← The Peel with Turner Novak
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- [00:03]
A
Alex, welcome to the show.
- [00:05]
B
Thanks, Turner. It's great to be here.
- [00:07]
A
Yeah, I'm excited. I, I talked to a bunch of people before doing this. I know you told me to talk to Jamie at Ring, I talked to Adam Bain and then the guys at Slow Will and Yanni. So I got a bunch of different perspectives on. And then I think you gave me some ideas too. So I think we have a, we have a pretty fun conversation coming up.
- [00:24]
B
I'm looking forward to it. I'm. Now you have to be nervous or intrigued as to what they said.
- [00:29]
A
I mean, honestly, it was better than I would have came up with by myself. There's a lot of interesting almost perspectives and narratives and stuff to hit on. I think probably one of the big ones is you're kind of the first or maybe the most prominent at scale to pull off this kind of venture growth buyout AI roll up strategy that maybe we'll talk about in a couple minutes. But I'm, I feel like that's probably what I'm most interested in. Just like hearing how it's all, how the sauce is made.
- [00:58]
B
I was wondering if they took credit for it.
- [01:01]
A
Oh, they did. Yeah. They're like, you know, make sure we get, we get, we're in, we're in the lead position for how much work we did here.
- [01:09]
C
But I think probably the most interesting
- [01:11]
A
thing is we were talking about, you think that something like 50 million Americans have in some way interacted with or used the Metropolis product at some point, which is kind of massive, like, that's insanely large. And I feel like a lot of people have never even heard of a company before. So what, what is Metropolis?
- [01:30]
B
Yeah, I think you're right. A lot of people haven't heard of the company. And to your, to your comment over, at this point, over 24 million Americans have signed up with the platform and probably at this point north of 50 million people have actually used our product or our services. And I think that goes to the fact of how do you think about, how do you actually describe Metropolis? And there are two really fundamental ways to think about the company. On one side, this idea of an applied AI company. We talk about ourselves as artificial intelligence for the real world, but really how do you take these services and these products that we're so used to in the palm of our hand? And how do you extend them into the real world? So what we've done is we've leveraged computer vision and artificial intelligence to create seamless experiences everywhere around you. And we started with parking this idea that you could just drive into any Metropolis enabled facility anywhere in the United States, get a text message when you arrive and seamlessly charged when you leave. That's one side of our business. The other side of our business is we've rolled up these legacy businesses to accelerate our go to market. And as a result of that, our services that you know, consist of businesses that have been around for almost 100 years at this point. Those businesses in just the last few years have touched the lives of north of 50 million Americans.
- [02:53]
A
That's insane. So when I'm thinking about, I'm interacting with a Metropolis product for the first time, I drive my car into a lot like what happens to make the product kind of work.
- [03:07]
B
Yeah. So our goal is to drive what we'd qualify as a magical experience. So you scan a QR code, you enter your credit card, your license plate and your phone number, and from that moment on you're a member on the Metropolis platform. Which means you have access to the entire Metropolis network. And you pull into any Metropolis enabled facility anywhere in the United States, you drive up, the gate automatically vends, you get a text message welcoming you back. And when you leave, you get a text message with your charges. You never have to fumble with tickets, none of the traditional pain points associated with parking.
- [03:41]
A
And so you do have to sign up the very first time.
- [03:44]
B
You do have to sign up for the first time. And that's where we've crossed the Rubicon of 24 million Americans that have signed up on the platform to create those seamless experiences. And we started in parking and now we're scaling past parking into both mobility and non mobility based experiences.
- [04:01]
A
So what are those for example? I think I saw some things on the website like restaurants, hospitals, like are these all parking or is it like placing an order? You walk into Wendy's and you get a, you get a burger that just shows up at the counter in due time.
- [04:15]
B
More on that in the future. But what you'll see right now Turner, is we're extending very deeply into the mobility landscape. So first and foremost we're going deep. And that depth manifests itself in gas stations, car wash, quick serve retail. This idea that you can just go to a drive through and you're welcomed back that your order history is on file. So you can say, you know, do you want your same big Mac or your quarter pounder or your double, double, whatever it may be. So preference, this sense of belonging, everywhere you go, where you're recognized, your order history is on file and you can seamlessly pay at the same time, we're extending past the mobility landscape, past the gas station, the car wash, the parking lot, past tolling and moving into the real world, further into experiences in your day to day life. And how can we leverage what we qualify as the recognition economy? How can we leverage biometrics that you'd see with Clear or with other organizations to create seamless experiences everywhere you go, whether that's an office building, no longer having to check in, whether it's a doctor's office, never having to fill out the same monotonous forms over and over again. How do you facilitate those same type of seamless experiences? So there's a sense of belonging, a sense of personalization everywhere you go.
- [05:32]
A
So it's almost like in a sense, Stripe for the real world or like TOAST for the physical world? Like some kind of automated frictionless checkout experience for things that don't have a point of sale system or like a Buy now button on the Internet?
- [05:49]
B
Yeah, it's the Buy now in the real world. You're right. I mean, you could think about as the context of Stripe, you think about it in the context of toast. But we're so used to these online experiences where we can just click where it's seamless. But then we enter the real world. We go into a restaurant, we go into a doctor's office, we go into a class A office building, we try to check out at a grocery store. And we have to represent our identification. We have to give our credit card over to a perfect stranger. Think about how these technologies have evolved over time. It's like really interesting. I like thinking about the credit card. Right. You know, Turner, when we were growing up, most people paid with cash. Then you'd slide a credit card to one of those credit card readers, then you'd swipe a credit card, and now we tap a credit card and then just recently, we tap a cell phone. It's this kind of a linear expansion of technology. It's not exponential and it's not disruptive. But why do you need a credit card? Why do you need identity everywhere you go? Why can't you just belong? So how do we leverage your identity? How do we leverage recognition? How do we leverage the technology that already exists to create these seamless experiences? First starting with the car and then extending past the car and moving with you everywhere you go?
- [07:02]
C
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- [08:12]
A
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- [09:00]
A
And now let's jump in. So then how does the actual technology kind of work? Because there's I think there. I almost get two opinions of this where when I think about the parking experience, it's just computer vision. There's the numbers on the license plate. I'm assuming that's how it gets categorized in a database. It seems super simple. Anyone could do that with technology from a decade ago or even more than that. And then the other end, I also think of you're talking about biometrics and how do you even get an eye scan or fingerprint or whatever. I feel like there's almost two ends. This sounds both really easy and really hard at the same time, like, what are you actually doing or what? What actually happens kind of on the back end with the product.
- [09:41]
B
Yeah. So let's start first, Turner, with the car. I think you're absolutely right. I would actually say that technology that you're describing has been around since the 70s. Think about it as like optical character recognition, right? It's like you identify a license plate and you charge a person, right? Relatively easy. You know, you look up a file in a table somewhere, you match that with some profile and you charge them. Fortunately or unfortunately, that's not what we do. And the reason is because, one, it's not very accurate. So those traditional models get to about 70% accuracy. And two, what happens if you don't see a license plate? What happens if I need absolute accuracy? What happens if, Turner, I'm granting you access to a secured government building or a residential building with limited access, you need near perfect information, and it needs to facilitate that actionability in real time. So I need to recognize you, I need to match you with that account. I need to know you're authorized to pull into that facility, and I need to do all of that in fractions of a second. And not only that, I have to create a level of accuracy, even if your license plate is obstructed. So the way you think about biometrics, the way you think about that type of robust technology, you also think about that in the context of a vehicle. How do we create a fingerprint of your vehicle? How do we actually capture your vehicle independent of whether or not your license plate is covered in mud or snow, or you're traveling with your family and you put bike rack on the back of your car. So we can identify your vehicle independent of the license plate based on the heuristics and the machine learning that we've created surrounding the vehicle we've captured over. I think at this point, I don't want to misquote the figure, but I think it's over 250 million images. So how do we think about leveraging those images to train our data set to identify a vehicle independent of the license plate? Where the license plate just becomes one variable, not the most important singular variable.
- [11:42]
A
So would there be, like, let's say one of my cars, we have like a shitty minivan that's like a dent in a scrape on the side. Would that be in the database? So you could check.
- [11:52]
B
Yeah, just search shitty minivan dent inside. No, but that's a perfect example, right? It could be dents, it could be scratches, it could be A bumper sticker. It could be colors. All of these characteristics make up a profile, make up a fingerprint of your minivan that identifies your vehicle as juxtaposed to a vehicle that's the same make, model and color that pulls in right after you.
