Brian Shoemaker - What Life Time's 190 Clubs Taught Him About Killing Features

Brian Shoemaker is Senior Director of Innovation at Life Time, where he runs Life Time Labs and the company's new Innovation Hub.

He started as a developer and spent 24 years across companies like Intel, Dow Jones, and Thomson Reuters before landing at Life Time, where he's spent the last decade deciding which product bets get a shot across the company's 190 clubs. He's also an Ironman finisher and Leadville 100 MTB finisher.

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Marco: Brian, how's it going? How are you?

Brian: Good. How are you guys doing?

Jonas: Doing well.

Marco: Nice to meet you, Brian. I think I only had the opportunity to see you in different posts on LinkedIn and at different events. So you are very active. Very, very active, right?

Brian: I'm trying to be a little more lately. Just trying to raise more awareness about what we do at Life Time. And I think every bit helps. It can't just be Life Time's company page on LinkedIn.

Marco: Where are you based, Brian, in DC?

Brian: Chanhassen in Minnesota, which is in the southwest suburbs of Minneapolis.

Marco: Yeah, that's good. I didn't know they also had headquarters there.

Brian: Yeah, that's right. We were founded in Minnesota. I think Minnesota still has the most Life Time locations, but we expanded from there. Texas, New York, California, all over the country, about 190, I think over 190 clubs at this point.

Marco: That's great. Well, thank you so much for your time, Brian.

Brian: Definitely.

Marco: It's going to be a really interesting conversation with you. Your background, it's amazing. It's really amazing because you started as a developer, which is great. And then from there, you started to build your own brand and yourself. But now you are more visible, speaking and representing the brand. So it's really cool, that part.

Brian: Yeah, it's been kind of an evolution over time. I feel like starting out as a dev and an individual contributor, kind of gives me a different perspective than a lot of others that are more of those leadership roles that I get to work with. So I've been in the trenches.

Jonas: Awesome. Well, to kick things off, we want to start with rapid fire questions, Brian. Anthropic or OpenAI, Claude or ChatGPT? What's your favorite currently?

Brian: Anthropic, Claude. I think I made the switch from ChatGPT a little over a year ago. I think Claude Code really was a big driver for a lot of people to switch their preference over to Claude. And then just some policy and some company perspectives on OpenAI versus Anthropic kind of solidified that decision. And then we've adopted Claude here internally at Life Time as well.

Marco: Nice. Now, favorite fitness or wellness product? Right now.

Brian: Well, right now, I've been digging the Garmin fēnix 8. It does everything I need. The battery life is ridiculously long. I actually think having buttons instead of a touchscreen is a lot better as well, especially when you're swimming. It's not new, but it's a really reliable device and I love it.

Jonas: Window seat or aisle seat?

Brian: Window. I'm a tall guy and I kind of need to fold myself into the corner there. Otherwise, the drink cart is hitting me in the elbow all the time.

Marco: Red or black?

Brian: Black.

Marco: That was obvious, almost, from the T-shirt, right?

Brian: Yeah, exactly.

Jonas: Early bird or night owl?

Brian: Early bird. My training is usually in the morning. And when I was doing IRONMAN, that kind of solidified that. It's the only time of the day I had. So I'm usually up at 5, 5:30, getting on with my day and kind of had that feeling of, "Hey, I accomplished something today in the morning and I don't have to worry about it throughout the rest of the day."

Marco: I wanted to ask cardio or strength as one of the questions, but I guess it was the IRONMAN.

Brian: Oh, no, no. It's both, man. Absolutely both.

Jonas: Absolutely. I guess there's a preference for the cardio side, I assume.

Brian: Well, initially, yeah. Especially when I was really deep into IRONMAN, there was no strength training. I figured I was getting everything I needed with swim, bike, run. If I could go back in time and tell young Brian, "No, you need to incorporate strength training as part of your training regimen," I definitely would. Once I started folding in strength training, I saw that I just felt better. My injury rate went down considerably. And I was able to recover faster as well. And then after COVID, I think I got the IRONMAN bug out of me, I mostly focus on mountain biking and gravel, but then I am incorporating strength training three or four times a week. You've seen the hybrid fitness trend kind of grow for three years. Life Time launched LT Games, which is our hybrid fitness competition that I participated in in October. I loved it. This was so different than anything I've ever done.

