
that you've done in your wholelife and then create all the
zones based on that, you'regoing to get blown out intensity
wise for or you could at leastright over intensify the athlete
(10:22):
.
So you're better off to be alittle bit more conservative,
because my general approachapproach is I would rather under
train you by 10% than overtrain you by 1%, because I will
get a better result in the longrun.
And so now you layer that withyou know bad data or somebody
that doesn't understand thesystem that is getting auto
updates on something asimportant as FTP, and if you
(10:44):
throw in FRC and all these kindof things, it's like you can
start to see pretty clear howspider webby and like confusing
and terrible it could be with atraining program that is based
on bad data.
Speaker 2 (10:56):
Yeah, so that kind of leads into like what the future
of that system would be, islike we didn't even talk about
it last time.
But ftp we talked about asbeing like a really simple,
practical thing.
But ftp and wko is a littlemore sophisticated because it's
modeled and estimated based on awhole range of data.
So it's looking at your entirepower curve, but especially
(11:18):
anywhere from like 12 minutes to60 minutes, and updating FTP
based on that, instead of just a20 minute power.
That's not AI, but it's moreyou know, kind of like you're
talking about.
It's more inclusive.
It's looking at like oh, didyou get really anaerobically
strong and that falselycontributed to this 20 minute
(11:40):
power reading?
It can account for that a lotbetter.
Or even just practical thingslike oh, you have an athlete who
has a perfect 18-minute longstretch of road to do a time
trial.
Well, that would work better.
It can collect race data In thefuture.
If we got something like thatinto Training Peaks as an
automatically updating FTP, amore modeled FTP based on all of
(12:02):
the data, that's when it getsreally, really useful because
you have less need for superprecise testing, less need for
specific dur races and thenhaving that whole like kind of
high dimensional data foreverybody sets the groundwork
(12:25):
for a more like ai based toolfor uh indicating these changes
yeah, well, not not to put youon the spot, but I mean, is that
, is that a future thing that'scoming out in the training peaks
uh online platform anytime soon?
Anytime soon.
Uh, I can't say um, probably,cause I don't know.
(12:46):
But um, what I can say is that,like training peaks had other,
we've been working on a lot ofother stuff for the past few
years.
You've seen strength like goodstrength training is more
important than ai, and so weknew we had to build a strength
builder.
First, convenience for coachesefficiency for coaches is more
(13:07):
important than ai metricestimation.
So we had to, like it wouldhave been very foolish of us to
put wko stuff and modeledmetrics into training peaks
before we let you automaticallyplan a recurring workout Like
that would have been silly.
So now that we've got a lot ofthose convenience things built
in, we have a lot of engineerswho are really excited and
(13:28):
really capable looking atplaying around with WKO, and
then also a lot of really smartproduct people looking at like
what are the most useful partsof WKO?
And some of these like otherlike kind of cutting edge
modeling systems.
What parts are kind of likemaybe falling flat?
For the majority of athletesthey only work in specific
situations that don't reallywork at all.
It's kind of a testing ground.
(13:49):
So what pieces can we pull out?
Speaker 1 (13:51):
And so, um, we are the most active in looking at
bringing those things intotraining peaks that we've ever
been in looking at bringingthose things into training peaks
that we've ever been, yeah,yeah, and you know, shout out to
everybody at training peaks um,because they think in that way,
right, rather than just beingum, super cool with all the data
(14:12):
or overly engineered orsomething like this, which I
mean.
Some of these other platforms,like, again, intervalsicu I've
really liked it, but there's alot it's, there's a lot of
engineering, ish type stuffthat's going on there, and so I
don't think an amateur personwould be able to just pick that
up and, and you know, fly withit as quickly as somebody like
(14:33):
Cody or myself or somebody whoyou know, who knows data well,
you know that kind of thingWhereas whereas training piece
it's much more like iphone,right, you can pick it up and
start using it pretty quickly ifyou're tech savvy, and so I
think that it's super smart ontheir end and, um, they, they
put they don't put the coaches.
(14:53):
Well, you can tell me if I'mwrong, but they put the coaches
and the athletes kind of like touh on the same meaning, like
how would a coach need to worktheir business to run quickly
with this and how can an athletetake this software and run
quickly with it, as opposed togetting bogged down into the
(15:14):
data.
It seems like that's what youguys do.