- [12:19]
A
I feel like some people listening to this are like, oh, my God, this sounds like a privacy nightmare or something. Like, there's tons of potential things that can happen from this. So how do you guys think about just making sure all this stuff is, like, safe and secure?
- [12:34]
B
So I think one privacy becomes at the forefront of Metropolis. It's something we talk about at the executive level, at the leadership level, at the board level, we talk about privacy consistently. I think what you're alluding to is multifold. Determine on one side, you're talking about how we secure the data. So we use best practices. And we also don't license that data to any third parties. So that data is retained by Metropolis and the member itself. So you have your data, and we have a license to your data. On the other side of it, and I think you're alluding to this. You really start thinking about what I would qualify as the fair exchange of value. Why is someone willing to give your information. Why is someone willing to give Metropolis their information? Well, you can think about it like an online checkout. Well, we're willing to give someone our address and our credit card. And the reason we're willing to do that is there's a fair exchange of value. We carry around these little devices all the time. Why are we willing to carry around these little spy devices all the time? Well, we see a fair exchange of value. You can think about two concentric circles. On one concentric circle, you have convenience. On the other concentric circle, you have privacy. They don't really overlap. And where a consumer gets involved is where they think about where they are comfortable giving up their privacy in exchange for something else. While you and I are very comfortable giving up that privacy in the context of security use case, in the context of going to an airport. You and I are very comfortable giving up our privacy in lieu or in case. In the case of safety. When we go to an airport, when we engage in biometrics or a security protocol at the airport, we're very comfortable in that fair exchange of value. Same thing presents itself with Metropolis. If you can't present a fair exchange of value. Or someone is giving you their license plate, their credit card, but then you're giving them back time. You're giving them back what most matters most in Their lives. Not waiting in line to get out of a parking garage, getting to the event that they want to be in, getting to the meeting that they want to be at, getting back to their family, sitting down over a dinner. No one wants to be waiting in line to get out of a parking facility. No one wants to be waiting in line at a grocery store or to get into a stadium. They want to be in the stadium, eating a Dodger dog with their family
- [14:57]
A
waiting in line in a stadium. That is the worst, right? Like, you get up in between. You, like time in between periods, go to the bathroom, you're waiting in line for a hot dog for 30 minutes. And those, like, slow concession lines at the stadium, those are the worst.
- [15:10]
B
You want to be there. You want to be there sitting in your seats with your kids, having a wonderful experience. You don't want to be waiting to get into a bathroom, waiting to get into and buy a Dodger dog. You want to be waiting to get into the stadium. You don't want to be waiting to pay for parking at the stadium. All of these little experiences, these little pain points erode our most precious asset, which is time. So you have to give people back something. You have to give someone something where it is, in fact, a fair exchange of value.
- [15:41]
A
It reminds me a lot of those Amazon Go stores where you can just. And I've used them at stadiums. Like, they have these little, like, setups where, like, you walk up, grab your water, like, your hummus, fruit, whatever they sell in those things, and you walk out and then they're pretty quick. They're nice to have in stadiums.
- [15:57]
B
Yeah, Amazon called that just walk out technology.
- [16:01]
A
You're almost like, just drive up, just drive up. Technology.
- [16:06]
B
Exactly.
- [16:07]
A
And so what was kind of the pitch when you come to a parking lot operator to kind of do this, like, initially. I know, well, maybe talk a little bit about early days, like today, but, like, what is kind of the pitch? Like, if I've got this, like, parking asset and I maybe just. I feel like parking is notorious for being like, no technology changes for a century. And it just. It works and they make money. What's kind of like the pitch to someone to say, no, you should, like, use this technology and it'll do X to your business?
- [16:37]
B
Yeah, I think you're right on. You know, the industry as a whole hasn't really evolved to about 100 years. So if you think about, you know, traditional parking, it was a covered land play. It was a guy with a wad of cash or a box that you put you know, cash into.
- [16:52]
A
There's maybe a sign, right? Like $50, like Super bowl parking or whatever.
- [16:57]
B
Yeah, it's so old world, it's actually shocking. I mean it's almost, it's really interesting to think about. You know, parking represents 15% of the surface areas of our cities. Yet there it's. Yet it's almost not an institutional asset class, right? We talk about class A office, we talk about multifamily, we talk about single family. When do we talk about parking?
- [17:24]
A
Because you would think to your point, you know, it's super. I mean, the cash flow is pretty sticky, I would assume. Like it's low maintenance, low capex. Like it's like a lot with a gate and you got like a dude that doesn't have a college degree that just sits there and like, you know, if I'm looking at this lot, I'm like, oh, let's develop it into like a 50 story complex and make a ton more money on this piece of land that we own. In theory, like that's how someone might think about, like, why has it not really institutionalized?
- [17:53]
B
You know, I think there are a few reasons, but I know this sounds remarkably simplistic, but it's also really unsexy, right? Think about on one side you're like, oh, what did I do? Well, I created the biggest class A building in New York City. I created the number one residential tower in New York City. It's like, nah, I buy parking lots. It's like, it's dirty, it's, it's gritty, it's like a piece of pavement, you know, so there's weird smells and weird associations. People are afraid of parking lots, parking garages, you know, so it's this kind of last bastion of non institutionalized real estate in the United States. And to your question, Turner, when we started, and still today, what we found is we could create technology that facilitated a better mousetrap. And it did that a few different ways. One, it created this amenitized experience, a truly differentiated experience for the consumer. This idea of just driving in and driving out. Two, it reduced the cost to operate these facilities. And, and three, we actually caught and captured significantly more revenue. The net result of that is that we actually increased the value of the underlying dirt. So while at first it was kind of this battle and this kind of complicated sales cycle, what we've actually found is the product unto itself sells itself. And it sells itself. Because that differentiated experience for consumers and that differentiated value that we drive to the real estate owner, actually increasing the value of their underlying dirt, which is their primary objective.
- [19:32]
A
And how does that happen? Like, are you able to better optimize, like, use of space, Charge better prices, like surge pricing? Do they lose less money because there's
- [19:42]
C
like less fraud or something?
- [19:43]
A
Or maybe it's all those things, you know, it's.
- [19:46]
B
I mean, look, it's all those things. And I'm happy to go into great detail, but like, just think about what you're juxtaposing. You're talking about a company that's invested hundreds of millions in building this type of technology versus the dude with the wad of cash. And there's just a balance, there's just a difference. And it goes to our capitalization, it goes to that, our core, that our base. We founded this company as a technology company. We founded this organization bringing together a group of technologists to think about how we could build a solution from the ground up. Not how we could look at a parking operator, not as a history of parking operators. We started looking at parking as the first vertical where we could deploy this robust applied artificial intelligence to create these seamless experiences, but also create such a profoundly differentiated mousetrap for real estate owners. So yeah, you're absolutely right. We reduce fraud, we capture more revenue, More people actually go to our locations because we're starting to see more and more signal of this because they know that it's a metropolis location as compared to a competitor.
- [20:57]
A
So if there's like two parking lots, one on each side of the street, and you know that one you just drive in and one you have to like stop and like get your car and like get a ticket, you'll always choose to turn into the metropolis because you just know you can just drive in.
- [21:10]
B
That's the goal. That's 100% the goal.
- [21:13]
C
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A
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A
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C
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- [21:50]
A
All you have to do is ask, where is this kind of going? Because we talked about, you know, it hasn't changed much in A hundred years. There's like a dude with a lot of cash, whatever, maybe he's got a chair, maybe there's like a little booth, there's a gate, right? Like I feel like we've got gates over the past couple decades. There's like a little bit of tech. Where does this kind of go? Because when I think about like self driving cars, I'm like, do they even need to park? Like, does parking go away? Do you even need parking lots? Because the cars will just be self driving, et cetera. It could either be terrible or really good for you, I guess, depending on what you say next. But I'm curious, like, where is this all going?