Brian: The type of athlete that shows up for these things is totally different than what I'm used to. And I can't wait to do it again.

Marco: When you say different, in what sense? What type of athlete?

Brian: Just on the strength side. So when I show up at the starting line for like a gravel race, for example, it's a lot of skinny dudes. And it's obviously outside. And an endurance event is going to take six, nine hours to complete. But just the agility, the grace, the strength, and just like the raw power of these athletes that showed up at these competitions, I'm not used to being around that. And I was just in awe. And I stuck around. I just watched for hours of this competition. And it was so great. It's a community I'm just not usually a part of. And it was great to see.

Jonas: That's really cool. AI feature that's actually useful for you.

Brian: Deep research, vibe coding, just on the research side, getting to the point now where I'm able to draft a dossier on startups that are applying to Life Time's Innovation Hub and learn a little bit more about them. Even doing like legal research, drafting contracts, reviewing terms. I love the power, the self-service of having an assistant with me. And then on the coding side, you know, listen, I feel like I'm losing my nerd cred. Every month. And just talking to a lot of others who are in the same boat. It's just been a ton of fun to rediscover building things like I used to with an assist. And then actually having the skills then to deploy them to production and use them. So it's been both super useful and a lot more fun than I expected.

Marco: By the way, what are your thoughts around the legal stuff? Because probably your legal department says different things.

Brian: So on the personal side, I've actually had to navigate like the Minnesota court system, had a contractor dispute and just being able to draft documents and navigate the system. I don't know how mere mortals do this without an attorney. And then within Life Time, I will take a first pass at drafting things like a pilot agreement or reviewing terms and then sharing that with our legal team. I'm not sure if they appreciate that or not.

Marco: Probably not. Everyone thinks that they're an attorney now maybe.

Brian: But we also provide tools for our legal team as well to help with research and drafting contracts and the like. So I think it just makes everyone better. And anytime when we can give some support and enable self-service is a great thing.

Jonas: I'm going to double down on that AI question. More so personal use. Anything you came across like this is where AI has been really, really helpful in your personal life apart from like the professional side?

Brian: Yeah, a few things. MCP servers and then being able to connect them to Claude. So I've got this, I guess, environment now where using Claude Desktop combined with Todoist for task management and then Bear is my note-taking app that uses Markdown. Just the combination of those three things, being able to do research, set up tasks to do later, summarize that research in my notes has collapsed the time it takes me to get things done. So I think the expansion of MCP connectors with these desktop agents is super useful. And then just helping me enable like hobby projects. My kids and I are always building something with Arduino or Raspberry Pi. And instead of trying to hunt down instructions or guess at things, just being able to really go deep and build some really fun projects together that with detailed kind of step-by-step directions when we get stuck has made that a lot of fun.

Marco: I need to double down on that one because I'm also doing a big project with my kids. I have two kids and now they have their own 3D printer and now with Claude, they are doing their own toys. It's super funny. It's super funny. I have to be over there with them, of course, but it's really interesting now that what they can build with ChatGPT, between ChatGPT and the 3D printer, it's amazing.

Brian: It is. And it's a lot better than 3D printing keychains and like little tchotchkes, right? It's something potentially super useful. My dad, when he retired maybe five, six years ago, got into 3D printing and he is like looking for things around the house that have broken that he can fix through 3D printing. He gets so excited. And then now that I've turned him on to trying to use, again, Claude to help complement his projects, he's just, I mean, if this is what retirement is like, then great. I'm looking forward to it.

Marco: I agree.

Jonas: Yeah. Marco is doing his own summer camp with the kids currently at home because logistical challenges. So there had to be some creativity. ChatGPT and Claude are helping massively. Great. Most underrated metric in product.

