Speaker 1With the year in review, we also kick off our countdown of the most popular episodes of 2025. We'll drop two this week and the top three next week. And at number four, it's Alex Sasserdote from Whale Rock Capital. Alex is a passionate TMT investor who describes how he finds companies ascending their S-curve of adoption. Next week, we'll drop the top three. Wishing you a relaxing, enjoyable, and very happy holiday. Hello, I'm Ted Seides, and this is Capital Allocators. This show is an open exploration of the people and process behind capital allocation. Through conversations with leaders in the money game, we learn how these holders of the keys to the kingdom allocate their time and their capital. You can join our mailing list and access premium content at capitalallocators.com.
Speaker 2All opinions expressed by Ted and podcast guests are solely their own opinions and do not reflect the opinion of Capital Allocators or their firms. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Capital Allocators or podcast guests may maintain positions and securities discussed on this podcast.
Speaker 1My guest on today's show is Alex Sasserdote, the founder of Whale Rock Capital Management, a technology-focused investment firm that manages $8 billion. Across hedge fund, long-only, and hybrid strategies. Our conversation covers Alex's path to running Whale Rock, shaped by early exposure to the markets through his father, a longtime partner at Goldman Sachs, and his formative years at Fidelity. We dive into the key lessons he learned at Fidelity, the development of his investment framework centered around S-curves, competitive advantages, and underappreciated earnings power, and the application of the framework to AI, the MAG-7, cloud computing, electronic vehicles, and blockchain technologies. Before we get going, after eight years of being told by my friends that I have a face for podcasting, we decided to rip off the Band-Aid and produce video recordings. It turns out that YouTube is the fastest-growing channel for listening to podcasts. Not Apple, still the biggest. And not Spotify, still the biggest among younger listeners. It's YouTube. Now, I, for one, don't understand this at all. It's hard for me to imagine watching two people talk to each other, especially when so much of my listening comes when I'm on the move. But it seems that's not the trend, and the trend is your friend. At least according to Cliff Asness and others with the Momentum Factor Strategy. So we're giving it a shot. That's despite my hesitancy, and despite quite enjoying the many times I speak to both friends and new friends who tell me it seems strange to hear me talk while seeing me at the same time. Now, I'm not sure if that's a sensory thing, or if my friends were right about my face for podcasting, but either way, it seems I'll be a little more visible going forward. The irony of this is most of you hearing this already are listening, so you may be the exact wrong audience to share that we've added video. But regardless, if you do have a friend who's addicted to YouTube, please let them know we're now stimulating an additional one of the five senses. Thanks so much for spreading the word about Capital Hour, Allocator's videos now available on YouTube. Please enjoy my conversation with Alex Sasserdote. Alex, thanks so much for joining me.
Speaker 3Ted, I'm very excited to be on the show. We've been friends for a long time since 1997 at Harvard Business School, classmates, class of 99.
Speaker 1That is true. Why don't you take me back before that? When did you first get interested in stocks and businesses?
Speaker 3Well, I think actually the first, first stock that I owned was Apple back when the PCs were coming out and I owe it to my father. He was a long time Goldman Sachs partner. He ran corporate finance in the 80s and then the chairman of the private equity group in the 90s and into the 2000s. I lived in New York and I always was exposed to a lot. We had a few shares of Apple and we were so excited when it split. And then in college, I remember buying Boeing on the theory that they were somewhat of a monopoly and air travel had a huge future. I've always been interested in investing from an early stage and I was lucky to just be exposed to my father and a lot of others along the way.
Speaker 1How did your father transmit that knowledge or interest to you?