Speaker 2 (15:17):
Correct me if I'm wrong it seems like that's what
you guys do.
Correct me if I'm wrong.
Yeah, that's always been likekind of the driving principle is
like let's enable a coach andathlete to do their thing kind
of on their own as easily aspossible, and it's a good thing.
Other people are making thosedecisions, because I would have
fallen on the other side of like.
I see intervals, too, or I seeother apps and I'm like that's
really cool.
We should work on that nowExactly.
Thankfully, there's morepractical, practical people who
have coached 40 athletes at onceand understand how important
(15:39):
like real world stuff is and itpushes us to get those things
done fast, so then we can try tomove on to like not move on to,
but then like spend some timeon the cool stuff.
Speaker 1 (15:49):
Yeah, no, speaking of cool stuff, one of the things
that I've been involved with, uh, with y'all over at training
peaks and I know that there'sother I mean, there's a ton of
other coaches that are as wellbut the fueling insights tool
has been something that I gotreally excited about because, um
, uh, working with uh variouspeople to uh build a tool that
(16:11):
estimates kilojoule expenditureor calorie expenditure in order
for a workout, a race orwhatever you're doing in order
to get a better fueling plan forthe athlete, is essentially
what this tool does.
Can you tell us a little bitmore about that?
And I don't even know if it'slike, deployed to everybody just
yet or how much can we talkabout that?
Speaker 2 (16:34):
It should be.
I believe it's in everybody'saccount.
No, it might not be enabled bydefault, but you should be able
to go into your account settingsif you're a premium or a coach
and look for a data field on theworkout card that says fat
calories and carbohydratecalories instead of just total
calories for a workout, andthat's really.
It's just two little datafields that sit there.
(16:54):
But, like you said, kind of thebig thing we all know over the
past couple of years has beenlike the amount of fuel that
people take, Like it.
It boggles my mind.
Like you and I are kind of fromsimilar eras of racing.
It was it used to be one gel anhour and that was a kind of
like 25 gram gel, a 25 grand Joe.
Yeah, like, oh, a hundredcalories an hour of gel, you
have got glycogen, you'll befine.
(17:15):
And now I'm like reading abouthow much people are eating now,
and it's just a logisticalbattle, for how do you carry or
hand somebody that much food andthen how does your gut handle
it?
So, yeah, when you're talkingabout 100, 150, 200 grams an
hour of carbohydrate, and thenon the flip side, on the ultra
side, uh, fat at fat adaptationhas kind of like fallen out of
(17:38):
popular discourse, but I stillthink it's really important and
something to keep in mind islike oh, how much fat are you
burning?
How much fat could you beburning?
How much carbohydrate are youburning?
So, like a tool to like showyou a better estimate of that is
what this tool has been and wewanted to.
It took us a long time.
This was the kind of thingwhere if you just came up with
like an estimation algorithm,say like what some companies
(18:01):
will use for VO2max, you justcome up with an equation that's
pretty close, you know, see ifit's, check a regression against
it with real data and then plugthat in and it'll give you a
number which you could have donewith like, oh, everybody, once
they get to 60% of VO2 max or50% of threshold, that's where
they're going to be startburning more carbohydrate.
(18:22):
We could have done that, butinstead Inigo San Milan has been
doing a lot of research,collecting a lot of data.
He kind of had this inkling thatit's not consistent enough
among everybody, among everybody, and so his kind of big idea
was that and this is part of theconfiguration and training
peaks for it is that it'sgrouped based on, like kind of
(18:43):
your level in the sport and yoursex as well.
So those are both settings thatgo into this is, if you're a
beginner versus competitive,versus world class, the, the
ratio of carbohydrate and fatthat you burn at a given
intensity is actually prettydifferent among those groups.
So so we have to account forthat.
So there's a lot more data toput in, a lot more like cleaning
(19:03):
and picking that apart andfiguring out a good, clean way
to implement that with realworld data.
So that's what it's doing, kindof behind the scenes, and he's
written some blog articles forus Like, if you want to get in
the nitty gritty, he posts aboutit on.
I think he posts about it onhis own social media.
He's done a podcast with usabout it, so there's a lot more
(19:24):
information.
He could speak to better aboutit, but that's what it's doing
is like starting to help usunderstand nutritional, a good
estimation of nutritionaldemands for events.