Brian: I would say the L28 chart, right? So L28 is that count of distinct days that a user opens the app in a, I guess, trailing 28-day window, right? So it's a stickiness metric. It answers, "Hey, how habitual is usage of this app? Is it someone's daily driver?" So you can imagine on the X axis, you've got zero through 28 days. On the Y axis, you've got maybe a number of users. And Life Time, we're always trying to push the highest bar of users further and further to the right, indicating that it's sticky. People are launching a Life Time mobile app as maybe their daily driver. You can imagine an app like MyFitnessPal, you're using that every day if you're into it to log your food. And Life Time wants to be that trusted, that dependable, and keep pushing our L28, I guess, highest bar, or our trend further and further to the right.

Marco: Awesome. Probably this is going to be the last one. But I want to hear from you, a pilot that looked great in one club but never survived.

Brian: So if that pilot requires like a lot of training and puts a heavy burden on the club staff, it's never going to work. It's never going to scale. Or if the feature is something that like corporate is mandating, you know, kind of pushing on the clubs rather than the club asking for it, you know, pulling on the feature, it won't stick. So both things, when we launch a pilot and try to determine, "Hey, is this something that we want to scale beyond three clubs?" That is a big metric. That is a big question that we ask ourselves before scaling to 100, and now 190-some Life Time locations.

Marco: Makes sense. Do you have any example?

Brian: So I would say one, for checking in at the club, we tried, we experimented with face recognition, maybe like soon after COVID, and tried a variety of methods and just trying to train up the staff, like, "Hey, no, you don't have to ask them to swipe their card. You can just look down and see whether they had already been detected." And sometimes it didn't work. And it just robbed them of that human connection, greeting someone when they enter the club, and then trying to explain like how the system... It was really immature. The technology was very immature at the time. And that was a great example of something that we're just like, "This will... Even if the technology was great, it puts too much of a burden on that club staff." And we abandoned it. I would say with the labs team, I don't have a hard metric, but maybe 30% of our projects ever go to production.

Brian: We learn a lot, and then we document it for future reference. But we're always really cognizant of, "Is this enhancing the member experience or is this improving club operations?"

Marco: That's interesting. So when you document all these features that didn't work, eventually, maybe when the timing is correct, then you can use it again? Or do you have any case like that? Like, "This pilot didn't work right now." But then, I don't know, after two, three years, five years, do you retake that feature and start... Do you try again?

Brian: Yes, I've got one right now. So pre-COVID, we wanted to understand equipment use on the fitness floor. So how often were pieces of equipment getting used? The camera analytics technology didn't exist at the time, and not every piece of equipment is powered and online. So what we settled on was putting little coin-cell-battery-powered vibration sensors on fitness equipment. And then when the machine is in use, it vibrates and then transmits that over ANT+ to radio receivers that we have in the club anyway. And then we log that data. So we actually paired each sensor to that piece of equipment in our asset catalog. And then we were able to visualize over time, like, use. And it was interesting. Those batteries don't last forever. And we have to hide them on the equipment. It's kind of hard to find them when the battery dies. And it was just very difficult to understand how we could possibly support this going forward.

Brian: So that was the early indications of like a facilities intelligence or digital twin type of platform. So super useful for club staff, but at the time, very difficult to implement. Fast forward to today, we've dusted off that documentation, we want to revisit our facilities intelligence project. So now we're forming a new pilot that uses a combination of telemetry off the equipment from our equipment vendors, such as Technogym and Life Fitness. And then for unpowered equipment, we've got cameras, security cameras everywhere. And now the platforms exist where we can essentially draw a box around each piece of equipment and monitor their use at the edge. No data, no video rather is leaving our facility, but we're processing it at the edge.

Brian: So we're able to combine telemetry from the equipment and the camera analytics and understand what equipment is getting used, get perhaps predictive maintenance alerts logged to our service catalog, and then get recommendations on how to swap equipment around to even out the use of like treadmills, for example, if the one on the end is always the most popular, perhaps get recommendations on how to move things around to even the wear and tear on the treadmills. So that's a case where we tried this before and it didn't work, but we documented what we did. And then four or five years later, we're dusting that off and trying again with new technology.

