Pod Insights Capital Allocators Top 5 of 2025: #4: Alex Sacerdote About this episode We're counting down the top 5 episodes of 2025. At #4, it's Alex Sacerdote from Whale Rock Capital. Alex is a passionate TMT investor who describes how he finds companies ascending their S-curve of adoption.
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0:00 Ted Seides? With 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 Sacerdote 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.
0:34 Ted Seides? 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.
1:01 Speaker 01 All 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 in securities discussed on this podcast.
1:20 Ted Seides? Our guest on today's show is Alex Sacerdote, 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 MAG7, cloud computing, electronic vehicles, and blockchain technologies.
2:05 Ted Seides? 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
2:47 Ted Seides? 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
3:27 Ted Seides? spreading the word about Capital Allocators videos now available on YouTube. Please enjoy my conversation with Alex Sasserdo. Alex, thanks so much for joining me.
3:41 Speaker 02 Ted, 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.
3:49 Ted Seides? That is true. Why don't you take me back before that? When did you first get interested in stocks and businesses?
3:58 Speaker 02 Well, I think actually the first stock that I owned was Apple back when the PCs were coming out and I owe it to my father. He was longtime Goldman Sachs partner. He ran corporate finance in the eighties and then chairman of the private equity group in the nineties 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. 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.
4:42 Ted Seides? How did your father transmit that knowledge or interest to you?
4:47 Speaker 02 He always had so many stories of the characters he met, the IPOs, the M and 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
5:31 Speaker 02 a flashlight Barron's at 2 a.m. Sean Dwyer. 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 Citigroup. I was lucky to join the tech, media and telecom group there. That's a big thing for me is I was involved in technology early on. Then I realized I wanted to be an investor. During that period where we would spend three months with a company and then we'd do the IPO and I'd show up at Fidelity and there was a guy my age or a little bit older who
6:12 Speaker 02 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 startup called Interactive Imaginations and their finance group, 90 people, they did internet games as well as they started one of the first internet advertising networks. It was a good, not great company. It ultimately went public. It was one of the competitors of DoubleClick. And then I knew I wanted to get to the buy side and I was enrolled at Harvard Business School. I got a summer internship at Fidelity and that was a great moment for me where the
6:57 Speaker 02 seven or eight interns were each assigned a different industry. And I said, oh, you know about the internet. There's this new sector called e-commerce and our current internet thinks Amazon's a fraud. Why don't you cover these eight companies? And it was Amazon, Egghead.com, Preview Travel, OnSale, N2K, CD Now, which sold CDs online. I was like a kid in a candy store. I spent the entire summer visiting every one of these companies. I was at Amazon's first Investor Day, had lunch with Jeff Bezos. He still had that laugh. Wrote this 40-page report and we all had to present to the entire equities group. It basically said, the leader grows bigger, faster and wins.
7:42 Speaker 02 Buy Amazon and short everything else in the space. Half the people at Fidelity thought I was crazy because here was this book company that was going to beat Barnes and Nobles and made no sense. But we looked very carefully into the unit economics, the growth. At that point, even if the internet did not grow, they only had 2 million customers and there were 90 million internet users at that point. Hindsight makes it seem easy, but at that point, it was a harder call. And one guy who bought it was Will Danoff, who Has proved to be one of the best PMs in history, frankly. And it's great to have him as a mentor at Fidelity. But I was totally hooked. I had found my calling.
8:26 Speaker 02 I spent the next six years at Fidelity and Fidelity is an amazing training ground because there are so many different types of PMs. They give you free rein. They give you a computer, a credit card and a sector to cover. And you get tremendous access and tremendous travel to go do primary research. At Fidelity, they rotate you on the different sectors. I started with internet, then I did software. Then I moved out of tech and I did gaming, lodging, leisure and media. I ran the select leisure fund. And then I also ran the aerospace and defense fund.
9:07 Speaker 02 In the last two years, I was a sector PM, running a large cap tech and a mid tech. Ultimately, I saw such a huge opportunity in tech and I really wanted to specialize in tech. And at that point, really the career track at Fidelity was to get a big fund diversified that runs against the S and P 500.
9:30 Ted Seides? So as you're learning at Fidelity, how did you think about the mentorship that comes from having all these different PMs around?
