Lessons from 20 Years of Venture Capital (Roelof Botha, Managing Partner & Steward at Sequoia Capital)

A lot of what we think about at Sequoia is we need to buy discounts to the future and we need to not be anchored and worried about paying premiums to the past because these companies can grow so, so quickly. And a company that you looked at 6 months ago is now raising money again at 3 times the valuation. And you wonder, well, I could have invested 6 months ago and I didn't, and I maybe should have, and now it's 3 times and I should just ignore it. And the question's not the premium. The question is, given what you think this company can become in the long run, is this a good entry price?

How do you feel about the US's ability to lead in the AI race?

I think it's very important for us as a nation to think about the importance of staying ahead in the AI race. I think the US is in the lead. I'm confident the US can remain in the lead, but it's healthy to be paranoid. Complacency would be the death knell of us.

Hey, I'm Mario, and this is The Generalist Podcast. You've probably heard the saying, the future is already here. It's just not evenly distributed. In this podcast, I speak with the visionaries who are living in these pockets of the future to help you see it earlier, understand it better, and capitalize on it. Today, I'm speaking with Roelof Botha, the managing partner and steward of Sequoia Capital. In his 2 decades at Sequoia, Roelof has backed transformative companies like YouTube, Instagram, MongoDB, and Unity, helping them grow from seeds to giants. Before joining Sequoia, Roelof was CFO of PayPal during its near-death experience and remarkable turnaround, a formative period that shaped his investment philosophy. Companies backed by Sequoia when they were private now account for more than 30% of the Nasdaq's total market value. This extraordinary track record stems from the firm's ability to maintain shrewd judgment across more than 50 years of market cycles. In our conversation, Olof reveals the frameworks and principles that have enabled Sequoia to consistently identify legendary companies before the rest of the world. He also shares how he maintains equanimity during speculative booms. In our conversation, we discuss the psychology of investment decisions and how naming your cognitive biases can disarm them. The art of maintaining discipline in abundance. Why certain companies with excessive funding often lose their edge, and lessons from historic missed opportunities, including Roelof's candid reflections on passing on Twitter's early rounds. I learned so much from this conversation about building a resilient investing mindset. I hope you'll walk away with practical insights about making sound decisions in uncertain circumstances. This is a new podcast, so if you like it, I hope you'll consider subscribing and joining us for some of the incredible episodes We have coming up. Now, here's my conversation with Roelof Botha. This episode is brought to you by Brex. Fred Adler, the influential venture capitalist of the 1970s, was known for displaying decorative pillows in his office that featured a signature business philosophy: corporate happiness is positive cash flow. In today's post-SERP environment, Adler's wisdom feels particularly relevant. As founders need to make every dollar work harder. That's exactly what Brex delivers. Their modern finance platform was built specifically for startups like yours and designed to help extend your runway when capital efficiency matters most. With Brex, you get global corporate cards with up to 20x higher credit limits and no personal guarantee required. Their banking solution has no minimums and no transaction fees. While letting you earn high yield from day one with same-day liquidity. Best of all, Brex knows you were born to build, not juggle spreadsheets and finance tools. Their AI-powered platform brings cards, banking, expense management, and travel all in one place. It's simple, scalable, and designed to get you back to what you do best: building. More than 30,000 companies including 1 in 3 US venture-backed startups, trust Brex to help make every dollar count toward their mission. Join them at brex.com/mario. This episode is brought to you by WorkOS. What do companies like OpenAI, Cursor, Perplexity, Webflow, Plaid, and Vercel all have in common? They use WorkOS to power enterprise features like single sign-on, directory sync, and multi-factor authentication. WorkOS is set apart by its modern APIs and SDKs for seamless enterprise integrations. Plus, it's free to get started. Whether you're a scrappy startup or rapidly scaling, WorkOS has the solutions you need to secure enterprise deals. Future-proof your authentication stack with the identity layer best suited to meet the evolving demands of enterprise environments. Find out how at workos.com. Roelof, thank you so much for being here today. I've been looking forward to this conversation a huge amount. And as you know, this is a podcast about the future, but our discussion today is going to be a slightly different spin on it. Really the mindset it takes to anticipate the future, assess it with clear eyes when it arrives, and avoid some of the irrational exuberances that tend to crop up when, when bubbles do appear.

Challenging topic.

Yeah. You've lived through some of these cycles, of course, with PayPal and Sequoia and Sequoia, 5 decades plus of navigating these. So just to begin and level set a little bit, do you think we are currently in a bubble?