Speaker 3He always had so many stories of the characters he met, the IPOs, the M&A, the deals he would do. Sometimes we'd meet those guys along the way. He was involved in the Alaskan Pipeline and meeting some of the entrepreneurs that were trying to build that out and just hearing his stories of the deals he would do all over the world. He was chairman of the Commitments Committee at Goldman Sachs, and he talked about some of the deals he was able to keep them out of and then told us about some of the stocks he would own. He would always read Barron's and I grew up reading the newspaper and in college would read Barron's. Actually, one of our classmates basically decided to invest. In my firm early on because we were on a weekend at HBS and he saw me reading with a flashlight Barron's at 2:00 a.m. Sean's Liar I always had a small account and was investing along the way I started in the business in investment banking and I worked at Smith Barney which became city group I was lucky to join the tech media and telecom group there that's a big thing for me as I was involved in technology. early on and then I realized I wanted to be an investor during that period where we would spend three months with a company and then we do the IPO and I'd show up at Fidelity and there was a guy my age or a little bit older who just knew everything about the industry and he was talking directly to the CEO his job was to evaluate is this a good company or not I immediately was like that's what I want to do in the year before business school I worked at an internet advertising company. early on and then I realized I wanted to be an investor during that period where we would spend three months with a company and then we do the IPO and I'd show up at Fidelity and there was a guy my age or a little bit older who just knew everything about the industry and he was talking directly to the CEO his job was to evaluate is this a good company or not I immediately was like that's what I wanted to do in the year before business school I worked at an internet advertising company. early on and then I realized I wanted to be an investor during that period where we would spend three months with a company and I'd show up at Fidelity and there was a guy my age or a little bit older who just knew everything about the industry and he was talking directly to the CEO his job was to evaluate is this a good company or not I immediately was like that's what I wanted to do in the year before business school I worked at an internet advertising company. early on and then I realized I wanted to be an investor during that period where I would spend three months with a company and I'd show up at Fidelity and there was a guy my age or a little bit older who just knew everything about the industry and he was talking directly to the CEO his job was to evaluate is this a good company or not I immediately was like that's what I wanted to do in the year before business school I worked at an internet advertising company. learn how to do creative research, but you learn a lot by watching all the different PMs and their various styles. And of course, you've got to pitch your stocks to all these PMs. So there's so many great characters of Fidelity. There's value managers, growth managers, GART managers, high-yield debt managers. And then you're just in an environment where you're constantly talking about stocks, other people's sectors, your own group, and your own peers, your peer analysts as well. I've had a few great mentors who really taught me to push and do creative research in different ways. What's the gross margin? What are all the factors that drive into that? And then how can you research those to get even deeper on those? But there's so many different styles of investing. You learn what your style is very organically.
Speaker 1What did you find and learn along the way that made for an effective stock pitch to a portfolio manager?
Speaker 3Peter Lynch. He wasn't active when I was there, but he would meet with the analysts individually three or four times a year. And he always had his thing, the egg timer, where you go into his office and he turns the egg timer. In fact, at one point, I had one here. You've got to figure out how to do it quickly. Obviously, it's the key points. It's the thesis. It's where you're differentiated. You've got to get your earnings estimates, your PE, get to the crux of it very quickly. And I find that's so hard. It's a hard skill for a lot of people where everybody's pressed for time, getting to the key points very succinctly and quickly, and just cutting down to what really matters and why is this so much better.
Speaker 1What was it that you saw in the tech sector that led you to be excited about the future and wanting to push in that direction?
Speaker 3The amount of innovation and growth, you could just see it. We had the internet come and that spawned a whole new. New companies, each tech innovation from the mainframe to the PC, to the client server computing, to internet builds upon the previous one and unleashes more growth and more innovation. And you can see the tech was such a small part of the GDP, but through the internet was rapidly expanding. This was right at the cusp of the iPhone because I started well. Rock and oh six, the iPhone was launched in 2007 and at that point, the big product for Apple was the iPod. You could just see digital music and the explosion of the iPod and what that did to the earnings power moving from the iPod to the phone was such an obvious move because all you really had to do was put a modem into that iPod and it was one device that could do more. Obviously. At that time, I didn't even realize how powerful that would be. What's been so fantastic that I didn't see is each of these cycles gets bigger and bigger and takes more and more of the economy and it doesn't stop. And frankly, I was a little worried when I first started doing internet. I was like, okay, I'm going to be great for two years and then the rest of the world is going to figure out all about the internet and there won't be that much change. And then I'm going to have to find other ways to make alpha. But what's been so dramatic and shocking is the amount of major innovations and S-curves and how big and broad they become. I mean, mobile was just massive, but now it's just table stakes. After that, we had the cloud. Now we've got another one with AI. Each one gets bigger and bigger and each one enables the previous. So I knew inherently tech was going to be a great place for growth and also stock picking. But frankly, I didn't think it would be as huge as it has become at the time.
Speaker 1So when you spent your six years at Fidelity and you were exposed to all these different styles, you knew that you were interested in the growth of tech sector. What did you find was your style of investing and how you wanted to pursue the trade?