Speaker 1 (19:29):
Yeah, yeah, that's absolutely it, and I want to get
them on this podcast to talk alittle bit more about that once
everything is, you know up andrunning and going.
But to kind of recap this forour listeners, it's you know the
kind of soup to nuts of it is.
It's like we know you'reexpending a lot of uh calories
while training.
When you're doing, um,endurance, uh sport with a lot
(19:53):
of intensity, it's morecarbohydrate.
When it's ultra stuff going allday, it's more fat.
Right.
So we can build the intensity,we can build a model to show how
much calories from carbohydrateyou're burning, how much from
fat you're burning, and thendevelop a fueling strategy on
that carbohydrate in particular,and then we just kind of lump
in like some sustenance.
That happens with, you know,the fat and some of the protein
(20:15):
that you're coming, but it'sgoing to be driven primarily
through carbohydrate and it's.
It's not like it hasn't changedwhat I'm doing as a coach, but
it's helped me to show it betterand I think that that's what's
so important, which, which iscrazy to me that you guys have
probably spent like yearsdeveloping this and working with
one of the greatest likecoaches and physiologists out
(20:38):
there right now to do this thing, where I'm just like, oh yeah,
it doesn't do anything different, like it doesn't change what I
do, but it validates what I do,which I think is powerful yeah,
yeah, that's I mean.
Speaker 2 (20:49):
Yeah, putting real numbers on helps.
And one thing we've seen whereit is changing people a lot is
people coaching very newathletes that like lowest group,
the most like entry level orlike least trained group.
It was surprising to all of us,to the point where we kind of
doubted it, like we, we kind ofdouble and triple check the data
that they hardly burn fat.
And that was kind of surprising.
(21:10):
Is that even at really lowintensities, yeah, so that is
starting to change.
Like you think like, oh, if yougo as a new athlete and weight
loss is part of your goal, like,oh, it actually could be harder
than you think, because as soonas you're at 30% of threshold,
which is really like not a realtraining level, you're already
burning almost entirelycarbohydrates.
(21:30):
So it's like oh, that can helpset expectations or change
fueling strategies for that typeof athlete.
Like oh, you're probably notgoing to, you're going to have
to rethink parts of this.
For that type of athlete.
Like oh, you're probably notgonna, you're going to have to
rethink parts of this for that.
And that was that was kind ofopening to some of us.
But yeah, then at the upper endit was like just putting solid
numbers on it and validating itto athletes.
Speaker 1 (21:49):
Yeah, no, totally agree with that, and so follow
up question to that for you,because I don't know.
This is, is, is is the feelinginsights tool available to
self-coached athletes on premiumsubscription to training things
it should be.
Speaker 2 (22:05):
I believe it is.
Speaker 1 (22:06):
I'm like 90, sure it is okay okay, we will confirm
that and put a link into becausethere are some articles out
there, we'll put a link into it.
Um, I just want to be sure thatI'm accurate in stating that
because, again, this is a newtool and for those who are
curious and they're self-coachedathletes, I would definitely
use this because, like Cody said, it's like if you're new to the
(22:27):
sport, this can.
This is another tool, anotherlayer to help guide you in the
stuff that's super hot right now, which is fueling, fueling your
body to meet the demands of, uh, whatever you're doing out
there, you know ultras, crit,racing, cross, whatever it is.
So, um, cody, we're kind ofgoing long here, but I I
(22:47):
definitely want to mention TPvirtual.
This is another tool that youguys have been rolling out.
I was on the original stuff.
Uh, I will say it was like coolbut buggy and lacking a couple
things and like recently, asI've been like utilizing it more
, it keeps on blowing my mindbecause of the enhancements to
it, because of how it works, butI think goes back to how you
(23:10):
like, how everybody at trainingpeaks kind of thinks with, like
the coach and the athlete herethey can pick it up and run with
it and also customize and letthe coach go do their thing with
it by building community.
Can you talk a little bit aboutTP Virtual, what it is and why
people listening should maybe gotry it?
Speaker 2 (23:26):
Yeah, tp Virtual is like our virtual training and
racing platform with kind of,like you said, two or three kind
of different pillars that Ithink make it kind of unique and
exciting One.
You talked about like communityand branding.
Other virtual platforms dopretty good with community too.
We have lots of like custombranding, so like if you as a
(23:47):
coach want to set up your ownteam kit and club kit, you send
us like a.