I don't think we're currently in a bubble. At least my definition of a bubble is something where you have widespread inflation of asset prices across every single category. And so when I think about, you know, at least the ones that I've lived through, you know, the dot-com era, largely fueled through monetary policy because of the concerns of Y2K. It seems like a distant memory, but that was actually a lot of what fueled it. The financial crisis, what we experienced during COVID you, you know, you experienced very low interest rates and it really propelled all asset prices. I don't think that's the case right now. US real estate, both residential and commercial, is candidly still very soft. We have an internal tracker here at Sequoia. We send it out every Monday as a reminder to be rational and level-headed as we look at late-stage private companies. There's about 690 public tech companies that we include in this basket. And we look at the current median multiple, enterprise value to revenue multiple of this entire basket of companies. And right now it's sitting at the 60th percentile of the last 2 decades. So when you look at that in aggregate, I just, I think it's hard to argue that in general, we're facing a bubble. And I think the question that maybe the next term comes to mind is, is there a bubble in AI? And I think, you know, that's one that I think is up for debate. But at least a lot of what we think about at Sequoia is we need to buy discounts to the future and we need to not be anchored and worried about paying premiums to the past. And so this is one of the very difficult psychological things that you have to overcome being an investor in technology because these companies can grow so, so quickly. And a company that you looked at 6 months ago is now raising money again at 3 times the valuation. And you wonder, I could have invested 6 months ago and I didn't, and I maybe should have, and now it's 3 times and I should just ignore it. But that's not the question. The question is not the premium. The question is, given what you think this company can become in the long run, is this a good entry price?

So many different threads that I'm excited to unpack that we're going to cover, I'm sure. But I can't help but think about this Monday tracker. And how you sort of use it to level set yourself, sort of understand, it's a little bit of a this is water reminder to yourself of this is where we're at, this is what we're looking for. What other indicators, if anything, is in that Monday tracker that sort of helps you stay sane?

Well, in addition to that particular tracker, we have a sheet that we hand out that summarizes all the investments we've made To date in the current fund that we're investing. And it's a useful way to just reflect on what is the quality of the companies we're assessing today? How does it measure up to the companies we've agreed to invest in? And admittedly, there are mistakes in there and there's some good decisions in there, but it's a useful mechanism because humans are very good relative decision makers. Now, I've read some interesting behavioral economics research on this where if I show you 3 different homes and 2 of them are Spanish and one of them is Tudor, probably pick the nicer of the 2 Spanish homes just because you have a comparison.

Okay.

If I showed you 1 Spanish and 2 Tudors, you might choose the nicer of the 2 Tudors. And so humans are just a little bit stuck in this relativism and how we make decisions. And so if you can widen the aperture of things that you put in that consideration set, I think it helps you make better decisions. Otherwise, you might just think about how good is this company relative to what else we're looking at today or what else we've seen in the last month. You step back, you look at a wider set, and it helps you really think about what quality means. Does this company have the potential to become a legendary company in the Sequoia language? You know, we've had the benefit, you know, since we've been around for over 50 years, the companies we backed when they were private today account for more than 30% of the total market value of the NASDAQ.

Yeah. I mean, that's just mind-boggling.

And so we really think about which companies have the potential to be legendary companies that can continue to compound and really make a difference in the world.

Do you think the speed at which legendary companies are being produced is increasing or decreasing or staying the same in the world of AI? Because on the one hand, we are seeing these companies rack up revenue and oftentimes much, much faster, but it also perhaps feels slightly more fragile or a little less defensible.

The rate at which companies grow into pretty rich valuations and big meaningful businesses is shorter than ever. I think AI is playing an important role in that. But if you take a step back, you've seen this as a consistent trend over the 50-plus years we've been in business. So I don't think it's a new phenomenon. It's a continuation of a trend that has been persistent. Now, if you want to unpack why that is, you know, when we first started off, the reason it's called Silicon Valley obviously is the origin of semiconductors. And the founder of Sequoia, Don Valentine, actually worked in the semiconductor industry. And his vision was to invest in companies that would benefit from this incredible rise of the semiconductor industry. And so if you look at the history of our investments, in the 1970s, it was a lot of semiconductors. By the 1980s, it became more what you'd call systems. We put together entire systems. So whether that was companies, we weren't an investor in Sun, but Sun Microsystems or Tandem Computer, those sort of companies. Then you ended up with enterprise software like Oracle. Later on, we started to connect all these systems and that led to the rise of companies like Cisco and the era of networking that led us to the 1990s where we ended up connecting the entire world with the internet. And then we had cloud, then we had mobile, and now we have AI. So we'll sort of speed through this evolution of 50 years. At every point, distribution has become easier than ever before. When we took PayPal public, there were about 300, 400 million people on the planet that had access to the internet. Smartphones didn't exist. And Korea and Japan were about the only countries in the world that had true broadband access. Most of the United States was on dial-up. And so that's a very, very different era. Today you have over 5 billion people connected to the internet. Most of them have access to mobile devices. So it's an arm's reach away to get access to a service. And you have all this data that is accumulated. And so when you put all those ingredients together, it is understandable that every successive generation has a quicker rise. And so the time to get to 100 million users or 100 million in revenue is much shorter today than it was back then.

It's not an aberration. It's an evolution.

Exactly. I think that's a great way of phrasing it. This is an evolution and it's making our business a lot more difficult, honestly, because you could take your time. You know, it might've taken 3, 4 years in the past for a company to get to $100 million in revenue. Now it can take 12 months. Part of the question is, do companies grow quickly and then reach the upper bound of their market potential? Because some companies, maybe the upper bound of their potential is $200 million, but they'll grow to $200 million very quickly and then the growth rate might stop. And then it wasn't worth paying a lot, but some of these companies obviously grow quickly to 100. And then before you know it, they're at a billion and they're building a really durable business. And the ability to understand and discriminate between these 2 use cases is very, very challenging for investors. And so I think that's made our job a lot harder.