Speaker 3One of the things I was good at understanding, was that you really wanted to be behind product cycles and true growth. And in tech, there are areas that don't grow that much. And frankly, the period after the internet crashed and before the mobile revolution happened, there weren't any major mega trends happening, but there were minor trends. And it would make sure that I was invested behind those. And then, of course, I started in the internet itself in 97, 96 and got the early, early days of Amazon. And even before that, I invested in AOL for my own PA at the time, which was just growing like crazy. I devised this three-part framework, which we're known for at Whale Rock, which is S-curve, competitive advantage, underappreciated earnings power. And the first one is all technologies start slowly. They have a lot of barriers to adoption. It might be too expensive or complicated. There might not be the right ecosystem. There might be a lot of inertia. There were smartphones before the iPhone, but they were big, clunky, hard to use. There was no wireless network, and they were expensive. Steve Jobs fixed all that with a $200 phone, a touchscreen monitor that your grandmother or child could use. And then he connected it to the 3G network. And so all those barriers were immediately removed. And then you hit that. You hit that mainstream takeoff phase, that inflection, where you go from 1% of people having a smartphone to 50% in a four- or five-year period. That creates just incredibly rapid unit growth, some of the fastest growth in the global economy. Not only is it fast, but it actually can be predictable. So one of the reasons Warren Buffett has not liked tech is he found it to be so unpredictable. But this S-curve framework. It gives you insight into how big the market can be, where it might be in four or five years. It's like a map into the future. And that's why you want to invest in tech. What are the characteristics of these big, multi-year, now trillion-dollar companies? How do we find the next Microsoft or Dell or IBM in the mainframe world? So find a powerful S-curve. And then second, look at all the companies in that. There's a lot of companies in the ecosystem trying to find the one or two that have an incredibly powerful competitive advantage. And the thing about the digital world is some of these competitive advantages can be much stronger than in the offline world and accrue faster. In software, you can be the operating system. On the internet, you can have a really powerful network effect. If you're LinkedIn, the more people on LinkedIn, the more valuable it is, the faster it grows. It makes it impossible. But for the competition and in e-commerce, you can have brand, you can have scale, you can have scale that helps you in logistics. You can be a platform company where everyone needs to be on your system. Or you might have critical intellectual property like Qualcomm, for example. Everybody had to pay them a 3%, 4% royalty if they wanted to do cell phones. Or ASML has critical intellectual property in their lithography. So you've got these really great. competitive advantages, learning how to spot those. And then when you get the S-curve plus a competitive advantage, that's the third thing, which creates exponential earnings growth, which we call it underappreciated because very few people look out two, three, four years into the future. When you get S-curve and a rising margin, your earnings don't grow linearly. They grow exponentially. And it's very hard for the world to think exponentially because very few things in our day-to-day lives do this. So if you can get those two things right, very often you can buy amazing companies at extremely low multiples. And it might look expensive on the first or second year, PE, but three, four, five years out, it might look crazily cheap. Examples of that are when we first bought Tesla at the end of 2019 and 2020, when the EV S-curve really took off because Elon got the price of the Model 3 down to $40,000. And then we saw they had very good competitive advantages. We said, wow, they can do 2 million cars at a $50,000 ASP with an X gross margin. And we knew what the op-ex would be. And so we calculated the earnings. And looking back at it, we were buying Tesla at literally four times the earnings they did three years later. And similarly, we loaded up on NVIDIA right after ChatGPT in January 2023. We were buying NVIDIA at four times the earnings they're going to do this year.
Speaker 1When you're thinking about figuring out that S-curve, let's assume you find a trend that you think is going to climb an S-curve. How do you decide where you want to buy in on a stock on the S-curve?