Marco: This is awesome. This is super interesting. I was about to say in the first pilot, and then every time the cleaning staff comes and cleans the machine, the vibrations kind of count as usage?

Brian: Exactly. There was a lot of noise and it was very difficult to separate the signal from the noise on the equipment use, but we learned a lot along the way. And then especially on the camera side, there's a lot of startups that are getting into that space of being able to leverage computer vision for the purposes of analytics by doing measurements through video. The video doesn't leave the hardware; it stays at the edge. And then we get the telemetry, we get the data from that monitoring. So that was not a thing five years ago, six years ago. So we're taking advantage of it now, we're going to pilot at one club. And then if it works, we'll pilot at maybe three to five clubs. And then from there, since the cost is very low, this might be something that we roll out across all locations over the next three to five years.

Jonas: Great. Cost obviously is a very important aspect, especially when you think about scale, right? 180-plus locations, etc. When you look at this from a product-challenge perspective, do you normally start by figuring out any way of doing it or is cost something you have in mind kind of from day one already? Because that's kind of like a critical point of like, we know we have to scale it at one point. So if the technology we're going to use already feels like, oof, this is going to be expensive. Is it a no-go from the beginning? When does cost really come into the equation from that product mindset?

Brian: Yeah, we've always got cost in the back of our mind. But during the homework phase, I'll say, I don't want any constraints on trying to solve the problem. Sometimes it will be just cost prohibitive, even to run a pilot. And we know that this will never work. But I don't want my team to feel like they can't explore a possible solution. Because maybe during the process of that exploration, we're going to figure something else out that's cheaper or less expensive. So that's what's really great about this team. And the freedom that Life Time gives the Life Time Labs team is we've got the ability to do that homework to set up those pilots and really explore, come with our findings, which will include anticipated cost to scale to 190 locations, if that's what we want to do. But upfront cost is only in the back of our mind, it's not a major factor in determining a technology solution.

Marco: That's really cool. And how big is the team today, because someone has to review all the previous projects that you have, and then the new ones and everything. How big is your team right now?

Brian: It's fluctuated over time, maybe just three to five folks. And I borrow from other teams as well. We owe it to our various dev teams to, hey, do you want a tour of duty with the Labs team just to try something different, right? Variety is the spice of life, maybe instead of focusing exclusively on our member management system, or our mobile app, we give developers the opportunity to spend one to three months working on a Labs team project. Or if we just don't have the expertise on our team, we know we need someone who's great building out like a Kafka architecture for us or ingesting telemetry in that example from our equipment vendors, we'll borrow someone for a month or two. So we try to keep the Labs team itself somewhat small, but ensure that the pilot projects that we prioritize we're able to pull in talent as needed.

Marco: So it looks like you build little squads?

Brian: Yeah, no, that's actually the way that we structure our teams. That Life Time is kind of a squad-based approach. So we'll have like a self-contained squad that contains front and back end architecture UX, there might be two or three of those on a given product. So like the mobile team, I think has maybe like five or six squads at this point, another like our member management system could have two or three. So they're very, for lack of a better term modular, it makes it easy to borrow from various teams. And then we have two-week sprints here as well. So if we need to kind of pivot, or we don't want to make too long of a commitment for an individual on a team, it's really easy to swap people in and out of projects as we need to.

Marco: And who is the lead on those squads? So it's like you have like a leader, and then the squad, it's like, I don't know, it's like the ones who are performing really well, or is everyone who is raising, you know, the hand, how do you structure everything?

Brian: Yeah, in the squad itself, we've usually got, you know, a project manager, a business analyst, and a development team, in the case of a group that we set up for a Labs pilot project, I'll typically lead it because I've got enough of the business background, the technology background. And then it's just a lot of coordination. Like we know what we want to build, we've done all the homework prior to the dev team joining when it's time to build out the pilot. So we're able to keep it down to like, you know, individual contributors, join our crew and I'll wrangle everyone to implement the pilot.

Jonas: It's awesome. Life Time just recently launched, right? A new program, actually, I don't know the exact term is innovation hub or innovation incubation hub, right? Like, is that directly tying into the Labs team?

Brian: It is. Yeah, absolutely.