We have a format file, you sendus your kit, we set it up.
We're moving into more and morelike race branding, so like if
you set up a race series, thefinish banner and the things on
the side of the road can be yourclub or your events company or
your coaching company or justthe name of the series.
(24:08):
So you can like do a lot ofcustomization, get athletes,
like I said, a lot of athletesjust want to be a part of
something so they can feel like,oh, I'm in this group and then
like for the coach-athleterelationship, like a spectating
and coaching mode, and we'restill working on more stuff with
that so you can just like watchyour athlete race without
having to be like try to set upand be riding at the same time,
(24:29):
if you don't want to be Easierways to like watch racing for
like, if you have a whole squador a group of people riding.
And then to me, me the coolestpart but is it's got a high
focus on realism, especially forlike, how does road racing work
in the real world?
Can we make it as realistic aspossible in this world?
(24:50):
So the physics modeling is real,pretty realistic, as realistic
as any, but then also realisticcornering and drafting physics,
especially the cornering part.
So if you try to pedal through acorner, we can't make you crash
, but instead we can.
There's a penalty, there's alike a power and speed penalty,
so it'll slow you down comparedto somebody who coasts, knock
you out of the race line andthen your trainer will kind of
(25:13):
like, create resistance that youhave to pedal out of it, create
resistance that you have topedal out of it.
So it's like, oh, if you're acoach, coaching tactics,
coaching like cornering dynamics, can be hard to do in the real
world.
Especially, say, you haveathletes in the Midwest or
someplace cold, you could set upa weekly 45 minute race series
with all of your athletes spreadaround the world and like,
watch them do it and it's.
(25:34):
You know it's not perfectcompared to the real world, but
it's 20 hours of practicing,like having people work on their
team tactics together, becausethose aspects of the physics are
(26:02):
more realistic yeah, well, I Ido want to say there's nothing
wrong with staring at a wall andpedaling your bike when you
need some me time.
Yeah, oh so training peaksvirtual also has a zen mode and
and I can't remember the name ofthe other mode, I think it's
incognito mode or something zenmode turns off the display, so
(26:24):
all you see is like your workoutdata, and the other one removes
all of the other people so youcan ride alone.
Speaker 1 (26:29):
So I'm going to use that anyway.
So we don't need to get intothe psychology of coach AP right
now, but you can see everybodylistening, hopefully you can.
You can hear um, that thereit's evolving, right, like
there's, there's cool tech,there's cool stuff, cool tools
that are being pumped out andand and again.
Like this is one of them, right, so go try it, see if you like
(26:53):
it, um, and you know, if it'snot your cup of tea, cool, uh,
move on.
But I think in that way, likepeople who are creating and
innovating, um, you know, jumpinto that community, jump on
that bandwagon because, um, they, they are going to drive um
(27:24):
this this market.
Speaker 2 (27:25):
they're going to drive new things, so new things.
Probably the last two questionshere for you, Cody, Is there
any little?
Speaker 1 (27:28):
teasers of new things more that we can divulge for
our listeners that may be comingout sometime soon from Training
.
Speaker 2 (27:31):
Peaks.
I wish I could contributeWithout getting you fired, of
course, yeah, I wish I couldcontribute more, but almost most
of the really cool things we'reworking on right now Uh well,
there's a cool thing coming outin training peaks virtual soon,
so just pay attention.
I can't say anything about that, but it's, it's pretty, pretty
sweet.
Um, most of them are actuallyjust in flight enough that we've
talked about them.
Fueling insights, you know, notdone.
There's cool stuff gonna.
(27:51):
We don't actually know whatthose cool things are going to
be.
We need to start hearing frompeople using it.
But, like, we see this as abeginning.
Um, new sport types, againgoing back to like, kind of
fundamentals.
If you haven't noticed, we'restarting to add sub sport types,
so like, oh, you can add yogaor you can specify gravel biking
or indoor riding.
Um, again, basic, but really,really, I think, important
(28:12):
because it's been requested forso long.
Um, we talked about, like, weare doing the most research into
getting WKO ideas into trainingpeaks that we've ever done.
Um, so that's, that's exciting.
And, yeah, I guess, tell uswhat kind of things, what else
(28:34):
you want to see cool things thatshould be coming out.
Speaker 1 (28:37):
Yeah, I mean and I will put that to the listeners
In this way, you can write in tous.