- [22:26]
B
You know, it's interesting. Look, I think there's a few ways that I'll respond to that. Turner on one side, look, we have 23,000 employees. We have a lot of people in those booths, in those parking lots. And those individuals, those teammates, those metropolites are driving remarkable value today. At the same time we see those experiences evolving where that human capital, those employees, those team members can drive even more value. Think about our valets, think about shuttle drivers. But I'll also tell you that while Metropolis is the 800 pound gorilla in US parking, we represent 6% of the market. We're nothing, we're tiny. So the question is, how quickly can we get that 6 to 12 to 24? And that's about scaling. That's continuing to prove out this value proposition to real estate owners and that's continuing to scale into new verticals. There's nothing more powerful than a real estate owner that realizes they can pay for parking with the same application, pay for their fast food with the same technology, the same recognition, artificial intelligence, and then at the same time get into the same office building leveraging that exact same technology. So as we expand into new verticals, that becomes self reinforcing in the context of autonomous vehicles. It's a great question. So one, I am for someone who people often draw this distinction that if you're an advocate of parking, you're probably a real advocate of car culture and you're probably antagonistic towards autonomous vehicles. So let me just dissuade you of that assumption right away. Like I'm hugely bullish on artificial intelligence and the application of artificial intelligence in vehicles and how we can bring AVs to the forefront of our day to day lives. So I'm an early adopter, I'm a huge proponent. I, you know, I have an 8 year old daughter. I still am a advocate and proponent that she'll never have her driver's license. And I hope for that day, I mean, you know, look there, you know, I think it's right around 50,000Americans lose their lives every year as a result of automobile accidents. I want to take that number to zero. Right? You want to reduce the percentile of fatalities as a result of the deployment of autonomous vehicles. So I'm very bullish about the application of technology and how it's advancing. What I'll tell you is there's always the temporal questions, right? I think that you will talk to some people and they will tell you the technology will never get you there, will never get there. We will never have level five autonomy. I think it's bullshit. I think we're going to be there and I think we're going to be there sooner than people think. What I'll also tell you is it's not going to be tomorrow. And it's not going to be tomorrow for a number of reasons. One, we all have our personal vehicles and personal vehicles at this point in the United States have kind of a life expectancy of north of 11 years, right? That's the useful life. So if you buy a car today, you're probably going to have that vehicle for 11 years. You're probably not going to switch over to an autonomous vehicle. Now, may you supplement your personal travel with an autonomous vehicle? Absolutely. So the question becomes temple now. Why is Metropolis so bullish? I would say the Metropolis is so exciting because we're the only player in the market that at scale can convert parking into mobility hubs. Where do all these vehicles need to go to be clean, serviced, charged, deployed data offload? All fundamental services necessary to facilitate the future of autonomy. Without those services, we don't have autonomy. We don't have level 5 AVs. What you're not going to see is this kind of dystopian future where cars are just circling the block, endlessly waiting for their next ride. That's never going to happen. It's kind of this pundit speaking point. That's not a thing. Cars are going to need to go somewhere. They're going to go somewhere to be stored. They're going to go somewhere to be deployed. Cleaned. Service data offload. We have 4,600 locations across the United States that we were that were traditionally archaic overall infrastructure that's now connected. So the question is, how can you bridge next generation autonomous vehicles? Next generation mobility? Whether that's an av, whether that's a drone, whether that's a robot with old world infrastructure and we're that API layer and it's that kind of, I would say, pragmatism that puts us at the forefront of autonomy and really allows us to leverage our ecosystem, our platform, our footprint, to bring autonomous vehicles to reality at a much faster pace.
- [27:18]
A
So I guess if I was like hyper dissecting the Metropolis kind of like business model and the opportunity making it almost like as simplified but also like as sexy as possible, it would almost be like you've got this profitable, cash flowing, parking, self checkout, real world business that also is sort of the autonomous robotics hub of cities in the future or something like that. Is this a fair way to describe it?
- [27:48]
B
Yeah, look, I think that we have significant depth in our business and then we have breadth. And I think you're right. On one side we have this recognition platform and on the other side what we do is we have verticals and one vertical is mobility and then the other is verticals are outside of mobility. Actually. How does this technology travel with you everywhere you go? And you're absolutely right, as we think about depth, we think about this convergence from personal car ownership to fleet ownership to individual AV ownership and how those kind of modalities coalesce into the future of mobility. And I think that Metropolis is perfectly positioned to take parking and convert it into this mobility offering, this mobility hub offering. And I think you're absolutely right. We have that depth which provides that defensibility. And then to your point, we did something that most companies, I would say almost no companies in the applied AI or AI space have this defensible service layer, this traditional business layer. It's almost as if, almost as if we planned it, this idea that you can blend next generation artificial intelligence with traditional managed services.
- [29:05]
A
So was it all planned? Like, to what extent was all this like planned? Because, I mean, I think it might, it might be interesting to talk about this is your second parking company. Like you actually had another parking company even before this. So maybe that might be an interesting thing to get into. Is like, like how, how did that initially start? Because I think you had gone to film school, you are working at MTV or something, and then you're all of a sudden it's like parking, you know, business magnet, I guess or something. Like you're just like, so, so how, how did this all kind of start and, and evolve over time?
- [29:39]
B
I was very excited to go into a career film. You know, it's interesting. Starting startups and, and creating film or television is actually very similar in the sense that you're taking something from abstraction and you're bringing it for fruition, right? You're taking an idea on paper and you're building it. The difference with film and television is it's normally a year and then you're done and you start a new one. With technology, with startups, you know, you build for a decade and you continue to build. You know, we set out the ambition when we founded this company that this would be our last company. Four co founders, last company. And not that we were going to generate generational wealth. That of course was an objective, but that wasn't the core when I say this, our last company. We built a culture. We would build a company that would stand the test of time and we would all want to remain at that business. And that was an objective early on.
- [30:28]
A
Well, so the MTV thing, what did you produce? I think you were there for like a year or two. Was there like a certain show or concept that you worked on while you were there?
- [30:36]
B
I was a contract producer and we were producing international segments for international mtv, like red carpet segments, behind the scenes segments. I was excited. I loved it. Listen, I loved producing, I loved producing shorts. I was really excited for that career. Maybe one day I'll get back there.
- [30:55]
A
So then how do you start a parking company?
- [30:59]
B
It was happenstance. We actually started what I'd qualify as a Daiya company. We were, myself and my co founder at the time were late for a movie. We couldn't find parking and we couldn't believe it, right? We couldn't believe that there's this real world friction. And we realized that we could build a reservation platform, build a data platform that allowed and told people where parking was available in real time, both on and off the street, all of the world. We pooled our bar mitzvah money, we raised some family and friends money. I think we raised about $150,000 and we just flushed it down the toilet.
- [31:43]
A
Oh no.
- [31:44]
B
I mean we had no idea what we were doing. We were non technical, we had no reasons to, you know, no basis, no business. Starting a startup. And then we started to get traction. We did it again, we raised a little more money, pulled a little more capital together and we started to get traction. We started to get licensing deals. We where these large scale automotive companies as well as large scale, if you remember these like dashboard navigation systems would want to actually license our data. So we started licensing data to most large navigation companies globally from Waze to Google, to these dashboard systems like TomTom and Tele Atlas and then most largest automotive companies from Ford to Porsche to Everyone in between.
- [32:33]
A
So I could click a button and say like, you know, show me the closest open parking spots or something like that.
- [32:40]
B
You get into your minivan today and you go into your navigation system and let's just say you navigate to downtown, you will see all these little blue P's pop up on the map. Most likely that data is still coming from the company I founded and sold.
- [32:58]
A
Fascinating. Okay, and this shows up on like Google Maps, Apple Maps or it shows up in a different product.
- [33:03]
B
Exactly. So if you go into Google Maps right now and you look about all those little parking P's that'll come up where parking is located all over the world. That comes from a company that I sold to a Microsoft spin out called Inrixed.
- [33:17]
C
Interesting.
- [33:17]
A
And then at this point like did they keep this data cleaned, updated, et cetera, and just kind of sell it to Google? Sell it to any of these like map providers?
- [33:26]
B
Yeah, that business is still up and running and thriving and a division of a larger company. Yeah, there are, it's wild to think, Turner, there are executives that I hired that are still with that business, you know, almost, almost 20 years later. Wow.
- [33:46]
A
And I know you had a pretty big culture of doing, of pranking and pulling pranks on, on people internally. What's, what's the story with that?