Speaker 3It's great if you can get it right at the end. inflection point. But the thing about the S-curve that's so important is it tells you how long you can still own it. And sometimes it's okay to be late because maybe it's unclear why or how it's totally inflecting, or you're not sure how strong the competitive advantage of a company in that space is. But generally, once you get to 30 to 40% penetrated on the S-curve, that's usually when that exponential growth becomes linear. Because in the first few years, you go from 1% to 3%, 3% to 6%, penetration along the S-curve. And then a value of the S-curve is how big is this market and how long can this trend keep on going? A lot of times, the S-curves can be dynamic, because these are new things that we don't always know for certain how big they're going to be. So we do a tremendous amount of research to figure out how big the S-curve is. And some can be. Be very quantifiable. And some are more, you're directionally right. A good dynamic S-curve would have been the cloud computing. When cloud first came out, there was no real estimate for it. And no one really knew what it was. Is it just a server in a warehouse? And we realized it's not just the server, it's the networking, it's the storage, it's the database, it's all the software layers. And we looked at, in the traditional world, that was 600. Billion dollars of spend, and AWS was going after all of it. This was the biggest market in business IT ever, because previous markets were just the server market, or just Cisco was good in networking, EMC was good in storage. And the analysts were set up in different compartments, and they couldn't see this coming together. That was 600 billion. And then we said, it's going to be 50% deflationary. So we've sized it at 300 billion. And then we looked at Amazon's revenue, and that was 1 billion. Then Amazon grows like a weed. And what happened, it actually wasn't deflationary. It was equal. So now we're saying, we thought it was 300 billion. It's actually 600 billion. We have another five, maybe even 10 years to go on this, and it's still growing.
Speaker 1A lot of these technology trends, the competitive landscape can change quickly. How do you conduct your research so that at any point in time, if there's a wobble in a quarter, you can have conviction in a longer-term trend?
Speaker 3We've got a team of 10 of us, and we're doing 2,500 face-to-face meetings with management teams a year, using our S-curve competitive advantage underappreciated earnings power framework to guide where we look. So we're focusing on these different S-curves or sub-S-curves. And then we're going to industry trade shows, many different countries. We're talking to all the competitors, suppliers, customers. And we've been doing this for 18 years. We call it the Whale Rock Learning Machine. We look for clues as to what's changing or what looks like another history rhymes in a lot of ways. You have to have deep research to really understand. And then when you have that deep research, when something, deep-seek comes along, it scares the rest of the investment community. AI had been around for 20 years, but serious last five years, but it was hidden inside the clouds. And it really wasn't exposed to anybody or consumers or businesses. And then bam, OpenAI put out ChatGPT. It's just like the Netscape moment. And then four of us really spent 110% of our time just sprinting to the next step. And then we're going to be able to do that. And then we're going to be able to learn everything we could possibly learn, meeting with private companies, public companies, mega caps, chip companies in Taiwan, in the US, software companies, venture capitalists, you name it, to put together the pieces and anticipate that we might not have all the answers, but we knew the questions to ask and where the fulcrum issues would be.
Speaker 1As you pull that thread now, a couple of years later, how are you thinking about AI as it relates to your framework?
Speaker 3I think AI is definitely one of the major mega S-curve trends. And it's great that we have another one to invest in. It's going to be a multi-decade story like the cloud, like mobile. This is in a lot of ways more complicated than the previous ones. With smartphone, you had units and ASP. You could really quantify easily how big the market was with precision. When you look at the market, you can really quantify how big the market was with precision. When you have a new computing cycle, you've got the whole stack. This was pioneered by Lou Gerstner. He talked about the new stack in a client server world versus the mainframe world. In the AI world, there's a new stack. And at the bottom, always first comes the infrastructure layer because you've got to build the compute out. And when you have a new stack, that's when the inflections happen, creating winners and losers. Then above that is the cloud. Most of the cloud delivery layer with AWS, Azure, there's some of the new Neo clouds, and then some will be delivered on-prem. And then above that is the foundational model layer. These are the big LLM companies like OpenAI, XAI, Google Gemini, Meta. And then above that are the applications that can be software applications or internet applications. And they can come from startups like Microsoft, Amazon, and so on. And so we've got the infrastructure layer first because that's always the first to inflect on the S-curve. And also, no matter who wins above, we know we're going to need tremendous amounts of AI infrastructure. And then third, we also know what the ecosystem's like. We know it's going to happen on GPUs. We know it needs a lot of shifting a little bit, but this is the competitive advantage. We were able to understand and identify winners. At the foundational level and at the application level, especially with startups, it's very challenging to figure out the ecosystem's