9:38 Speaker 02 Fidelity is a very interesting culture because it's a huge team, but it's very individualistic. I don't want to say it's sink or swim. There's some training. You have to do industry reviews and write notes, but it's really up to you to 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 at Fidelity. There's value managers, growth managers, GARP managers, high yield debt managers. And then you're just in an environment where you're constantly talking about stocks,
10:19 Speaker 02 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.
10:47 Ted Seides? What did you find and learn along the way that made for an effective stock pitch to a portfolio manager?
10:53 Speaker 02 Peter 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 in 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 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?
11:39 Ted Seides? What 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?
11:47 Speaker 02 The amount of innovation and growth, you could just see it. I mean, we had the internet come and that spawned whole 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 could 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. Cause I started Whale Rock in 06. The iPhone was launched in 2007. And at that point, the big product for Apple was the iPod.
12:33 Speaker 02 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.
13:16 Speaker 02 I was like, okay, I'm going to be great for two years and then the rest of the world's 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 one.
13:55 Speaker 02 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.
14:08 Ted Seides? So 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?
14:21 Speaker 02 One 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 I 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 days of Amazon. And even before that, I invested in AOL for my own PA at the time, which was just growing like crazy.
15:03 Speaker 02 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.
15:47 Speaker 02 And then he connected it to the 3G network. And so all those barriers were immediately removed. And then 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 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.
16:33 Speaker 02 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 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.
17:17 Speaker 02 If you're LinkedIn, more people on LinkedIn, the more valuable it is, the faster it grows. It makes it impossible 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 cellphones. Or ASML has critical intellectual property in their lithography. So you've got these really great competitive advantages, learning how to spot those.
17:58 Speaker 02 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.
18:41 Speaker 02 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 OpEx would be. And so we calculated the earnings.
19:21 Speaker 02 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.
19:42 Ted Seides? When 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?
19:57 Speaker 02 It's great if you can get it right at the 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?
20:42 Speaker 02 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 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 and 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,
21:25 Speaker 02 that was $600 billion 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 sized it to 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.
22:09 Speaker 02 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.
22:21 Ted Seides? A 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?
22:36 Speaker 02 We'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 or trends. 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.
23:20 Speaker 02 You have to have deep research to really understand. And then when you have that deep research, when something like DeepSeek 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 learn everything we could possibly learn, meeting with private companies, public companies, mega caps,
24:03 Speaker 02 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.
24:20 Ted Seides? As you pull that thread now, a couple of years later, how are you thinking about AI as it relates to your framework?
24:28 Speaker 02 I 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 have a new computing cycle, you've got the whole stack. This was pioneered by Lou Gersner. 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,
25:13 Speaker 02 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 AI is going to take place in the cloud. There's 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 or incumbents.
25:57 Speaker 02 Our thesis was invest in the infrastructure layer first. Because that's always the first to inflect on the S curve. It 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 networking. And most of the dye has been cast. It's still 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.
26:42 Speaker 02 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 safest 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.
27:27 Speaker 02 And 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? And then there's the training in AI. There's the inference when people use it. So 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? And 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.
28:12 Speaker 02 We're only about 14% penetrated on the AIS 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 ratio.
28:57 Speaker 02 And now DeepSeek 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 here.
29:09 Ted Seides? How do you think about layering on shorts?
29:13 Speaker 02 The 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 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. In smartphones, if you were RIM, Palm, Nokia, HTC, Motorola, Lenovo,
29:56 Speaker 02 the list goes on, you're a complete zero. And there are a lot of 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 two early in the S-curve. Again, people get excited about new technology. It's real, it's gonna happen. But the barriers to adoption are strong and not removed. So AR/VR glasses, for example, has been stuck in too early in the S-curve. At one point, we were short a Japanese video game company where the CEO is like, I'm moving all to VR games. The problem is there's no VR games.
30:40 Speaker 02 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're 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,
31:22 Speaker 02 but they hang on and there's only two players. And so we talk about it. Are you a ice cube on a hot day in Arizona on the highway? Or are you a block of ice in Massachusetts in 35 degree weather that's going to last a long time? And maybe you're priced as though you're going out of business, but you've got another 15 years. So you have to be careful of that.