- [33:54]
B
You know, it's interesting how like pulling pranks on people fades as you get older. You know, my, my co founder at the time when we founded this company called Park Me, you know. Yeah, we'd pull a lot of pranks on one another. It was like it was just a culture of, you know, keeping, keeping the, you know, as you know, Turner, these, these startups are so stressful. Right. You have the highest highs and the lowest lows in, in the context of a singular day. And I think we wanted to, or we strove for a way, strived for a way to keep our day to day lives a little more humor filled. So we definitely had a culture of pulling pranks to one another. Normally me pulling pranks on my co founder Sam, I think that I pull a prank on him like a pretty robust prank every birthday. And like I'll give you an example. We, we had these glass offices, right. It's like door and glass panel. And in one year we all went home around kind of 8 o' clock and everyone with their respective ways, my co founder went home, I went home. And then five of us, probably four engineers and myself teamed up. We went to Home Depot and we bought drywall and molding and we drywalled over the door and over the window. So when he came in, when he came in in the morning, there was just no office.
- [35:22]
A
There's just a wall.
- [35:23]
B
Neuro Linguistic Pro, like your programming, like you actually just, he was just confused and it was so well done that he couldn't tell, you know, where his office was. And they eventually kind of Kool aid manned through the wall.
- [35:37]
A
Oh really? It actually smash it?
- [35:39]
B
Yeah. There's no other way to get into his office.
- [35:43]
A
Are you guys still pulling a lot of pranks at Metropolis today? Similar scale, Bigger scale, smaller scale?
- [35:50]
B
No, I don't think we pull pranks as much. I would say we all still, at least at the ELT level, troll each other a lot. You know, it's more like via Slack.
- [36:03]
A
Oh yeah, fair. Much more tame.
- [36:06]
B
You know, I asked my, one of my co founders for a deliverable on an ELT Slack channel yesterday and you know, he responded by saying it's in that little box under your screen. You know, it's just like we all, I think we just, we push each other and we, you know, use humor to bring levity.
- [36:26]
A
Yeah. And so you mentioned you sold ParkMe to kind of this Microsoft spinoff that's still around. And you, I think I remember you were like ready to not actually keep doing parking. Like you were going to do something, I don't know, completely different. I'm not sure what it was, but I think you had a conversation where you're like doubling down on parking again. I'm going to start another parking company. Like how did that go?
- [36:49]
B
You know, there's twofold, two kind of components. Turn to that, that story. When we founded Metropolis, we were really not looking at parking. We were really looking at this intersection of artificial intelligence, computer vision and autonomous vehicles. And we were thinking about the future. And what we settled on was could we build what we now call a recognition platform? Could we create seamless experiences? And we were focused. We were thinking about, as you alluded to Amazon's technology, like just walk out. We were thinking we could start grocery stores. We could think we could leverage these kind of secular trends or this evolving landscape of artificial intelligence to create these Simbus experiences. And then we quickly started narrowing down on mobility. That mobility should be our first instance, our first use case. And we spent a lot of time thinking about car washes initially. And we spent a lot of time really thinking about tolling as well. And we ended up settling on parking because it's everywhere, because I had some experience. And we realized that if we could tackle parkin we could build this flywheel to your point earlier, where it could affect tens of millions of people's lives on a daily basis. And that was really where we settled as the first vertical, with the real intention to use that as a jumping off point to be and build this platform to the point of exactly where we are today, where we could use it as a jumping off point to scale into so many other verticals, where we had these license plates, where we had these members on platform, and then we could expose that same member value to so many additional verticals both in and outside of the vehicle. But you know, the other side of the narrative is when we did settle on Parker, I was still pushing back. I had kind of had enough. Right. And I sat down with a friend of mine who has since passed the former sea of Mattel, and I told him that I had no interest in going after the parking vertical, this new company. And he basically called me an idiot and really talked about how I had built this kind of idiosyncratic knowledge set, that I knew something so much about kind of this old world industry, such a defensible, unique data set, and that I should exploit it, that I should go after it, that I should take advantage of it, that I could do something truly kind of remarkable in the space. So that's why we've kind of settled on parking as our first vertical. And it still is the most important vertical for Metropolis. But what you will see, Turner, over the next five years is you will see parking becoming a minority of our total platform.
- [39:34]
A
Yeah. Because it's, it kind of follows that of just, you know, what do you have a competitive advantage in? Like, do that. Like what are you really good at? Just lean into that. Because starting this company is hard enough in itself. Like if you have an advantage, take that advantage.
- [39:49]
B
I completely agree. And that was, listen, Brian gave me great advice and that was exactly that. Which is just take advantage of the knowledge of the history, the background there.
- [40:01]
A
And I think all great startups, if you go back to Silicon Valley lore of Google, Apple, et cetera, they all started in a garage. I think you guys also started in a garage, is that right?
- [40:11]
B
We did. We started in a garage in Santa Monica. Yeah, Four of us, garage whiteboards. We have some early pictures of, you know, post ops on the wall. Both of my startups are starting in a garage. Yeah, it's a great place for collaboration. Right. It's easy, it's central. And I don't know, I think there's something. A garage unto itself is inhospitable but it's also homey. Right. You can make it your own. And yeah, both companies started in startups, started in garages. That one with one co founder and this company with three other co founders.
- [40:53]
A
And so you mentioned. So you have this advantage in parking. I'm assuming you hit the ground running. Everything was working well. Customer signing up left and right. You know, company grew super fast. Is that, is it. Did that happen or is that not the case?
- [41:05]
B
Yeah, I was just, you know, it's all. It's kind of like a fairy tale. Right. We wrote it down and it just played out day by day, exactly as you planned. No.
- [41:15]
A
So, so what happened? You get in the garage, like you're like, all right, did you.
- [41:19]
B
So you.
- [41:19]
A
So you had this realization. I was like, all right, we have this idea for this recognition product, the recognition economy. And you had this fight in like internally slash in your head of like parking. Yes or no? You decided to do parking. What did you do next? Did you go out and try to convince some people to start working with you? Like get some customers signed up?
- [41:40]
B
Yeah, you know, we ended up raising a two tranche seed round. We raised seven and a half million dollars as our first seed tranche, which for me compared to my first seed round, which was $350,000 in my previous company, felt like an exorbitant amount of money. Now feel small today. We ended up raising about 20 million in our initial two tranches. Overseed round, raised initial capital and started to build a team, started to hire technologists, hire engineers, started to build out our AI platform. And this was end of 2017, beginning of 2018. And started to build the technology team, started to build the technology stack and started to test technology. We started to put cameras on the side of the road and actually start seeing if we could capture vehicles. And then we started getting our first location and we started with our first location which is actually called M1, which Metropolis One, which was our first location in, in Venice. And then, you know, eight years later we're, you know, just under 4,600 locations. But yeah, it was definitely nonlinear. You know, we scaled to, and I'm guessing Turner, this is where you're getting to, but we scaled about 50 locations in Southern California. And we quickly realized that real estate is just as old world as parking. You know, people that go into real estate like picks and they like shovels that cash flow, they like low risk value propositions.
- [43:16]
A
Yeah, they want to go and like touch the building and like feel the brick and like know pick up the dirt and like feel it in their fingers. Yeah.
- [43:23]
B
And they don't like to take risk. Right. So they don't want to adopt new services, new technologies, new, you know. And I'll tell you, no one in real estate wants to be the first hamster on the wheel. Right? No one wants to be a first adopter. So what we found is kind of we, we hit a wall, we hit an adoption wall where you'd sit down with a class A office developer and you'd say, hey, we'd like to take the keys to your $250 million building. We'd like to be the first touch point for your visitors. And we'd like to build in parking. But then we'd like to scale past parking. And it was something along the lines of cute startup, come back in 50 years. And if you look at the legacy providers these real estate companies work with, the construction companies, the property management companies, the parking companies, many of them have been around for north of 50 years. True legacy experience. They don't want to take that risk. So what we realized is we were going to shift strategies. We were going to do something that startups, technology companies do not do. And this is what you were kind of alluding to the beginning of our conversation. We pioneered what we call a growth buyout. This idea that we could take a traditional venture backed business, a traditional technology company, a company developing artificial intelligence, and we could actually acquire an old world business. We could do something that people don't do, which is buy ebitda. And they definitely don't do it in technology. You know, EBITDA is almost a dirty word in technology. You know, you think, turn it back to that. I don't know if you were a Silicon Valley fan, but like there's that scene where he's liked, oh no, no, no, no, you need to be pre revenue, don't have revenue. I think tech investors are similar in that context. With ebitda it's like, no, no, no, no, no, no, no. Don't have ebitda, don't have profitability. But we went out and acquired ebitda. We went out and we acquired these old world staffing businesses. We bought our first parking operator. So we bought a company based in Nashville called Premier parking, probably the 10th or 11th largest parking operator in the United States. And we tested our mob. We used it to scale our technology to 400 locations overnight. So we went from this kind of mom and pop technology company to running one of the largest parking operators in the United States.