And harder in the sense that part of the issue there is that because this happens so much faster, you just sort of have less time to actually understand how much durability there is or like why is that tangibly more difficult if it just plays out faster?

There are a couple of things that I think about. One is, what is your judgment of the ultimate market size potential of this particular category? And I'll give you an example. Maybe 10, 15 years ago, you saw the rise of flash sale sites, about 15 years ago, Gilt and Rue La La and companies like that. And they had a meteoric rise. Mobile phones already were prevalent. And so people would shop on these. And there was a judgment question about whether this would become mainstream. Could you imagine that 80% of Americans would be engaged in a flash sale every week?

Yes.

Or was it going to be an important category, but a smaller category? And it is impossible to tell in the early days because these growth curves are just spectacular. And then there's, if you think about S-curves, like logistic curves of where, you know, things tap out, it turned out in that case that flash sales didn't become mainstream. It's an important category. And so it was the right decision for us to not invest in those particular categories. But that's the judgment. What's the upper bound? Is this thing truly mainstream or not? So that's the first question that's difficult. The next one is because it's so, such a short-lived phenomenon, it's unclear whether you can prove sustainable competitive advantage. These categories are typically not undiscovered or unknown to others. And there is usually a few other competitors. And even if you have the early lead, it doesn't guarantee that you'll succeed long-term. Google wasn't the first search engine. And there are many other examples in history that the first mover advantage is often a disadvantage in technology. Often it's a second or a third mover that can spot some of the challenges that tripped up a first mover that enable them to do an end run. Facebook wasn't the first social network.

I

mean, these are two, you know, pretty notable examples.

Yes, canonical examples.

That weren't the first in their categories, and yet they ended up being victorious. And so there's this tricky judgment of whether or not this company can sustain its early lead and be the winner. So it's both a market size challenge and a competition challenge that makes the judgment very challenging.

Fascinating. Looping back to sort of this moment in AI, you sort of tweeted recently that we're repeating the mistakes of the past, and particularly you cited You know, the practice of managers starting an SPV, putting a tiny amount of capital themselves in, and then bringing in some tourists to join and really having very little skin in the game. Are these some of the signs to you that, you know, maybe things are getting a little too hot or, you know, we're seeing too much of this bloatedness in AI, or is that really something that you're seeing across venture?

It's particular to AI. Where there's a tremendous amount of enthusiasm. And again, my definition of a bubble is it has to be pretty broad-based. In every era of technology investing, there are individual companies that are overpriced and that don't end up living up to the hype. So that's one challenge. The other one is, you know, even when there are good investments, I worry that that investment dynamic ends up muddying the water. Maybe part of that experience is, you know, born from my own firsthand experience at PayPal where When we had a limited runway left, when we had 7 months of runway left, it really forced us to get religion, so to speak, and to focus on a bunch of innovations that ended up defining the company's success because it was born out of necessity. And so I sometimes worry that if fundraising is very easy and companies have excess capital for what they need, you know, that discipline doesn't enable innovation because it's so easy to just hire more people or cope with not having great gross margins, or maybe your sales and marketing efficiency isn't quite good enough yet, but it doesn't matter. You've got such a big balance sheet. You'll just, you know, it's growth at all costs. And I don't know if that's the best ingredient for building the healthiest business long-term.

How often do you see a company raise what feels like too much and the founder actually is able to retain that sense of discipline? This is very top of mind for me because I've talked to a few founders recently where they've sort of talked about, you know, Actually, things are going great. I could pull forward a round or 2. I'm sort of weighing it up. And often, you know, we'll have a discussion like this and their perspective is, well, I'm, I'm not going to fall into that trap. Like, I know that I'm going to keep the discipline and keep it tight and make hard trade-offs. Is that something that like really you do see it change depending on the manager in a radical way? Or is it just that we are human and so, uh, you know, can, can find ourselves buffeted by these circumstances more than we might imagine.

For better or worse, I think we're human. And there's a reason Kahneman won the Nobel Prize for his seminal work in this field. It turns out we're not really irrational. I think that the fact that we're not fully rational, sort of clinical decision makers doesn't mean we're irrational. It just means that we're human and we have sort of these other innate reasons why we do things. The founders that I've seen who are able to maintain discipline even when their cash balances are very high are those who have often had a scarring experience. So when I think about a Brian Chesky, you know, we were a seed investor in Airbnb. My partner Alfred is still on the board of the company, you know, spectacular business. And the company had a near-death moment in early 2020 during COVID And that was really challenging. And I think Brian has lived through that valley. And I think he's learned from that. And I doubt he would fall prey to this sort of temptation in the future, given what he's lived through. But honestly, unless it's a lived experience, I think it's very hard for people to restrain themselves given excess capital.

That is, it is something that is so hard to impart to someone. You know, I can't remember. I think it was Bismarck who, you know, has a great quote about only fools learn from experience. You know, a wise man learns from the mistakes of the past, but it is so hard to actually feel it in a real way unless you have lived it.