31:47 Ted Seides? Where have you had situations where you're long something that you think is in the right part of the S curve, you're short losers in that trend, but you got it wrong?
31:58 Speaker 02 In our experience, when we make something big and we have a 10 out of 10 conviction across the board, where you've got valuation support, you're really confident this S curve is happening, and you have very strong underpinnings of the competitive advantage, it really is a risk reducer because you've got valuation support. The biggest reason people blow up in tech is they miss on revenue. And when you're rocketing up that curve, you very often over deliver on the sales. And if you do have an airtight competitive advantage, there's few things people can do against you. But sometimes you get excited. One S curve that we got wrong, but we're able to get out was the EV S curve. And that's another
32:41 Speaker 02 dynamic S curve. The idea was that 50, 60% of cars were going to be electric. And that's happened in China. But when we hit about 10% in the US, it hit a wall. Tesla and the EV S curve was amazing, and they had a great competitive advantage, and they had underappreciated earnings power. But then that S curve went from being a 10 out of 10 to a zero out of 10 because it was mature in the USA. And the underappreciated earnings power went from being really cheap to expensive, given it wasn't growing. We haven't owned Tesla in a while because of that.
33:19 Ted Seides? How do you think about the importance of the management team attached to an S curve? Do you think Elon being a great example, Tesla versus Elon?
33:29 Speaker 02 For so long, we had three tenants and people would say, well, what about management? We realized that almost all of these companies that got into this position had these amazing leaders, but it wasn't the original reason why I invested. So we've added another tenant in so we can identify these super leaders. If you have a super leader and an innovation culture, so these leaders, they have a vision, they can see into the future, they are talent magnets. Their teams iterate and move so quickly, creating high-quality new products very fast. And they're mission-driven, but these leaders are also commercially oriented.
34:13 Speaker 02 If you have a leader like that, you can say, there's probably another few areas they can get into and they should have a premium for that, or you'll hold on to a stock for longer. And so historically, it was very few companies that could move to find the next S curve. Tencent was a beauty in that where they started literally with AOL Instant Messenger that they hacked and then turned it into a payment system, a social networking system, a mobile video game, and they dominated each of these and then did one after the next. It was just unheard of. And then, of course, Amazon, it's crazy to think that they dominated e-commerce and then cloud.
34:55 Speaker 02 And then they have an extra S curve on top, which is the getting into the advertising. Apple had one that was just so big with the smartphone. The challenge for them was they did well with tablets and they did well with earbuds. They're doing well with the watch, but those weren't big enough to move the needle. We were at one point hoping they would do a car because that is big enough. They decided not to. Everyone said when Steve Jobs left, the stock's going to be terrible, but he put that company in such an amazing position that it outlasted him. Now, Tim Cook is a great manager. He did a good job as well.
35:34 Ted Seides? Since you're trying to find these various S-curves and really the really great ones, how do you think about constructing your portfolio?
35:42 Speaker 02 We will buy something up to 10% at cost and then we'll let it get up to 15%. And usually it's reserved for larger companies and sometimes the largest can be most exposed to the best S-curve. So there is a misnomer in tech that a lot of allocators sometimes don't want to allocate to large cap because they don't think there's a lot of alpha. But if there's so much change happening and sometimes it's the biggest companies that are able to get into cloud or get into AI or get into smartphones, that there can be. So generally, if it's larger helps, if it's liquid and then larger just means you're that much more dominant. But sometimes we'll let smaller companies get into that.
36:27 Speaker 02 So usually we'll have one name at 10 and then we'll have a handful at seven or five. And the top 10 will be 60%. We like to have four to six different S-curves. AI infrastructure might be 20% of the fund. Internet security has been a big one. That was one of my first sectors of fidelity. E-commerce and we call it follow the sun where you look, see an e-commerce company trend in one country and then it's taking off in the country later. We followed the mobile video game S-curve 10 years ago. It hit first in Japan, then we knew it was going to hit in China and then we followed it to Korea.
37:11 Speaker 02 And then we've seen it happen all over the world.
37:13 Ted Seides? It's hard for almost anyone investing in public equities to not be thinking about the MAG7. And this is particularly relevant in your space. How have you thought about how you're positioning relative to MAG7?