- [45:43]
A
You said you went from 50 to, I think, 400 or.
- [45:47]
B
Yeah, about 450, exactly.
- [45:49]
A
And so that was basically, they were based in Nashville. They owned a bunch of lots kind of around Nashville or around the country.
- [45:56]
B
They managed a bunch of lots across the country.
- [45:59]
A
So what you were acquiring, you were acquiring. They had. It was almost like a staffing and property management company for parking.
- [46:06]
B
Yeah, that's exactly how you think about it.
- [46:08]
A
And then how. How did you acquire them? Because I think you mentioned earlier, you raised about 20 million bucks. I'm assuming this business probably less than $20 million. Maybe, or maybe it wasn't. But what was the process like of acquiring an existing pretty big company is about, you know, 10 times bigger than you at the time?
- [46:24]
B
Yeah, no, the company was doing around between 10 and $12 million of EBITDA. And we acquired it for, if I recall, a little north of $120 million. So we had to go and raise money. We raised money from Silver Lake and Dragonier and a lot of the usual suspects you described 01A and others, these kind of, I would say, kind of tier one Silicon Valley firms. And we did something that people don't do, which is go buy a traditional business. So we raised the capital, raised some venture debt as well. And then we went and acquired Premier. And we went from, you know, just under 200 employees to just north of 2,200 employees overnight, just around 50 locations, to just about 450 locations overnight. And we took a company that was doing, you know, a few hundred transactions a day to a few thousand transactions a day. I mean, at this point, we're probably doing. I don't know the exact number I
- [47:28]
A
saw, like, once a second.
- [47:30]
B
Well, it's actually, it's more than that. It's more than that. So we're doing almost a new member signs up for the first time every one to two seconds, 24 hours a day, seven days a week. So someone signs up for the first time, but transactions are multiple of that.
- [47:48]
A
You couldn't just say, you know, go to Google and go to Facebook and say, like, I want to spend $10 million. Just like, acquire me customers that are profitable. Like, here's all my, you know, parameters and just like, run the ads and like, make it. Just make sure I. It all goes the way I want it to. Like, you can when you're running these ads because you had to literally put up stuff around hundreds or thousands of locations. So it actually made more sense and almost like, probably sped up the implementation time to just go and acquire the existing footprint.
- [48:21]
B
The Business at the core, Turner the economics. So what happened is we had unit economic fit, we had product market fit. What we didn't have was go to market. And the go to market was flawed because, and this is, you know, something you may have touched base with on will and slow, but you just hit a wall when you talk to these traditional real estate investors, traditional real estate owners, because they wanted an institutional operator, they didn't want to take that risk. And we needed the proof points. So we used Premier to help build that base, that proof point. What we didn't know at the time is the acquisition of Premier was going to be a remarkable success. We didn't realize that we were going to take this traditional business that was doing a certain level of gross profit and we were going to 2x that gross profit relatively overnight. So we then went back to the venture capital community and we were like, hey, I think we should do that again. And they were absolutely on board, they were actually pushing for it that we should acquire more companies, that we should leverage this go to market to really accelerate this inevitability. So instead of kind of this ground war of organic sales, we could scale inorganically. So we went out and we raised $1.6 billion as our series C to go acquire the largest operator in the space, which was a company called SP plus, which was a publicly traded company that had just north of 20,000 employees, just north of 3,600 locations. And we acquired them almost two years ago.
- [49:53]
A
Now were they the biggest parking company in the US Did I see that?
- [49:59]
B
They were the biggest parking company in
- [50:00]
A
the U.S. okay, so Metropolis is now the biggest parking company in the US
- [50:05]
B
Metropolis is the largest parking company globally.
- [50:08]
A
From garage to largest in the world in a decade or less. Yeah, that's crazy.
- [50:13]
B
It's been exciting. What the team has done over a short period of time is remarkable.
- [50:19]
A
And so if I was thinking about doing this because I feel like one that's it's been pretty common in sort of like services businesses like you see people doing this with, you know, accounting firms. I feel like there's like a dozen of these kind of like AI growth, accounting roll ups or other categories. Like what do you think has to work or makes it so this type of strategy doesn't work. If I was going to try this in a different category or does it only work in parking?
- [50:47]
B
You're seeing, you know, we de novoed this strategy and you're seeing a lot of people now implement the strategy. I don't want to say copy the strategy, but realize the value in the strategy, especially through the application of AI. So you're seeing General Catalyst deploy this strategy now for hospitals, you're seeing thrive as well as others deploy the strategy in the context of accounting as you described. So you're seeing this as a, a significant component of the future of venture capital. I think that what makes this strategy successful is singular and I couldn't be more aggressive about this statement. People focus on M and A, on cost synergy. It's the traditional mantra of private equity. Lbo. Everything is about cost synergy. And cost synergy doesn't create durable growth. So any growth buyout, any application of artificial intelligence to an old world business that focuses on cost takeout, on cost synergy, on the reduction of human capital will succeed, but will not succeed in the context of a growth multiple, a technical multiple, a technology company multiple. What they'll succeed at is building private equity companies. And that's not to say private equity companies aren't interesting. They are interesting. It is a compelling industry, but it's not as compelling as technology. And in order to succeed and build a technology company, in order to have a successful growth pile, in order for companies like General Catalyst et al to succeed in these models, they need to focus on revenue synergies. They need to focus on a model that drives incrementally more revenue through the deployment of technology, not simply the elimination of cost. And what's going to happen is given the history, given the focus, given the proprietary, unique, compelling nature of private equity, everyone is going to gravitate towards cost synergy. It's easy, it's ingrained. But in order for this to be successful, in order for people to replicate the strategy that we're deploying, they have to focus on revenue synergies. They have to deploy more revenue through the deployment of technology. They have to see and yield more revenue, more gross margin, not simply the elimination of cost. In the spirit of driving ebitda, the simple test there, Turner, becomes through the deployment of technology, are you seeing more gross profit? Profit? Not simply. Are you seeing the elimination of cost and just accretive ebitda?
- [53:30]
A
Well, even cutting costs in, in your gross margin, I mean, so it's almost like you need to like generate more revenue.
- [53:35]
B
You need to generate more revenue.
- [53:38]
A
Yeah, it's almost like cost cutting using AI is like kind of like table stakes. Like if you do it like you must, like you really should be doing it, but it really only works then also if you are using it to grow the business, probably much faster than like non technology Native companies that are in your industry.
- [53:59]
B
Yeah. I mean what you're finding right now is there are partners all over the world and there are analysts all over the world sitting in rooms, sitting at board tables, sitting in investment committees with memos in front of them. They're talking about how they can buy an old world business and deploy AI. And it's the same model that they've levied for years. In this model they'll be taking technical risk which a lot of the time private equity firms don't want to take. But they'll take that technical risk because they have confidence in their underwriting. Surrender but take out of costs. It's just not that interesting. It's not interesting enough to facilitate durable growth. It's not going to be the next trillion or $100 billion company. It's going to be compelling enough for medium mid teen returns.
- [54:47]
A
So then how should I think about what is sort of like the durable revenue opportunity? Because if I'm just thinking about this, I'm just kind of like making this up. I haven't thought about this a whole lot before just saying it live right now. But like if I'm trying to like roll up accounting firms or roll up a law firm or roll up like a creative advertising agency or something like that and these like services businesses, if I'm a client or a customer, one of my customers can just say like I'm just going to go to this other firm. I guess they can't really do that with parking. Maybe it's just a lot harder or maybe it's easier, I'm not sure. Like are there certain things that need to be true on this like revenue generation opportunity in order for that to kind of play out?
- [55:31]
B
Yeah, exactly. So you're right. We have built what I would say is a truly phenomenal moat in part working. That being said, to your comment, you need to deploy technology that drive the revenue needs to be driven by the technology unto itself. So if you take your accounting analogy, you need to not just like. And it's really, it's really interesting in the context of a roll up.
- [55:57]
A
Right.
- [55:57]
B
If you think about an accounting roll up, the natural inclination is like okay, every HBS study I can take a business combining with B business and I don't need two CEOs at reduced cost. Right.