not baked. It's a lot like internet 1.0 when you had seven or eight search engines, and then later Google came out and crushed them all. So we found that to be a dangerous place to invest at the infrastructure layer, the best place to invest, because not only was it coming first, but it was analyzable who the winners could be. Then we did all kinds of work to quantify how big this S-curve would be. We were quite bullish, but we really underestimated how big the CapEx could be. That's another dynamic S-curve situation. There's a lot of ways to skin the cat, but we looked at how much capacity was getting put in place. How many chips were they able to make? Because it was under such short supply. Then, of course, that wasn't enough. We got to figure out, are we really going to need all this compute? How many major foundational models will there be? What's it going to cost to train all of these? How many small models will there be? Then there's the training in AI. There's the inference when people use it. Then we tried to forecast how many times would people go to the internet and ping ChatGPT? What if Copilot gets adopted? How many people are going to be using OpenAI? Then anticipating the future of what kind of applications we're going to hit and how compute-intensive those would be. Our thesis has been AI CapEx has been the place to be, but it's not over. We're only about 14% penetrated on the AI S-curve for infrastructure. Within the cloud, it's only 3% or 4%. But everybody got so scared about, oh my God, the first year, NVIDIA's revenues did this. It has to go down. We feel good about that because these changing models, particularly with inference reasoning, you have these models where you ping it and then the model thinks and reasons against itself, checks its work, does a multi-part question, and it might ping the model 100 or 1,000 times. When we were doing our calculations, we didn't bank on the 1,000 to 1 inference. And now DeepSeq is basically solidifying this inference time reasoning is going to be adopted by all the models. That's another reason we feel positive about the AI infrastructure story from
Speaker 1here. How do you think about layering on shorts?
Speaker 3The S-curve framework is good for shorting as well. And you can find great shorts all across the S-curve. The classic would be mature and getting disrupted. So traditional media, you can find great shorts all across the S-curve. Media by Netflix or newspapers or CPUs losing to GPUs. Then you can have great shorts in the best part of the S-curve because you might be in the sweet spot of the S-curve and selling into it. But if you don't have an airtight competitive advantage, you're a zero. You're going to destroy value. And smartphones, if you were RIM, Palm, Nokia, HTC, Motorola, Lenovo, the list goes you are a complete zero and there are a lot electric vehicle companies that tried to be Tesla or BYD, and they're all very likely to either fail or not generate any profits. And then there's too early in the S-curve. Again, people get excited about new technology. It's real. It's going to happen. But the barriers to adoption are strong and not removed. So AR, VR glasses, for example, has been stuck too early in the S-curve. At one point, we were short a Japanese video game company where the CEO was like, I'm moving all to VR games. The problem is there's no VR games. Headsets cost $5,000. There's no killer app. There's no market in place. One of our best shorts was an EV battery company 12 years ago spun out of MIT, supposedly had proprietary. technology. And they were building capacity for this coming EV boom. But it was 10 years too early because the cars were expensive. There was nowhere to charge them. Their range was 50 miles instead of 300. Some mistakes people make in shorting in tech is there are a lot of old technologies, but maybe you still have a competitive advantage. And maybe your earnings power might be underappreciated. People have been trying to short the disk drive companies for years. But you're not going to be able to short the disk drive companies for years. Because these are all digital workers, and it's coders, and it's running digital warehouses. They have the temperament, the culture to do this much faster than other companies. Goldman Sachs can apply AI, but a banker is living in the real world, at least for now. Or a grocery store, they'll have AI to make things more efficient, but they still need the people there for now, at least. These big cloud, Mag7, they have massive data advantages, a thousand X the data. than anybody else has. And then they have the ability to invest in it. Then they've got distribution. And that's huge in AI. Having the customers already in a digital surface area, you can inject AI into Google Docs. You can inject AI into Gmail, into YouTube. And then there's one more thing is the first stage of AI advertising is incredibly better targeting to show me the right video and then show me the right ad. And we think that's driven 50s to 70 billion of extra sales to Meta by adopting AI. But then the next piece is, if you're a small advertiser, let's say you've got a $20 million e-commerce business, you don't have Madison Avenue making ads for you. You've got to do it yourself. The next phase with AI is you download all your SKUs, a picture of what it is, a description. Then AI makes 10 ads of each SKU. That's ahead of us as well. So, the MagSep won't be all monolithically growing. The last two years, it was all good. And they were all depressed. And they all came back in 23. And then they all had good years in 24. Now there's valuation discrepancies. And some companies are going to benefit a little bit more than others. It's going to be a lot more disruption or variability in the MagSep. But generally, I don't think it's a sign of a bubble.
Speaker 1What are some of the other, S-curves you're watching?