Jonas: Can you share a bit more about it?

Brian: Happily. Yeah, in May or late April, we launched the innovation hub. And this was a new iteration of what the labs team had done prior to COVID. So we had a beta testing program at Life Time where members could sign up and help us test features at Life Time. So it might be something that's feature flagged in our mobile app, or we've got something that we want to test in the clubs. At the time, maybe 8,000 members had joined our beta program, and we would give them early access to features or ask them to test something in the club and survey them for feedback, learn, and iterate. COVID, like a lot of things, made that disappear. And then late last year, we were looking around and starting to get the feeling that maybe Life Time wasn't perceived as being as innovative as we know that we are.

Brian: We looked at collaborations between OpenAI Health and I think it was like Weight Watchers and Peloton, right? Or Function Health and Equinox. And we know that we have the opportunity to play in that same space. So we rehydrated our beta testing program. Now we have close to 20,000 members who have opted in for our beta program. And then we opened it up to startups, early stage companies that know they have a product, but they haven't yet had a chance to test it in a structured environment with actual users. And this could be an app, this could be a physical product, it could be something that helps enhance our facility operations. So we put out the call on LinkedIn to apply. We had around 190 companies apply at various levels of maturity.

Brian: In some cases, it was like an established wearables manufacturer that I think was probably looking to get their wearables in our store, all the way through like high school and college students that had a hobby project that they wanted to show off. I took every one of those calls. I love that. I love the high school kids—they're enthusiastic, they build something, want to show it off. I will always take that call. But as we go through these companies that applied, we look for those that have a good fit with our member base. And that we could visualize—we can envision rolling out in our clubs, maybe as a small or even as a broader like, hey, this is something that's part of the Life Time ecosystem now. It's early, but we've got a few pilots that we've started around nutrition tracking, and then that digital twin that I mentioned previously, and some other things in computer vision.

Brian: And then at the end of the day, if there's an opportunity to draft a white paper and have some press around it, great. But Life Time benefits from this greatly by getting some great insight on what the cutting-edge technology is in the space, where the market is moving, what our members really want. And then I think in the case of the startups, they're benefiting from testing their products against a very opinionated member base for that feedback and are able to find product-market fit.

Jonas: Obviously, it's a huge opportunity for you to find new opportunities, new things you can tap in, position yourselves as even more innovative. But obviously also for the incoming companies, it's a massive pool of users and locations they can obviously potentially expand to test.

Brian: That's right.

Marco: Brian, I want to go a little bit more deep on that one, because when you have all these 190 companies or people who want to join this lab and build features and build different types of things, how do you select which ones could be a very good fit for Life Time Fitness? Because at the end of the day, also, it's like you have so many things. You have your own roadmap, you have people who are looking for specific things, you have end-user feedback, you have too many things at the same time. How do you handle everything?

Brian: We can't impact the technology roadmap. We cannot impact our broader strategic roadmap. So we look to put a lot of the burden on the startup to help us implement and roll out the testing. So in the case of a physical thing in the club, they'll come on-site and install. It could be sensors, it could be some sort of a product in the club. And then from my perspective, it's just a lot of coordination. I've got the pool of beta testers. All I need to do is communicate with them, have them opt into this particular beta test, follow up with survey data. It's just a lot of research and coordination. And that keeps the burden on our technology team especially low. If there's something that's very, I guess, more complicated, requires more integration, we'll pull in folks, like I mentioned before, with those squads.

Brian: But the idea is to keep the level of effort as low as we can to still get a useful result out of that pilot.

Jonas: I want to hone in there a little bit, especially right now, we talked about it in the beginning, like Claude Code, Cursor, you can build product even faster right now. The engineering output can be increased quite a lot. But is it now even more important to actually do that deep research? And maybe even you mentioned probably only 30% of the projects actually make it to production. Maybe that percentage in the future should even be smaller because you can build even more products even faster. What's your take on now the importance of research? Is it becoming even more important? New bottlenecks, which previously were maybe engineering power, is that now becoming like a product innovation definition labs type of work where we see new bottlenecks coming up to define the next products? What's your take on this?