- [56:10]
A
Just cut all overhead. You just save, you know, 10% of costs. Yeah.
- [56:14]
B
Get rid of all these accountants. That's cute. It's nice, it's interesting. It's not that interesting, but it's not going to Create durable growth. It's going to create. Create what I would qualify, an uptick in ebitda, but not multiple expansion. In order to get multiple expansion, you need to increase the breadth of the product and you need to actually drive more revenue, to your point turner, from your customers. You need to create a solution that. All right, I brought these two accounting companies together. There is fundamental cost synergy, there will be cost takeout, but I'm going to invest in a technology platform that, that is going to allow me to generate more revenue from my customers. And what you have is often the inverse. You have the consultancy or the accounting firm being like, hey, listen, we've just reduced costs by 40%. And the clients are like, can you extend some of that cost saving over here? So you need to create that durable growth through revenue synergy, through driving revenue, through the relationships and the unique nature of your technology with your partners, with
- [57:30]
A
your customers maybe reminds me a little bit. Do you remember these Amazon aggregators that really popped up during like a little bit before and throughout Covid. Do you remember this kind of phenomenon? There's a lot of them. I mean, I feel like the model maybe could have worked. I think some of them might still be alive, but most of them, that was kind of the play. It was like we're cutting costs, we're aggregating all these things. You know, we are reducing over because it will acquire 50 brands that are all separate and there's only one marketing personnel instead of 50. There's only one logistics team instead of 50. And we cut the costs and like the company's worth more because we've consolidated like a, you know, a floor mat brand in the car, like a ladle for soup ladles or whatever. Like the best soup ladle on Amazon or whatever. And you just kind of rolled all these things up and it was kind of like this random collection of products that, you know, in a spreadsheet it probably looks pretty good. But then it's like to, to your point, I think what maybe could have worked in that model is what I thought the idea was was like, oh, you expand them into Shopify, like you get them into Walmart and Target. Maybe the issue is they were just like shitty products. Like it was just like a drop shipped soup label or car floor mat from Amazon. Like they don't need that in Target. So maybe that was. So it's almost like maybe it's like you need premium product to like you need to make sure you're buying like a good, a good asset and a good Product that actually enables you to, to really lean into the higher revenue generation. Even, even if there's technology or not. Just like, you know, you're buying like a top of the line, high quality, what is it like Madison Avenue type asset?
- [59:06]
B
Yeah, look, it could be luxury, it could be premium, but it needs to drive value. You know, you and I were talking about the fair exchange of value. Like the purpose of technology is to, or a technology company is to create products that generate value for your customers, for your partners. If they're not generating value. Like you're, you're really engaged in financial engineering. And a lot of these roll ups are inherently, this cost synergy is, is inherently a financial engineering technique. It's not really the idea or the component of durable growth. If you look at so many companies that perform well in public markets, like you can distill their value to durable growth. If you look at dcf, if you look at the future value of these organizations, it's all tied to how the market perceives the viability of their durable growth over the next five or ten years. And you look at companies that trade at a significant discount, the market's basically saying look, we don't think that company's really going to grow and they're not going to facilitate that durable growth. And that's why these private equity are compelling. But it's not how you build a business that stands the test of time. It's not how you build a business where founders sit around the table and say this is the last business I'm ever going to be a part of. It's not how you build a business that you say this is going to be the next trillion dollar company. It's how you build a cool little rollout and you generate a lot of wealth for yourselves or other investors. But it's not how you build a really compelling business.
- [60:33]
A
So do you think more people should be using this growth venture roll up strategy or do you think it's going to end in disaster if we have the whole industry kind of adopt it in the wrong ways?
- [60:47]
B
Look, I'm a huge advocate, a huge proponent. I think it's the future term. I think this idea of. Look, I don't want to go as far as to say the idea of future for co founders de novoing a business in a garage is dead. Because it's definitively not. And especially with the advent of AI, like do I think we'll have the first, you know, $1 billion one person company? Yeah, I do. I think that's inevitable. It's a matter of time. I don't know if it's gonna be one person, maybe it's three people, but I think it's. It's only a matter of time. But I think that there are really, really compelling solutions and products to be deployed. Leveraging a gbo and I think it's the future. I think you're going to see every major venture capital firm deploying these strategies. And I think you'll see private equity firms moving down further into a higher risk profile associated with venture capital to deploy growth balance strategies. Yeah, I think people are catching on, especially through the advent of AI. I think they're a little too narrow, they're too simplistic. They're really thinking about cost synergies, even though they have the lens or the guise of revenue synergies. And I think that's not going to be a remarkable success. I think they'll yield return. But I think that the venture capital firms and the private equity firms that can capture both cost synergy to facilitate this downside risk mitigation and also have revenue synergy will be remarkably successful. And look, I think that's what Metropolis got. Right? Right. They have this. Metropolis has this kind of idiosyncratic or asymmetric return profile. Right. You don't see. I mean, if you look at our cap table, you have this blend of traditional private equity investors, traditional credit investors, and traditional venture investors in every round. You don't see them. You don't see those players playing together in one company. And that's because we have all the downside risk mitigation of a traditional private equity play and all the upside potential of a traditional venture capital play. And it's that kind of idiosyncratic bell curve, if you will, that allows us to attract kind of unique capital where we can work with players like Eldridge and we can also work with players like bdt, msd. We can work with players like Dragonier and Silver Lake, but we can also work with players like Temasek and Vista. You don't see those names on the same cap table. And that's because of this idiosyncratic return profile where we can have that downside and upside potential.
- [63:27]
A
And is that maybe where you kind of try to figure out that balance of, you know, you may have the pure private equity guy that comes in, like, show me the spreadsheet, let's delete some lines. But then also the people like, like Adam at 01 more of a technology investor like, okay, let's, let's grow the Revenue. Right. Like, does that help with sort of that balance and making sure you kind of, kind of nail, you know, triangulating those two aspects?
- [63:53]
B
Yeah, 100%. I mean, look, it's been interesting, Turner. When we found the company, I was probably disillusioned in how I thought about the capital markets. Right. I thought like an investment was an investment. Right. You know, if you can give an investor an opportunity to make money, they should seize on it. And you quickly learn that the capital markets operates in this pretty narrow box. I'm a private equity fund. I invest here. I'm a venture debt fund. I invest here. I'm a private credit fund. I invest here. I'm an infra fund. I'm a real estate fund. They all have these very narrow niches, and what we found is Metropolis didn't sit in any of them.
- [64:33]
A
That could be bad. Like, how do you raise money then?
- [64:36]
B
No, I actually think it's wild. Right. It can be very bad. And it takes brilliant investors to see vision, to move past those hurdles. And it takes really creative, smart minds to understand how they can play across that capital structure. You talk about people like Adit, Matt Bain, you talk about people like Todd Bolly and Tony Manila Eldridge. Those are players that can invest or have. Have fund structures, have capital bases that allow them to invest across the board, that allow them to invest in venture and also in private credit. So they can look at these unique businesses and they can operate outside the box. They can think creatively. But I think that that's unique. What I'll tell you, Turner, is we've had limited to no success at the VP or analyst level raising money. If I get on the phone with a VP or a principal and I pitch them, historically, almost no luck. It took a partner on IC with a significant level of investment experience to understand the vision of Metropolis, to understand where we're going. So we shifted. We stopped talking to junior team members, not because we undercut them, not because we didn't think they were smart or they were brilliant, but that they weren't going to see this and they weren't going to be able to sell their IC on the model, on the vision. Now that's changed over time. It's changed over time because we built the track record and we have, you know, a business that generates at this point, you know, over $2.1 billion of revenue. So it changes when you have that foundation, when you have the models. But yeah, it was. It was very complicated at first.
- [66:34]
A
Have you heard of this concept of being legible to capital?