Speaker 3Driverless did hit the mainstream takeoff. We are taking driverless taxis, one basis point of miles driven. And they're going to be rolling out cities. And it's just going to get bigger and bigger. So, that is one that's definitely going to be hitting. It could be negative for some companies who are selling cars that don't have good technology. Or maybe some people think it might be bad for Uber. We'll see what happens with that. Another one is robotics. And, you know, I think it's going to be a lot of different things. I think it's going to be a lot of different things. And that is very exciting. But a lot of people are starting to believe that this could be the year. We've seen a lot of that in the past. I think it will take longer before we can have a humanoid robot doing anything too complicated. But we'll see what the world holds there. So, we're watching those two.
Speaker 1How have you thought about layering in privates on your investing?
Speaker 3One thing that's definitely happened is companies are staying private longer. And that was a trend that started with cloud computing because you didn't need as much CapEx. You could be more capital efficient. And then the private markets grew larger. And so, frankly, our S-curve framework is borrowed. We took a venture capital approach and applied it to the public markets. And so, this same framework fits incredibly well for privates. Now, we do late stage privates. And so, these are companies that would have been public anyway in the past that have some scale. And so, we're watching those two. And so, we're And we were meeting, since companies are staying private longer, if you're going to be investing in the public markets, you really have to know what's going on in the private markets. Our first one was Stripe. And we loved Audion. There's two payment companies, which are next-gen cloud-based leading payments companies. And those two are like Coke and Pepsi. They're a little bit different in different ways. But in order to invest in Audion, you better know what's going on. And so, we're watching at Stripe. We were doing tremendous amounts of work on Audion. And every Audion call would be like, tell us about Stripe. And then we were fortunate to have the opportunity to invest. And along the way, we're like, oh my God, we need to make Stripe a 10% position. And then we got that chance during COVID. And that's played out really well. We're fortunate in that it's about 10% of our capital and 55% of that capital is in four iconic leaders that really fit this framework well. Stripe, which is dominating digital cloud-based payments. Canva, which is next-gen cloud-based Adobe. Databricks, which has emerged as the leading software, AI, heavy analytics, big data platform. And then Revolut, either one or two digital bank in almost every single country in Europe with a fantastic leader. One of the things we
Speaker 1haven't talked about are crypto and blockchain investing. I'm curious to hear your thoughts on that. I think it's a great question. I think it's as you've looked at it over the years, what you've seen.
Speaker 3We spent a lot of time looking at it, trying to learn as much as we could. We met with dozens of these companies. It was always a technology looking for a problem. The use cases were few and far between. Also, there was an element of it where there were all these meme coins and it wasn't solving any true productivity gains. We thought that was somewhat a false S-curve. There was a view that, oh, the whole finance industry would be rebuilt on top of the blockchain, or we're going to rebuild search on top of the blockchain, or we're going to make a blockchain version of Facebook where no one has our data, or we're going to make a blockchain stock market. And that's a great idea, but it's a chicken and the egg problem and the stock market works pretty well. So that was definitely too early on the S-curve. We're not going to buy Bitcoin in the fund. I haven't been a huge Bitcoin guy, but it's a great idea. It is sort of like digital gold. And in a way, that's an S-curve asset class with a fixed amount. And so that's going to have a lot of volatility, but it could be positive. Stablecoin, that's a true S-curve. It's so efficient way to move money around. So that's actually one that we're very much focused on now.
Speaker 1You started the firm right before the financial crisis. And a couple of years ago, it had another big sell-off in the tech space. I'm curious how you've navigated the volatility of this space. While you're trying to get to these longer-term cycles.
Speaker 3Tech has outperformed for the last 50 years. And every seven to 10 years, there's a significant sell-off in tech. And tech generally does the worst. It's the most volatile, even though it's sometimes a little bit more secular than cyclical. There is a cyclical nature to it. But each sell-off has been followed by a major innovation cycle. So after 92, 94 was the PC and the internet cycle that drove into 99. The 99 crash after that, there wasn't a major new product cycle. And then you had 08. But in the middle of 08, the iPhone came out. So then you had mobile cloud thereafter. And then here with the interest rate spike and the COVID hangover, you had a significant crash only to be followed by another massive S-curve. So volatility comes with the tech territory. And it's hard to totally protect against that. In our fund, we do own these big secular winners. And sometimes we try and match them with high-growth losers that are going to lose over time. So sometimes there is a mismatch. But over time, that's the right thing to do. So volatility is part of the ballgame. And it's important to have investors who understand that they know your process. They know what you're trying to do. It's also important not to get shaken out of your process. And so we had a hard 22. But I'm really proud of the team because we stuck to our process, keep our heads down, and we focus. When you're at the top, just realize you're not as smart as you think you are. When you're at the bottom, you're not as dumb as you think you are. And humility is an important aspect of this. And I learned early, you can't there's going to be lows. And so it's not as giddy when you're doing well, but it's also not as bad as when you're in a harder period.