37:26 Speaker 02 There's a lot to say about the MAG7. Some people are worried that there's a lot of market concentration and that's a sign that the market's frothy. What it's a sign of is the digital platform economy that we're in, where the leader grows bigger, faster and is able to accrue.
37:47 Speaker 02 Huge profits. So it's purely driven by the shape of the digital economy and not by some scary bubble. In general, the Mag7 is very attractively priced. You've got Amazon now, which is 25 times next year's Street EPS, which that's GAAP EPS, cheaper than Walmart, cheaper than Costco. Meta is something like 22 times earnings. Microsoft is 26-ish. Tesla's quite high. But in general, the Mag7 has moved up because of the earnings have been so strong. In addition, most of these companies have major scale and they have
38:31 Speaker 02 cost savings. So they're able to grow without adding costs. If they want to be more aggressive, they can dial back costs. I think these Mag7 have the most to gain from AI on so many different dimensions. Number one, revenue growth. A lot of the Mag7 is driven by advertising and AI plus advertising is amazing. We've seen this with Apple oven. We've seen this with Meta. Google's doing it using a massive self-learning LLM to target 30,000 times more effectively than the old CPU-based systems. In addition, a lot of the Mag7 have their own clouds. So they're going to benefit from other companies' AI and make money from that.
39:16 Speaker 02 So you've got revenue opportunities. Then you've got cost savings opportunities 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 mag seven, they have massive data advantages, a thousand X the data than
40:00 Speaker 02 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 advertisers, 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.
40:45 Speaker 02 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 mag set 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 mag seven, but generally I don't think it's a sign of a bubble.
41:26 Ted Seides? What are some of the other S-curves you're watching?
41:30 Speaker 02 Driverless 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 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.
42:10 Speaker 02 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.
42:19 Ted Seides? How have you thought about layering in privates on your investing?
42:22 Speaker 02 One 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 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.
43:08 Speaker 02 Our first one was Stripe and we loved Adyen. 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 Adyen, you better know what's going on at Stripe. We were doing tremendous amounts of work on Adyen and every Adyen 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
43:53 Speaker 02 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.
44:15 Speaker 02 And then Revolut, either one or two digital bank in almost every single country in Europe with a fantastic leader.
44:22 Ted Seides? One of the things we haven't talked about are crypto and blockchain investing. I'm curious to, as you've looked at it over the years, what you've seen.
44:31 Speaker 02 We 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 of 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.
45:15 Speaker 02 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 and fund. I haven't been a huge Bitcoin guy, but 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.
45:46 Ted Seides? You started the firm right before the financial crisis and a couple of years ago 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.
46:01 Speaker 02 Tech 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. 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.
46:45 Speaker 02 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.
47:30 Speaker 02 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, can't enjoy the highs as much because you know 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.
48:04 Ted Seides? So when you set out, reading the newspaper, following this stuff at 2:00 AM, now 18 years, teams 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?
48:24 Speaker 02 Well, it's just, I'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.
49:05 Speaker 02 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.
49:15 Ted Seides? All 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?
49:23 Speaker 02 Time wise, it's definitely golf. It's great. You get to spend a lot of time with people. It's great exercise, walking, and it'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.
49:40 Ted Seides? What was your first paid job?
49:42 Speaker 02 Well, 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 mopeds in Nantucket as well. I've had a lot in my fair of interesting summer jobs along the way.
50:06 Ted Seides? What do you remember learning from those early experiences?
50:09 Speaker 02 The 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.
50:24 Ted Seides? So despite gravitating to stocks at a young age and making that your profession,
50:32 Ted Seides? How's your life turned out differently from the way you expected it to?
50:35 Speaker 02 I 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.
51:14 Speaker 02 So that's been a surprising thing, but since 99, 25 years later, that was a big surprise.
51:21 Ted Seides? Alex, last one, if the next five years are a chapter in your life, what's that chapter about?
51:26 Speaker 02 It's getting 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 in 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.
52:04 Speaker 02 I'm going to be here for decades, decade at least, like 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, but nothing too different from here.
52:26 Ted Seides? Alex, I know you don't do this often, if ever, so really appreciate you taking the time, telling the story.
52:32 Speaker 02 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.
52:41 Ted Seides? Thanks 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 podcast transcripts, my investment portfolio, and a lot more. Have a good one, and see you next time.
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