- [66:37]
B
No, but tell me, I mean, it's
- [66:41]
A
basically what you just described. Like, how familiar would an IC be with this pitch, right? Like this memo shows up in the meeting. There's basically just like 10 people sitting there and it's mostly finance people that are reading all the same things, doing all the same things, all investing in the same businesses, all the same theses. Really, at the end of the day, they know what works, they know what doesn't work and how like legible is your idea. And so I mean a pretty, a pretty legible pitch right now is like, hey, we worked at OpenAI for four years. We trained the things, like we trained some of these models and we're leaving to start this new thing. And like that is just, that's the most legible pitch you could possibly have to an investment committee versus, you know, it's like kind of real estate. There's like some cameras, it's like payments in the real world, right? Like it's almost not as legible. Like if somebody's like, they have like a couple different ideas, like, what could I pitch the investment committee today as like part of my job? It's the thing that's the most legible. So they almost, even if they kind of got your idea, it's like, what can I actually get through? I see. Like they just wouldn't even pitch it. Like they just, they would, they would just do the thing that's like way easier and like way more trendy. The thing that they can talk about in a happy hour that makes them look good at those like VC catch up events or like the investor networking events. I don't know. And it's, it's kind of like I feel like it's, it's gotten worse. Just like as, as funds have gotten bigger and like capital flows have gotten more pronounced. Like another way I think about it is like you, like for a lot of investors, they think about positioning themselves at the beginning of capital flows, right? So where's capital going to flow? Is it going to start flowing towards robotics and humanoids and space? I need to deploy capital into this theme and ride the narrative of just this sector, whether or not the company actually works or makes any sense at all. It's more so about exposure to narratives almost, or exposure to a story or a theme or a sector. I don't know. I have mixed feelings about it personally. I think you kind of have to do it. But there's so much alpha, I think as an investor and just understanding a core new stream of Cash flow, really, that's opening up at the end of the day, whether it's an individual business or whatnot.
- [69:16]
B
Look, for me, if you think about human behavior, you think about game theory, you think about decision matrix. Like what I find often is people are inherently risk adverse and they're really risk adverse in the context of their careers. Right. If you think about government bureaucracy or a venture capital shop or a private equity firm, people not only kind of stay in their lane, they don't want to be creative. Creativity exposes them to risk. Career risk, personal risk. No one's going to get fired for investing in OpenAI.
- [69:52]
A
You're going to get promoted because you got allocation in this hot deal.
- [69:56]
B
Yeah, yeah, look, I think that what you find is twofold. One, people are risk adverse, so they're inherently not going to do something that's creative. And on the other side, 90 plus percent of investment is pharma. There are market forces at work and people are just investing out of fear of missing out. There's no creativity, there's no unique thought. This firm is investing, so we should invest. And people like to justify their existence and say that's not the case. They're unique, they're different. It's the same way people like to think about AI, like, I'm not going to be affected, my job's safe. You're not safe. Everyone's job is going to be affected. And most people in venture and private equity globally are lemmings. Most people at startups are lemmings. Right. Most people don't focus on creativity. They don't want to take the risk. And that's not a judgment. That's fine, that's okay. It's fine to not take that risk. It's okay to be risk adverse, but I think it's not okay to be a hypocrite. It. It's not okay not to say that. Right. It's not okay to claim that you're going to be creative, that you're going to do things that are unique or idiosyncratic and not. And I think that you have a small handful of investors and we are very lucky to have worked with a number of them. But you have a small handful of investors that are actually doing unique creative things with the deployment of capital, things that haven't been done before. And it's rare. It's rare. And it takes a level of risk and a level of creativity that most people don't want to deploy even if they are capable of it.
- [71:48]
A
Yeah, it's almost like thinking about it from my perspective as an investor. So if you're the founder, you're acting on it, you're doing it, you raise the money for me and you're like, I know I'm going to execute on this, but then I'm almost like a middleman, almost as an investor of like, I need to raise the capital and I need to give it to someone else. So it's almost riskier to take risks, if that makes sense. And so, I mean, that's the point of venture in like this asset class is you do need to take risks. So it's almost gotten too institutionalized.
- [72:22]
B
Most investors are in the business of raising capital, not deploying capital. Right. Most investors generate more return for themselves personally off their management fees than their carry. So, yeah, they're focused on fundraising constantly. And then you get the rare investor that is truly focused on doing innovative things, truly focused on building not only a unique firm, but investing in unique institutions, unique companies, or building those companies from the ground up. And there are those founders, there are those firms. You look at what Todd Bowley and Tony Manila have done at Eldridge, you look at what Robert Smith has done at Vista, you build on really interesting track records. You look at what Byron Trott has done at bdt, MSD and Michael Dell, really interesting entrepreneurs that are not just investors, they're entrepreneurs unto themselves. They're building entrepreneurial firms and they are injecting that spirit and that culture into their organizations. That's really interesting. It's really compelling, but it's rare.
- [73:30]
A
One thing you mentioned a couple minutes ago that was kind of interesting is you mentioned, like, AI is going to change a lot of skilled labor, white collar labor. It's kind of. I mean, it's really one of the first times that, you know, quote unquote, skilled labor or white collar labor is getting disrupted in terms of these different industrial or technological revolutions. How do you think someone should position for that in their career? One angle is just get really good at AI, learn it, be the AI expert at your organization. Is that the key?
- [74:08]
B
Yeah, I think there's a few fold. There's one as I think about it on the personal level. Right. Which is what should individuals do? You need to move as quickly to an evangelist as possible, otherwise the disruption to your personal career is going to be profound. I think on the other side, as we think about the macro sense, I think people are getting this wrong Turner, and I think they're not talking about it. And you mentioned kind of this idea of an industrial revolution, which I think this is at its core, but we talked about industrial revolutions historically as the repurposing or retraining of the low skilled workforce, right? We talk about this idea that you're going to take a Uber driver and with autonomy we'll retrain that. We're going to take the factory worker and we're going to retrain them in an automated factory. It's going to be an adjustment, it's going to be a upskill of that labor. I think what people are not talking about right now is what happens with the conflation of artificial intelligence and the advancements with robotics. In that context, we're affecting both sides of the bell curve. And what I think you're going to find is to your comment, we're affecting the blue collar worker and we're affecting the white collar worker. And what gets really interesting is what happens when you take a designer, a lawyer, an accountant, a doctor that is trained for 15 years and worked for 15 years and you say you're no longer needed. And at the same time you look at the plumber, you look at the janitor, you look at the chef and you say you're no longer needed. Look at the line hook the Uber driver and you say you no longer need it. And I think we really have this conflation or this combination of circumstances that we've never seen seen from an industrial revolution before affecting both sides of the. And I think it's something that we're not talking about as a society and I think we're not talking about it because it's not vogue, it's scary. And I think that people find that it could be antagonistic or promote a paradigm that just leads to fear mongering. But I think we need to embrace it, we need to understand it. And now as a society we need to address it. And we need to address it through a series of means. But I think that it's why you have people like Elon Musk talking about Universal basic income. He's not talking about this conflation or he's not talking about the compounding results of the deployment of robotics and artificial intelligence and the effect on our society. He's jumping to the conclusion, he's talking about things like ubi. I think we need to talk about both. I think we need to understand what the effect of this technology is going to be on our society. And we need to think about how we're going to support our communities, our families, our friends, those that are going to be impacted by this technology. I like to Think about Turner, this idea of Amara's Law, which is this idea that we have a natural inclination to overestimate the impact of technology in the short run and under estimate it in the long run. And I think that's exactly what we're doing with artificial intelligence, especially in the combination with robotics.
- [77:33]
A
You said, you said this is Moore's Law or what? Which law is it?
- [77:37]
B
Amara's Law. A M A R A.
- [77:41]
A
Okay, I've definitely heard that. It's like we, we overestimate what's going to happen in the next two years, and then we underestimate what's going to happen in the next 10. So it's kind of like, I don't know if you remember, like 20, 21, we were like Peak Web 3 blockchain, where it's like every single purchase is going to be like, you're going to get an NFT with your delta flight ticket. Or like each food you go to Wendy's and you get like an NFT with your meal and you're going to have this collection of NFTs and you think everything's going to be on the blockchain in a couple years. And I guess it's an extreme example because I don't know if anything will ever always be on the blockchain, but, but maybe it's just like the adapt adoption of it. And same with autonomous vehicles. Like, I think it was probably 10 years ago. People are like, oh, they're almost here. It'll be here in two years. And then we kind of forgot about it. And then now, like waymos are, they kind of work really well and they're kind of ubiquitous in some areas and most people don't talk about it.
- [78:38]
B
It's interesting, Turner. We go from. It is really interesting as a society. We also go, you know, my friend told me this, that we go from science fiction to entitlement overnight, right? It's like, you know, 10 years ago we didn't have the Internet on the plane and now, you know, if you don't have satellite Internet, you're panicked, right? You're entitled instantly. And you know, yeah, we see Waymos driving around all the time, but yeah, I think we are grossly underestimating the impact in the long run.