Speaker 1So when you set out reading the newspaper, following this stuff at 2 a.m., now 18 years, team's doing 2,500 meetings a year, what keeps you excited to keep going in an industry where lots of people at some point in time have had enough, done enough, it's intense enough that they decide to just hang it up?
Speaker 3I'm super curious. And I love the business. I love learning about new things. I love meeting people along the way. I love working with my team. The tech space, there's just always so many fascinating and interesting aspects to it that I'd be reading about and trying to figure out if I wasn't in the business anyway. And so I really enjoy playing the game. Maybe if tech was rolling over, there's nothing going on. It might not be as interesting. But I love stock picking. I love investing. I love learning. And I love building this firm. This is what I really enjoy doing, building the firm, the team, the organization, all the relationships I've made with LPs, with employees, management teams, just brings a lot of satisfaction.
Speaker 1All right. So I want to make sure I get a chance to ask you a couple of closing questions. What is your favorite hobby or activity outside of work and family?
Speaker 3Time-wise, it's definitely. Golf. It's great. You get to spend a lot of time with people. It's great exercise walking. And that's a real challenge, improving and getting better. And just the friendships you make along the way. That's one of the top things I enjoy doing.
Speaker 1What was your first paid job?
Speaker 3Well, I was a dishwasher in Nantucket. Rose my way up to be a waiter at the age of 14. There's a crazy Nantucket icon named Todd Arno, who had to battlefield promote me because all the college kids left and I was 13 doing that and I rented moped Peds in Nantucket as well. I've had a lot in my fair of interesting summer jobs along the way.
Speaker 1What do you remember learning from those early experiences?
Speaker 3The restaurant industry, there's a lot of characters in that. And I think people are working hard and the importance of tips, treating people well, looking people in the eye. You see who's a good person on how they deal with the staff.
Speaker 1So despite gravitating to stocks at a young age and making that your profession, how's your life turned out differently from the way you expected it to?
Speaker 3I grew up in New York City and did not expect to be living in Boston. I went to business school up here and I got the dream job at Fidelity and I always thought I would be back in New York. And then Boston just completely grew on us. It's a great city slash town because it's got size, but it's also a great community and it's got. Tremendous economic job opportunities with finance and healthcare, and then just wonderful communities. And you can live 20 minutes outside of town and there's great neighborhoods inside the city and then great summer opportunities all around and just great people. So that's been a surprising thing, but since 99, 25 years later, that was a big surprise.
Speaker 1Alex, last one. If the next five years are a chapter in your life, what's that chapter about?
Speaker 3It's getting my. My kids launched and seeing them through, it's going to have to be their own experience, but helping them along the way. Got one, a junior in college and one who's going to be going to college next year. We've got the empty nester hood, which we're prepared for and excited for the next chapter. And then work-wise, it's solidifying whale rock. It's in our mission statement that we want to benefit from the innovation and technology financially and put up excellent returns. And then we want to build an organization that supports and can fulfill that mission for decades to come. I'm going to be here for decades, decade at least, but setting up the firm to succeed for the long-term. And that's a hard thing, as you know, especially for public hedge funds. There's been some who've been able to do it quite well, but that is a goal of mine. It's a challenge on how you make that happen. Nothing too different from here.
Speaker 1Alex, I know you don't do this often, if ever. So really appreciate you taking the time to tell
Speaker 3the story. Ted, that was great. You have one of the best podcasts around. You ask thoughtful questions and I really appreciate the chance to do this.
Speaker 1Thanks for listening to the show. To learn more, hop on our website at capitalallocators.com, where you can join our mailing list, access past shows, learn about our gatherings, and sign up for premium content, including podcasts. Transcripts, my investment portfolio, and a lot more. Have a good one and see you next time.
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