Brian: I think that at this point, using these agentic coding tools, and then I guess trying to infuse AI into your product, I'll focus on the first one. It is a multiplier. We're seeing it now where our developers are almost starting to morph here into more coordinators amongst various agents to build a product, and then getting a boost. Life Time isn't... I mean, our desire to build things will always be far more things we want to do than we'll ever have capacity, even if we 2x, 5x the velocity of our dev teams. But on the flip side, for the startups that are hitting us up for the innovation hub, we're seeing a lot of like one- or two-person teams, right? Or very small teams where before it would be maybe 10 or 12 people.

Brian: Because they're able to complement their dev team, their skills with Claude Code, for example, that also leads to just, in some cases, like people who don't have any technical background that are building things without truly understanding how they work. And it's never going to be in a position where it can be deployed to production. We've seen some of those, you know, so far we're slapping a fitness layer on top of someone else's LLM, for example. So it does put more of a burden on the vetting process to understand what these companies really do. And we've seen a few that, yeah, there's not a real product here, and gently give that feedback. But by and large, I think it's both empowered these ambitious startups to be able to build more with a smaller team, which makes them faster and more nimble.

Brian: And then on our side, just being able to vet these startups easier because of the research capabilities that we have to understand what they're trying to build What's the science behind this in some cases? I don't have a team of researchers, or I didn't before, and now I kind of do with some of the deep research capabilities that I get through Claude Desktop, for example.

Marco: It's a really good moment. I mean, for a Life Time, it's like, again, you have the whole ecosystem. You have the clubs, you have the end users, you have a lot of startups who want to work with you. And again, for me, it's around the coordination that you mentioned before, it's quite important. So that's why to identify the correct features is going to be something really interesting. And that's where I can imagine that your brain eats all the time, right? So how do you handle it? Again, for me, I'm very curious about that. It's how do you structure yourself every single day to receive all this feedback from so many sources?

Brian: It's practicing what I preach. We have a vibe-coded platform to manage all of the companies that applied here, and we slapped an MCP on top of it. So that does help, again, as an assistant for that research, I'm able to see who applied recently, proactively do some background checks before a human reviews the product. There's always a small team that's reviewing every single applicant here. But then just being able to, like I said before, integrate with my to-do app, and, my gosh, being able to integrate with the Atlassian suite, JPD, right, to create individual cards for every pilot that we do want to chase down. So yeah, we have help. It just is not in the form of a bigger team. It's with these agentic tools that we're utilizing here at Life Time.

Jonas: Chasing the vision—too many stakeholders. I'm impressed. I'm honestly impressed because like thinking about like a three-to-five-person Labs team and then stakeholder interest from the market, from potential innovation partners, and from internal roadmap challenges—that's not an easy balance, for sure. I want to change gears a little bit and go back a bit to the challenges, the highs and lows of building product. Maybe you can share one killer feature where you felt like this was amazing, like this had real impact, where you had this in mind, executed it well, and saw the impact you expected. And then maybe also on the flip side, like what feature you felt like this is going to be the one; this is going to be great. And in the end, it was just... whatever you can share, obviously.

Brian: Yeah, let's see here. This is a little dated, but we rolled out live streaming during COVID under a very short timeline and at a pretty massive scale. And that was a huge achievement. So at the time, Life Time was faced with closing our physical locations. And we didn't have much of a mobile training platform and no live streaming at the time. So we got creative. And in about a month, we implemented live streaming from 40 Life Time locations with a goal of saying, 'Hey, we have to close our clubs', but we can still bring our members' favorite instructor to them if they're at one of those 40 clubs. But the scale—40 locations and a new live-streaming platform through our mobile app under a very quick timeline, that was a pretty great undertaking. And I'm super proud of how we were able to execute that.

Jonas: I mean, in a month, and at that scale again, like not too much margin for testing and just push, push, push, and we kind of fix in real time or like, how do you have to imagine this?