I work with Cody, dirk, tony,many others at Training Peaks on
various whenever they reach outand ask stuff, but on various
projects that come up.
So if you're listening to thisand you say, man, it would be
(28:59):
super cool to have XYZ, feelfree to write in to us about it.
You can go to trainrightcombackslash podcast and click on
ask a training question and youjust submit it in to me there.
And when I'm talking with Codyor whoever else, um, I will
mention that in um, some of thecool stuff that we want to see.
I was just actually had ameeting, uh, like three weeks
(29:22):
ago, with um two of the engineer, like platform engineers, and
it was so cool because, like, Iwas definitely talking to people
who were, you know, supremelysmarter than I was, but they
were like asking the questionsof like.
I was definitely talking topeople who were, you know,
supremely smarter than I was,but they were like asking the
questions of like okay, so howdo you use the PD model to do
this?
And I'm like oh, my God this isa great question.
Let me tell you all about it,and I don't know what they're
(29:43):
going to do with thatinformation, but they said it
was really valuable, right?
So in that way, listeners um,kind of giving you a voice with
somebody who is helping to drivethe ship at Training Peaks
write in and tell us what youwant to hear more about.
So and I think that may be agood way to end this, cody is
there anything else that youwant to tell our listeners?
(30:05):
People who are likely usingTraining Peaks or they might be
using something else, are likelyusing training peaks or they
might be using something else.
Um, what do you want to say tothem as it pertains to data
hygiene?
Cool techie stuff.
I want the ai right now and I'mso confused.
Speaker 2 (30:23):
I just want to learn more and go fast on my bike uh,
I think you can cover all mostof the training and coaching
stuff.
I guess I should say one morething on AI.
We kind of alluded to it.
I think the best way to makeprogress with it if you're
already integrating a lot or youare curious about it is to do
some basic learning about howthey work, Especially like right
(30:45):
now.
Ai is such a big thing, but whatmost people are talking about
right now is LLMs and so like oh, can you, even if you're not a
super technical person, look upthe Matchbox neural network or
the Matchbox machine learningmodel.
It was like the first analogproof of concept for how a
(31:05):
neural network can learn and itwas done totally like literally
analog.
There were no electronicsinvolved.
It was about in the 1960s.
Go find a podcast or a 10minute YouTube video about how
that works.
Read a couple articles abouthow these things work and that
can help put you in such abetter frame of reference for
what they do, how they work andthen how you can realistically
(31:26):
use them.
It'll help you understand whattools it will help you, what
things it can help you do reallywell and avoid the things that
like oh, it's, that's how itworks.
It's never going to be able todo X now that I understand that,
so it's worth learning just alittle bit of the basics to like
.
You're hiring an assistant, solearn how they work.
Speaker 1 (31:47):
Wow, that is a great.
That is a great way to end thispodcast.
I think that's a really goodadvice.
I'm going to go do that myselfbecause I've been telling my, my
athletes as well as like onthis podcast like, learn how the
system works before you'recritical, before you you're you
buy it before you jump into it,before you just like learn more
(32:07):
of how it works.
Right, then go, do and thenkeep on learning, because I
think that is probably thehealthiest approach with any
system that you're pouring yourlife into.
Because, keep in mind I mean youspend 7, 10, 12 hours doing
this training thing.
You want to make sure that it'sactually going to give you the
(32:29):
result that you want.
So learn how the system worksExactly.
Yeah, cool, cody, I appreciateyour time so much.
We got two episodes out of youand a ton of knowledge.
So thank you for your time andplease tell Dirk and everybody
over at Training Peaks thatthank you for letting us steal
you for a little bit and, youknow, maybe this turns into more
(32:52):
podcasts down the road.
Speaker 2 (32:54):
Yeah, thanks for having me.
It was a great time.
Hope to be back.
Speaker 1 (32:57):
All right, Thanks, Cody.
Thanks for joining us on theTime Crunch Cyclist podcast.
We hope you enjoyed the show.
If you want even moreactionable training advice, head
over to trainwrightcombackslash newsletter and
subscribe to our free weeklypublication.
Each week you'll get in-depthtraining content that goes
(33:19):
beyond what we covered here onthe podcast.
That'll help you take yourtraining to the next level.
That's all for now.
Until next time, train hard,train smart, train right.
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