That's difficult, honestly. I mean, and look, I was guilty of that too. I was part of this, you know, the same PayPal management team that is often praised for what they were able to accomplish. That same team in March, April, May, June 2000, we were spending money like drunken sailors. Now, our burn rate peaked at $14 million a month in June of 2000. And then reality struck, the NASDAQ had crashed. It was clear that we would not be able to raise money again, given how the environment had changed. And that same team that was so prodigal suddenly was able to figure out a lot of the key ingredients that made the company successful. So it's not a commentary on the quality of the people or that they're inherently good or bad. It's just, you know, these environmental constraints or freedoms often define our behavior. Now, a lot of the advice we get now in the case of PayPal, Michael Moritz was on our board and he was a spectacular board member. And I remember him showing up at these board meetings in Q2 2000 when the NASDAQ was starting its slide. And Michael kept on asking us, what is your runway? And he really got us to focus on our cash position and face the reality that we were not going to be able to raise more money to, uh, to buy our way out of it. We had to innovate, figure out a business model, drive down our costs. And that perspective, that 10,000-foot perspective from a board member who had seen previous cycles was invaluable to helping us realize it sooner because we could easily, left to our own devices, have spent another 3 or 4 months, at which point it would've been too late. And so he gave that perspective. And so I think that's a lot of the work we do at Sequoia is we draw on this 50 years of experience. We work as a team at Sequoia. Our phrase is that when you get one of us, you get all of us. And so we discuss these challenges that partner meetings, we discuss it at our portfolio reviews. We'll sometimes have another partner join a meeting with another partner at a company where they're on the board just to help bring perspective because we want to be able to pay it forward to a next generation so we can learn from some of those mistakes. And that's part of why we wrote the Black Swan memo just as COVID hit. We did an Adapting to Endure session in, uh, this was in May 2022 when the market was just starting to slide. And I don't think people quite woke up to the reality of what was going to happen. In, you know, in the next year or two. And we very quickly rallied our portfolio companies because we collectively could see a pattern that others may not recognize. And a lot of our founders, you know, we thought of this idea on a Thursday. We worked the entire weekend to pull together the presentation. And at Monday, I think it was at 7 AM, we gathered the call with our founders and we had, you know, over 150 of our founders show up for this call, the Zoom meeting. And we shared this knowledge because we wanted them to benefit from this collective insight. And many of them were able to make important changes in light of that. So I think that's part of the role we play as an advisor and board member and thought partner to our founders.

Yes. We talk about the importance of these lived episodes and PayPal obviously going through that valley of despair and the world sort of, I think you've talked before about the press sort of poking fun at PayPal during that period, Earth to Palo Alto headlines and this sort of thing. If there was a a rather discrete experience that you could give to entrepreneurs or new managers to live in some virtual reality world that could really simulate it, what would be the experience that you lived that you think would really hammer home those lessons to someone?

I think for me it was this June of 2000 when we weren't yet generating revenue, the burn rate peaked. We realized that Online fraudsters were starting to steal millions of dollars from us. We were, you know, it was a little bit under the radar and we haven't quite realized it. And we woke up to that reality. You know, when you sit there, I just graduated from Stanford Business School. I was on a student visa. I had a year to work in America. So from my point of view, this is my one chance maybe to make, you know, make good on this promise of the American dream. And I'm sitting at the company and we have 7 months of runway. And it was scary. And, you know, when I think about the innovations we made, we figured out how to redirect payments to ACH. We fixed all the fraud challenges. We refined our revenue model at that point. And we went from burning a lot of money. We generated $15 million in revenue that year. We generated $105 million in revenue in 2001 and then $240 million the year thereafter. So when you think about that as a trajectory, But it really required us to rally. And so, I don't know. So if I had to think about the lesson, I sometimes encourage founders to think about, you know, what would you do if you only had 12 months of runway left? What decisions would you make?

That's clarifying.

It's really clarifying. And there's a, you know, something we put in our own investment memos at Sequoia, which is the pre-mortem and the pre-parade. And this idea that, you know, at the outset, dream for a second if everything goes right in the pre-parade. Why should we Imagine that this company could yield a 10x or 100x return for us. And then the pre-mortem really helps you focus on the key challenges that the company has to overcome. And there's a version of that that the management team themselves needs to conduct, which is forget about the fact that you have 3 years of runway. You only had 12 months left. What would you do? It is really clarifying to focus the mind.

That's an incredible exercise. You talked a moment ago about Daniel Kahneman, and it strikes me that you are Really, and have been for a long time, a student of decision-making, of cognitive biases, of people like Kahneman and Tversky and so on. When did that interest start for you? Was that something that, you know, back in the actuarial days piqued your interest, or was it really something that you honed once you began your career in venture capital in earnest?