Brian: Yeah, it was the level of quality that we would accept at the beginning was probably lower than we otherwise normally would. Right. So initially, how do you scale 40 locations right away? Well, we used iPads and the front-facing camera on the iPad for our instructors. And then we had an app, I forget what it was called, that would act as the encoder and then stream to an ingest endpoint that we set up. And it worked. It wasn't great, but it worked. So definitely MVP. And then that's when rapid iteration started, we started bringing in actual physical encoders that we set up in the studio, we got much better cameras, we got better mounts for those cameras, we got better microphone systems, and then we consolidated the number of locations doing that. And then we could focus maybe on those instructors and those performers that show that they are really good at teaching a remote class.

Brian: So given the situation at the time, it was okay that it wasn't the best. But we like to say that we want to think big, start small, move fast here. And I think that the way that we rolled out live streaming is a great example of that ethos.

Jonas: Sometimes I feel like we forget to build this way, or sometimes it would be actually good to build under a lot of pressure, but positive pressure on you, right? Because you build, you launch, you get immediate feedback, you iterate, you change, you improve. Obviously at a certain scale, or if you have a certain brand behind you, you want to take care of the perception of the user. But yeah, this is great. Marco, do you want to jump in?

Marco: Yeah, really quickly. I'm very curious: what happened with that feature? Is it live? Is it dead? Is it working a lot?

Brian: So it evolved over time. So we kept, I think we went from 40 locations down to 12 for a while, and then five. But I mean, let's be honest, Life Time is the product we're best at is the physical club with all the amenities and all the classes inside, we have a free version of our mobile app. But when you become a member of Life Time, you have a goal in mind, and you're becoming a member for the physical location. So the numbers as COVID waned started to decrease, and then we had like a stable kind of a plateau of people who were maybe traveling, or they were digital-only users of Life Time. So at this point, we're scaling down, we're going to maintain live streaming.

Brian: But I think at this point, our strategy is we'll stream from one studio, one location, and then we're going to start taking our previous classes that we've streamed, maybe that week or earlier in the day and play an encore presentation of those as well, maybe automate them. So we'll keep our live streaming, you never know if there's an opportunity to use this in the future, even for like one-time events, we could certainly use it. This live-streaming platform is a great asset, it's really well architected, but it's just the situation over the last six years has evolved so much that it's just not as important as it was during COVID.

Jonas: Yeah, I can imagine. But it's also important from a company perspective to learn then, right, like, that our real sweet spot—what we're really good at—is something different, just the context and the environment back in that moment, obviously was totally different and everyone had to adapt. But like, in the end, you always have to go back to what are we really good at. And that's where you want to keep shining. On the other hand, products that didn't go so well, like, I mean, it's always the ones that work really well that we love to talk about. But like, what about any type of features or products you thought of, like, this is the one; this is great. And in the end, it turned out like, yeah, not doing really well in adoption or execution?

Brian: We have an in-club heart-rate tracking platform that we call LT Connect. So you can imagine joining a class and then your heart rate is projected up on the screen and the instructors coach to it. We've had that system since 2015. And teams that I've been responsible for have worked on that over the years. We have very high Apple Watch usage at Life Time among our members. If I look at the numbers for our beta testers, it's about 61% of those in our beta program have an Apple Watch. It's probably a little lower among our general member base, but that compares to like, I think 12 to 14% of the US population. So very high Apple Watch use.

Brian: And unlike 10 years ago, everyone, or at least among many Life Time members, they've already got a heart rate device on their wrist, and they don't want to buy a separate chest strap to use that LT Connect, that heart rate tracking system in the club. So we thought, hey, let's use Apple Watch to send that heart rate telemetry to our heart rate tracking system, and then project it up on screen. We just couldn't get it to work. Bluetooth is a little more finicky than ANT+ as far as sending data. We also encountered, over time, if you're using a kettlebell and you've got an Apple Watch and the face is up, you're going to smash that Apple Watch face. More often than you might wish. So what we found is among our members, they just don't care necessarily about projecting their heart rate up on screen; they've already got the data on their wrist.