- [79:11]
A
And speaking about impact, one thing I wanted to ask you. So you've gone from, I mean, I think if I'm remembering all your numbers correctly, like 50 employees or a couple hundred to 2,000, like 20,000 employees. Like the scale of your business has probably been one of the largest Magnitude of changes for a CEO of a company ever. Like, how did you do that? Six successfully? Or maybe it's not successful. Maybe you're like, in the, in the process of, like, landing it. Just like, what is your day to day kind of look like is. Is the founder of a company that's kind of scaled that quickly. And how, how have you kind of digested it academically?
- [79:51]
B
It's, it's, it's compelling or it's unique to think about how the role of the CEO changes over time.
- [79:56]
A
Right.
- [79:56]
B
And it really does. It goes from, you know, heads down, working every single day, sweeping the floors, and then it ranges to doing podcasts, press interviews, and government affairs. The role shifts. What I'll tell you remains the same is you're always focused on the biggest problems facing the company at any given moment. It's really interesting to think about how what comes to the mind or to the desk of a CEO, you don't get the great news, you don't get the best news. You don't get the good news, you don't get the news you want. You get the biggest problems. You get where you can be best serving, where you can best serve the organization. And it's often because someone else can't solve the problem. You've hired, you've retained, you've empowered the best people you can, and something rises to your desk because it's a problem, it's a nightmare. It's something that can't be solved by these remarkable team members. So you're constantly battling the biggest problems facing your organization at any given moment. You're a zeitgeist. Your focus becomes the dumpster fire that's right in front of you. So what I think as a CEO, you have to do is step back. You have to remain focused. You have to understand what, what actually are the greatest imperatives, most important objectives facing the organization at a given moment, and make sure your attention is focused there, not just on the single fire that's in front of you at endgame. You need to balance those two things. And I think that maintains itself from four people in a garage to 23,000 employees across the world. And yeah, I think to your point, am I succeeding at it? Am I failing at it? I'm learning every single day. And you know, I'm humbled in the team willing to put me into this position. Our investors, our board, my co founders. It's an adventure. And yeah, I like to say we're failing up. Right? You're learning. You're running to walls you're failing, you're falling down, and you're getting right back up and running through that wall day in and day out. So I'm very excited for. I'm very excited by what we've built. I think it's nothing short of remarkable. Even more excited for the future, which is interesting, right? I think that the true sign of this idea, of this being our last job is the idea, like, do you wake up not every day, but almost every day more excited about the business than you did the day before? And that's absolutely the case with Metropolis.
- [82:39]
A
And there's this concept from Reid Hoffman. I think it's called begin again. I've never heard of this before. I couldn't find anything about it. But I think it's like a framework they use. What is it exactly? Is this related to this or completely unrelated?
- [82:52]
B
Yeah, no, it's actually interesting. It's not Reid Hoffman. It's Sam Harris.
- [82:57]
A
Oh, from Sam Harris. Okay.
- [82:59]
B
Sam Harris says begin again. And he talks about meditation, and he talks about this idea of just taking a moment, taking a breath, and beginning again. You know, I think being a founder can be so emotional. We talked about this roller coaster day in and day out, and, you know, just taking a moment, closing your eyes, breathing, just beginning again. I like that idea. I find it very calming and reassuring, you know, and this idea of so many things happening to you as a founder, so many things that are outside of your control, but your breath is inside your control. And just this idea of beginning again. So, yeah, I use that all the time. I love the expression of begin again, which allows us not to also ruminate and focus so much on the past, which can be so unhealthy. It allows us to begin again. And you hear a lot of entrepreneurs talking about how much time or lack of time they spend ruminating on the past and how much time they spend learning from the past but focusing on the future. And for me, that's illustrative or indicative of this concept of beginning again. I may be butchering it. I may be dastardizing what Sam Harris is actually trying to do. But I, you know, I. I really appreciate, you know, his guidance on meditation. And I love the idea of beginning again. Interesting.
- [84:23]
A
Yeah, it looks like a lot of, like, reflection, gratitude. I just googled really quick, see what all comes up. And do you. Do you have like a personal AI stack? Almost like, do you. How do you use AI? Like, day to day? Are you pretty vanilla? Just chat GPT, get a lot of stuff done, done there. Like Are there any, like, cool new tools that you use? I. I'm trying to get better at it just as much as I can find little tips. And then I know listeners, people listening, like, learning stuff too.
- [84:51]
B
On the spectrum of, you know, CEOs across the United States, I would like to say I'm in the top tier. I think in the total capability of the technology, I would say I'm in the bottom tier. In the context of not as juxtaposed to other CEOs, but this technology is capable of so much. And I think, all things considered, I'm just scratching the surface. I think as a technology company, we're doing profound things. I don't want to say we're on the frontier, but I'd say we're definitely on the cutting edge. And I think it's really exciting how our team is leveraging artificial intelligence internally, but also how we're building tools that leverage artificial intelligence, namely computer vision. I think for me personally, I'm probably leveraging Claude and Anthropic more than anything else, but I'm also using Gemini and OpenAI every single day.
- [85:49]
A
And so when you talk about things that you guys have done internally, anything interesting that another founder might be able to listen, like, oh, that's a cool idea. I'll try that. Any interesting processes that you guys have or tools you built internally?
- [86:03]
B
One of the things that we've focused a lot on is where does AI innovation come from? Is it top down, is it bottoms up? Is it disparate through the organization or dispersed through the organization? We're actually spinning up right now a chief AI officer. And one of the reasons we're doing that is we actually want to drive even more innovation and more adoption of Turing. So we're creating a new office. We've hired that team member, placing them in that role, and their job is going to streamline and build tools for our organization internally, directly tied to artificial intelligence. And that allows us to balance top down and bottom up adoption of artificial intelligence and how we can, as an organization, really leverage our resources to deploy AI at scale internally and deploy AI to be leveraged by our 23,000 employees, not a limited set.
- [87:11]
A
So what does the background of that person look like? Like, who'd you slide into that role? Like, what's their skill set, prior roles kind of look like? Because that could be. You could tell me almost anything, and I would think that that would be an interesting kind of fit for that role.
- [87:26]
B
This individual has both a lot of experience in organizational transformation and is a technologist so they have the ability to manage engineers and they have the ability and have been involved with on a consultancy side of large scale transformation. The other thing is this individual actually works at our organization today and they're highly trusted by many of the, if not all of the department leaders across our organization. So not only do they have that inherent trust, they have that inherent foundation and they have the background of driving large scale transformation across organizations and and the technical background to adopt that technology at scale and with speed.
- [88:09]
A
So kind of the idea of this sort of team that you're setting up is build tools and processes that the rest of the company will use to get work done faster or more efficiently, more profitably, et cetera.
- [88:23]
B
100%. 100%. It's once again, it's about revenue synergy. It's how do we focus our team members on their highest and best use. You know, we have 23,000 employees. What is the best way that they can be driving value to our partners at any given moment?
- [88:41]
C
Well, cool.
- [88:42]
A
Alex, this was, this is a lot of fun. Thanks for coming on the show.
- [88:45]
B
Oh, of course, Turner. I thought this was great. Thank you for hosting, thank you for taking the time, and thank you for
- [88:50]
A
taking the time to listen.
- [88:51]
C
Thanks again to this episode Sponsors Flex Upgrade to Flex Elite with the link in the Description and get $1,000 off your first $10,000 to spend numerl Put your sales tax on autopilot@numero.com and amplitude for AI analytics. Just ask Amplitude if you enjoy this conversation, please like comment, subscribe and share this episode with a friend who's thinking
- [89:12]
A
about doing an AI growth bio.
- [89:14]
C
Make sure to check out the back catalog of over 100 episodes with the founders of companies like Robinhood, Sweetgreen and Mercury. Tune in over the next few weeks for guests like Jim Balosic at Send Cut Send making custom metal parts and one of the pioneers helping Reshore Manufacturing back to the US And Ali Partovi and Nio, where we'll talk about Nio's unique take on early stage investing and lessons from investing in the first rounds of Cursor and Kalshi. If you don't want to miss any of these, subscribe to my newsletter the Split linked in the description to get each episode plus a transcript emailed directly to your inbox every week. Thanks again for listening. See you next time.