I think it's a mix of a bunch of those. So my dad's a professor, or was a professor of economics. He's retired now. So I think I got a little bit of a window into that. Through him. I loved my economics classes when I was an undergraduate studying actuarial science. Interestingly, to study actuarial science, you generally design life insurance products, pension fund products that live for very long periods. You might issue a life insurance policy for the next 30 years that somebody is going to be alive, or you're designing a pension plan for somebody who's age 25 today who needs a retirement income in 40 years. And my actuarial science professor always talked about how Actuaries are trained to think decades into the future and accountants are trained to think one year in arrears.

Wow.

And I think there's something about thinking very long-term that he implanted and it was part of the actuarial training, which really suited me well to what is one of Sequoia's unique advantages, which is thinking long-term. And I think that's part of how you overcome some of these biases is you change the time dimension over which you consider things. You expand the time span of discretion and it helps you see through some of those traps. Then I'd say when I was at Stanford Business School, there were some amazing classes that I took and just amazing professors who exposed my mind to some of this thinking. We did a class in organizational behavior in particular that I think really opened my eye to heuristics, as it's affectionately called.

Yes.

Heuristics and biases. And then I started to read a bunch of books about that. There's a book by Dan Heath, who's a professor at Stanford. I actually invited him to one of the Sequoia offsites. And he helped us analyze some of our historical decisions in small teams in a way that there's no finger-pointing. It's just, what did we get wrong in this decision? And then analyze it and what psychological traps did we fall into? And the challenge is we will all continue to fall into these traps. Even if I've studied it, it doesn't make me immune from them. But as a team, if we're well-versed in understanding it, you can actually name them. And recently we've introduced it in some of our investment memos. One of my partners, Pat Grady, had this idea that we think about the biases that may be at play from the person who's trying to sponsor an investment and that they name those biases and actually just put them in the investment memo. You know, I might've gone native on this particular investment. I have not made an investment in 6 months and maybe, you know, am I trying to lean too far forward just because I feel I need to Make a new investment, whatever you think your bias is of the moment, and you write it down and you name them. And when you name them, it disarms them. Then you can talk about them, you know, remove a step removed. And we as a team collectively can minimize our collective biases.

Incredible. Yeah, you're taking it and you're sort of extracting it from the person enough that they can actually start to look at it a bit themselves and say, ah, you know, that actually is maybe what's happening here. I mean, that brings up so many interesting questions to me, one of which is, Do you notice that you tend towards any particular biases or as an organization, do you find actually, you know, when this sort of dynamic is at play, we actually need to be extra careful, for example?

It's an interesting question. Unfortunately, we keep on discovering new ones. So I wish we could say there are well-trodden ones. Maybe that's a good lesson actually. Sometimes it's, you know, it's okay to make new mistakes. You know, repeating mistakes isn't great. I think the 2 that really tug at human nature in this business. At one level, there's anchoring and adjustment, and it gets to this notion that I talked about earlier, where we need to buy discounts to the future and not be concerned about premiums to the past. And it's very, very difficult. It's very difficult. We, you know, we deal with it in the venture team where we looked at a seed opportunity and then the venture opportunity comes by 3, 6 months later and, and you regret not making that seed investment, but now the price is so much higher. Uh, we deal with it from venture to growth. We deal with it within our growth business. And so that to me is a very difficult one to fight, this anchoring and adjustment bias. The other one I think we struggle with is loss aversion. You know, so the prospect theory, which was one of the key innovations from Kahneman and Tversky, dealt with this fact that most of us are risk averse in the domain of gains and we're risk seeking in the domain of losses. And the concept basically is if you're down, you'll often double down in the hope that you'll make up the losses.

Yes.

But the loss aversion in the domain of gains is just as dangerous. Because it means that when you're up, you might just cash in your winnings. And when we have this ability to invest in companies that just keep going, it's very, very difficult to accept that. You know, the fund's already in a good position. This is already a very nice return. Why don't we just, you know, bank our winnings, so to speak? And that to me is the equivalent of, you know, getting to the finals, but not striving for gold or maybe even striving for a record. So, That's part of the reason we instituted and created the Sequoia Capital Fund, which we launched about 3 years ago, which systematically gives us an opportunity to continue to hold on to shares of companies where we were early investors, where we believe there's long-term compounding potential. And we bifurcate the ability for some people who do want to sell for liquidity reasons to take some of their shares. But by and large, we're able to hold on to some of these spectacular winners for many more years.

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Yes. I'll give you a concrete example with Jack Dorsey. So when he started to build Square, now called Block, at the time that I first met him, it was called Squirrel, by the way.

Oh, wow. I don't think I knew that.

That was the original name of Square when it was a seed opportunity. So it was about 6 or 7 people that were working out of an apartment. It was on Mint Plaza in San Francisco. just off Market Street. And I went to visit him in the apartment. I'd met him when he was building Twitter. Because of my PayPal and financial services experience, I was really enamored with this idea of mobile payments and what it could be. And I went to meet him and I really loved what the company was building. And he gave me a prototype of the original Square dongle back when mobile phones had audio jacks. Truly crazy to think about. To think about it, they turned it into audio waves and the application that they built on the phone would interpret those audio waves to understand what that magnetic code was to enable you to authorize the transaction. And he gave me the prototype. I remember coming to the Sequoia office and I was like a child who just received a birthday gift or something. I was running around the office. I was showing all my partners this. I would ask them for the credit cards and I would do a demonstration and charge them $5.