Brian: And the importance of coaching to a shared view of everyone's heart rate has kind of diminished over the last decade. And we're rethinking that whole strategy. Now, we might reinvigorate our training amongst our coaches and trainers to emphasize heart rate training. Or maybe we'll just focus on using it in the cycle studio only. But what was interesting about that project was I was so bullish that everyone's got an Apple Watch, we have to use this, it's going to be great, but we didn't vet the technology before we dove into developing it. And we didn't expect all those problems that we had along the way. And we really worked on this for about 18 months trying to get the thing to work. And it was just not reliable enough that I would feel comfortable telling our members to use this. It was just a poor experience. And we ended up abandoning the effort.

Marco: This is so funny. You see us smiling. And it's for a reason. This is almost the origin story of ROOK. And I don't know if you knew, but previously, we had a company called ROOK Motion, which was heart rate tracking in-person studio environments or digital classes in real time. So heart rate from the arm or from the chest, and then real time projection. So similar to what you just described as a SaaS business model. And similar thoughts of like, why should someone buy another heart rate monitor if there's already an Apple Watch, a WHOOP, or a Garmin? We started integrating. It's messy to integrate with these different solutions. And it's kind of a bit of the origin story of the leap into ROOK and the aggregation of wearable data today. Obviously not in a real-time fashion in the sense of second-by-second heart rate anymore. But yeah, it was super fun because we solved that problem.

Marco: In fact, we could use the Apple Watch information in real time and create effort zones and calorie burn, because everything went directly to your phone. From the phone, we connected with the devices, the TV, and everything else. So it was in real time. It was beautiful. But then that's when we switched everything because we saw the big problem with wearables and everything. But yeah, to your point, we know the struggle over there. What's really interesting is that I think things are different now because maybe you don't need a coach. Maybe you can use AI tools so you can bring these insights or something for the end user. But I also think cycling is where everything works better, I think. But yeah.

Brian: One of the phrases that we kind of repeat to ourselves is, our members should be able to leave their phone behind. I don't like requiring the experience to work by having your phone with you. Especially when I look at a cycling class, you go into the studio and around the perimeter of the room, people are setting up their phones so they don't sweat on them. So can I build experiences where people can just leave their phone in the locker and not bring it onto the fitness floor? And that was the idea to focus so heavily on Apple Watch connecting directly to our system without the phone as a bridge. And in hindsight, maybe relying on the iPhone would have been a good architecture, but it ran counter to what we were trying to achieve as far as a member experience goes. But that's another one of those where we learned a lot. And maybe we'll revisit this in the future.

Brian: Cycling also benefits because we capture cadence and watts off the bikes in conjunction with heart rate. So it's just a lot more useful than just heart rate.

Marco: Yeah. And that's great. That's great. That's cool.

Jonas: Awesome. We're coming to a close here, Brian. We have to ask that one question. Obviously, the podcast is called This Feature Will Save Us. So what is that next killer feature you're working on? What's that next big thing? What's the next product feature that you're super excited about?

Brian: I'd say something that was announced recently actually is system-wide MCP support coming to iOS 27. Right? So Apple is opening the protocol that lets AI agents like Siri talk directly to app services without the member ever opening the app. So you could book a class at Life Time, pull your workout history, get a coaching recommendation through that conversational layer that sits above our app. But that kind of raises a question that we haven't had to answer before. Is the Life Time app the product or is it just the delivery mechanism and data that will be consumed elsewhere? Right. So I think a lot of companies that treat the app as the moat are going to feel this as a threat maybe. But companies that treat their data and service layer, you know, as the moat will see it as just another channel for distribution. I don't know how this is going to shake out, but we're going to find out.

Brian: I want to make sure that we are there when iOS 27 launches. And I can't wait to see the analytics to see, hey, what percentage of classes were booked using Siri versus our app? That could be super interesting.

Jonas: Awesome. That's awesome.

Marco: No, no, no. I just want to say that the feature looks amazing with all these AI tools and everything, everything connected between different platforms and everything. It's going to be amazing. I do believe so.

Jonas: On that note, and with that from Marco, we're going to close it out. Brian, thanks so much for joining today. It was a pleasure.

Brian: Absolutely. Thanks for having me.

Marco: Thank you so much, Brian.