Yeah, then ran off.

And then ran off. Now I gave the money back, but I was so giddy about this company. And then as we had to make a final investment decision, The valuation was a little high for what I thought was a pre-launch company. They didn't have demonstrated product market fit, even though I instinctively loved the company. I struggled with making that investment and it ended up, they raised money at a roughly $50 million valuation, pre-launch, 9 months before launch. Then they launched the product in, I think it was August, September 2010. And I started to see that the product was taking off. One of my PayPal friends, former PayPal friends was at the company, told me that things were going well. And I reconnected with Jack. And the opportunity was very different because at this point the company had a product that was hitting the market and there was a clear inflection. And Square then at the time raised at a valuation of over $200 million valuation. It was, I think, $220 million post-money, something like that. So you're paying a price that's more than 4 times the price you could have paid 9 months ago. Is that the right decision? Sequoia is not in the business of investing at the time. We didn't think so. Way should be making investments of a $15 million investment at that kind of price in our venture fund. It broke convention for us to do so. And so I asked for forgiveness from the rest of my team. And I really strongly advocated that we should make this investment. And I really swallowed my pride because I was the person who didn't have the guts 9 months earlier to make a better investment at a lower price. And that's the kind of anchoring and adjustment. Now I've given you an example where I overcame it. This was 7 years into my career as an investor at Sequoia, almost 8 years. And I struggled with that a lot earlier in my career. And some of my biggest regrets is when I struggled with this anchoring and adjustment phenomenon earlier in my career.

What did you miss because of that phenomenon? If anything comes to mind.

Twitter, same company, well, same founder.

Jack really did a number on you somehow.

There are other ones. I'm just giving you one. Don't worry. There's a long list of failures that I can unfold for you. If time permits. Um, no, we listened to Twitter at the Series A and, uh, we had an opportunity to invest $2 million at, I think, a $20 million valuation, which in retrospect would have been a spectacular investment. This was 2007. iPhone hadn't launched.

Different valuation framing in that era, for one thing.

Completely different valuation framing. It was, but keep in mind, this is before mobile phones had launched. I mean, my signup date on Twitter is 2007. It was an SMS service only. There was no app. And so you'd get SMS messages from your friends saying, you know, I'm at the coffee shop or whatever. I mean, it wasn't as compelling a product by any stretch as it became. And they had a struggling business model because they had to pay for termination charges of all these SMS messages, especially in international markets. I remember Italy in particular was a very expensive market for them because it gained adoption and there was no business model, but they had to pay all the carriers for terminating these SMS messages. So we said no. And maybe when I think ex ante, it was probably the right decision. Ex post, clearly it was the wrong decision, but I'm not sure with the same fact pattern, if you had 10 of those types of opportunities, my suspicion is the consistent answer would have been to not invest under those circumstances. The struggle then was when the company raised money a couple of years later, the Arab Spring had happened and Twitter had clearly become a successful company. And this was In particular, the investment that happened in early 2009 was also at around a $200-ish, $250 million valuation range. But at this point, the company had proven product-market fit. Smartphones had launched, the App Store had launched, and it was a very different product. And I think there was a sense in, we're not going to do this again. We're not going to look at Twitter again. We already looked at it before. It's a much higher price now. Let's just move on to the next Series A and not make the Series B or Series C investment. And that was a terrible mistake. That was an absolutely terrible mistake. And I think the way that that was seared into my experience enabled me or helped me correct that with the Square decision, which happened roughly 2 years later. Wow.

You mentioned a little bit earlier when we were talking about some of the cognitive biases and influences at play, the concept of uh, timespan of discretion, which was, uh, an idea that I actually had never heard of

before, but I came across it, uh, in doing some research and your, your partner Alfred has written about it. And, you know, it sort of stems from this research by, uh, a social scientist, Elia Juck, who studied a corporation and saw that, you know, different people along the chain basically had different time spans in their life, the, uh, or in their minds. The, you know, workers on the factory floor were maybe thinking hour to hour, the management year to year. And so on and so forth. For, for you as a venture investor and also now, you know, in your leadership role at Sequoia, what are the right time spans to actually think in? Like, is it right to think about it on a fund length cycle, longer, shorter?

In general, I'd say our time span has to be much, much longer. And it, there's some nuances to the particular question you're wrestling with of whether it's, whether you're thinking decades or whether you're thinking years, but those candidly define the range. It's not quarters and it's not days. When we think about Sequoia itself, my title is that of steward because my role is to put Sequoia in a better place than I found it. I need to make sure that Sequoia is in a great place for the next generation. that manages Sequoia in the same way that Don Valentine didn't call it Valentine Ventures, enabled the next generation who in turn enabled the next generation. That is the obligation that I have and future leaders will have to make sure that we're a great partnership for the long run. And what that means is we need to be the first choice for outlier founders who want to build exceptional businesses. And we want to serve our limited partners. who we define as largely being great causes, foundations, endowments, and nonprofits. The privilege you have of working at Sequoia is you work with entrepreneurs who change the world on the for-profit side, and the returns we generate primarily go to helping nonprofits do incredible work to solve some of the areas where the market system fails because it doesn't cover all contingencies. It doesn't always deal with poverty or basic medical research or education. And so we're proud that these are the sort of people whose money we manage. We don't invest to help the rich get richer. It's just not in our wiring. And that was something that Don Valentine imprinted on us very early. So I'd say when we make many of our decisions, we have this very long-term timeframe that we think about at Sequoia. That has enabled us in my mind to be distinctive in how we think about investments. Because again, we think very long-term. We don't worry about whether or not the company can go public in 3 years, 5 years, 10 years. It's part of why we set up the Koya Capital Fund, we have a truly strong and differentiated advantage of thinking very long-term. It translates to how we then work with our companies. The reason several of our partners are still on the boards of public companies where we don't have the right to be on the board is because the founders and the management team want us on the board. And part of why they tell us they want us on the board is we bring this very long-term perspective. To public company boardrooms that are often tempted to focus on the next quarter. Are we going to make the earnings the next quarter? What are the results for the year? But maybe the more important question to ask is, are we putting in place the right strategy to really become an even better business in 5 years or 10 years' time? And so I think that is really what distinguishes us. Now, there's a temptation where you live completely in the long run and you don't have a sense of urgency. And I've got to tell you, that's something that we don't suffer from. So these are, you know, the pace we have at Sequoia is absolutely relentless. You know, we work feverishly. Our team is incredibly committed and relentless in the pursuit of an opportunity. Several times this year, I've taken company meetings on weekends or, you know, it's late night conversations with founders or we have 4 days within which we make a very important investment decision and we just rally. You drop the ball, you maybe miss a family dinner, you maybe miss that personal appointment that you'd looked forward to because this is what we do. We're totally committed to it. So thinking long-term in my mind is not in contrast or is not in tension with also having an incredible sense of urgency every single day.

How do you inculcate that mindset in the rest of the team and, and, you know, keep the maybe not underdog mentality, or maybe that is the right way to frame it, but the, the real feeling that you are only as good as your next deal when you're at an organization that has been, you know, at the top of this game for a really long time. In many ways, you would expect some level of motivation decay or urgency decay.

No, that's the risk. One of the phrases I've used in some of our all-hands meetings is Nothing wilts as fast as laurels that have been rested on. We published a book 2 years ago called Lingua Franca, and Lingua Franca is sort of your internal language, you know, your nomenclature. And the book captures a lot of the phrases and wording we choose at Sequoia. So for example, we don't use the word deal because we're in the business of partnering with founders and becoming their business partners as they build their companies. It's, it's, we don't do deals at Sequoia. So this is just a small example. In the back of the book, in individual handwriting from every team member, we wrote, we are only as good as our next investment. And it's almost not quite like taking a blood oath where we all wrote this down and we assembled everybody's signature, you know, everybody's handwriting with this phrase. And we're completing a small remodel of our office. And in that new office in the kitchen, There'll be a wall with everybody's handwriting that says, we are only as good as our next investment. And so we live that, we recruit for that. So the sort of person who joins Sequoia has that kind of drive. I don't think it's always the easiest place to work, to be honest. I think the joy we take comes from winning, not from being happy per se. Happiness is a derivative of success. And winning and being relentless about that. So that's how we find the people who work at Sequoia. It's part of how we think about internal culture and the reward mechanisms, the review process, and the promotion process.

I'm always fascinated by these little but big ways that companies create this sort of winning culture for such an extended period of time. And I know that your partner, Michael Moritz, has written about Manchester United and Sir Alex Ferguson and has talked about how when people ask him, you know, why haven't you written about a book about Sequoia? He is like, well, I, I actually sort of did. Um, it just happens to be in the lens of this football club that was so good for so long. Um, and yeah, those sort of cultural habits and, uh, yeah, practices are, are so important in, in inculcating it. So it's super interesting to hear how you've done that.

Just interrupt for a second. So, so my dad is a Manchester United fan.

Oh, I'm so sorry for him.

His sons are also Manchester United fans and none of us have ever been to Manchester, which is kind of strange. And the reason is my grandfather was ambassador to Germany, obviously long before I was born. My dad was a young boy at the time and that's when the team died in the Munich—

Air disaster. Yeah. Wow.

And so for no reason other than sympathy, my dad, a South African kid living in Germany with my grandfather as ambassador, chose the Manchester United team because he felt sorry for them. And so through accident of history, our family became Manchester United fans. And so anyway, so I felt some of the pain of the team having lost some of that. And getting back to this point about thinking long-term, at least my superficial understanding of some of what's gone wrong was under the owners, the recent owners of the club, they didn't make long-term investment decisions. The facilities, the youth program, the way that they selected and brought up young talent, didn't enable them to think long-term and to thrive. It was sort of maximizing the value over a really myopic period. And that's part of why the team is in trouble now. And so I try to learn what I can from that lesson too for Sequoia in terms of what we need to do to continue to think really long-term.

Do you find sports teams and those sorts of institutions useful inspiration and useful guidance for Sequoia? Are there other teams that you've studied, I imagine from rugby perhaps, that you think, gosh, they have managed to be elite for so long. Maybe the All Blacks.

Maybe the who?

The All Blacks.

I'm a South African. No, I admire the All Blacks. They're a fantastic team. And I really do admire the All Blacks, even though it's painful to sometimes have them beat the Springboks. But I actually look at rugby more generally. And my Partners are sometimes, I think, a little bit frustrated because I'll, I'll show little YouTube clips at some of our team offsites and they don't quite understand all the rules, but I'm trying to elicit some of the learnings from rugby. And I actually think there's some really useful ones for us. Rugby has the most number of players on the field of any sport, any professional sport.

Is that right? Wow.

You have 15 from each team on the field.

I didn't realize that was the most.

Rugby has an incredible variety of body types. Because the nature of the play is, you know, soccer is relatively more similar.

Yes.

Rugby, you can have the 300-pound or 140-kilogram prop whose job is primarily to scrum, but they have to run for the rest of the match too. You have the scrum half, which is typically, you know, somebody who's 5'8 and relatively slight. You have the wing who's typically incredibly fast. You have the lock who's typically 6'6 or 6'7 and has to catch the ball in the lineout. And part of the value of that for me, for Sequoia, is we need to celebrate differences in skills that we bring to bear because our goal is to make great investment decisions and to help those companies flourish. And if we were all former VPs of engineering or we were all former CFOs, I don't know if that creates the right breadth of experiences to bring to bear to help us be successful. So I think about that aspect of rugby. Rugby is also a continuous game. It's not a stop-start game. So in football, by comparison, the quarterback determines many more of the play decisions. Rugby being an open and continuous game, you have many more players who have to make decisions. And so for me, our team every single day is out there meeting companies, making decisions, serving on boards, and there's a far more distributed set of decision makers on the team. So you don't have as much authority or control vested in a particular role or the captain or the coach as you might have in other sports. So for me, there's some really fascinating things to learn about rugby. The last one I'd mention, which to me is super important. In rugby, no one really cares who scored the tries. The only thing that matters is whether or not your team won.

That's really interesting.

And for me at Sequoia, we have something similar, which is we want to have exceptional individualism and we want teamwork. It's both. It's an and, it's not an or. So in the same way in the rugby team, you need to shine in your individual role and play brilliantly, but what matters is the team's victory. And so if that means that I found an investment that you end up leading and that somebody ends up helping you make that into a successful investment, that's fantastic.

This is pure curiosity, but what position did you play in rugby?

When I was in South Africa growing up, I played in the forwards. I played lock and loose forward. And then when I played for Stanford Business School, when I came to the United States, we had a surplus of loose forwards and not as many people who grew up playing the game. So I played scrum half. Because I had a decent pass and I had a decent kick and I'm 6'2. So it served as an interesting intimidation factor because we meet the opposing team, that position is normally somebody who's 6 inches shorter. And so when they'd see me, they'd wonder, you know, what is the size of the rest of the team?

Yeah, wait till you see the other guys come out.

It was a fun experience to play.

We've talked a little bit, you mentioned how important outlier founders are to this equation at Sequoia. Obviously it's central. Have you noticed any changes in the founder archetypes that succeed in this new world of AI versus some of those in the past? Like, has that part of the game changed at all?

Largely the archetype of founder today is the same as it's ever been for the most part. And the reason I say that is at the end of the day, I look for founder problem fit, even more than founder market fit. I try to understand what is the problem that this person encountered that uniquely enables them to go and address this particular And so, one of the companies I've worked with for a long time is called Natera, which is a public company now, about $2 billion in revenue. The founder and I met in high school in South Africa by pure chance. He came to Stanford, he studied physics and electrical engineering, and was working on satellite signal processing. And his sister had a child that died within a week of birth in 2002 from a genetic condition that was undetected during her pregnancy. And that really shook his life. And the founder, Matt Rabinowitz, is absolutely brilliant. He went back to Stanford, he was an associate professor, and he went and studied everything he could about biology and genetics to get smart about that. And he started this company with a mission of helping people to have healthy babies. And today this company is responsible for testing half the pregnancies in America to give couples comfort of mind, peace of mind that they're You know, unborn child is healthy. And they've since branched out into doing oncology testing. They do organ transplant rejection testing. It's just, it's an unbelievably beautiful company in terms of how it serves society and how it really changes people's lives. When you go to the company's office, you have all these photographs that people have sent in of them with their babies, for example, just thanking the company for doing what they do. In that case, Matt encountered a problem that motivated him to go and solve the problem. You know, Eric Yuan at Zoom, he was at Webex. He saw that the technology hadn't kept up with what was possible at the time, and that inspired him to go and start Zoom. He had firsthand knowledge of this particular problem space. And so, so many of our great investments follow this pattern where the founder sees that opportunity. So that the founders focus on solving the problems for their customers, truly being distinctive in the product that they deliver. These things are truisms. There's something which has changed, which is, and this again is a continuum over the last several decades, the level of abstraction because of the quality of underlying technologies enables a slightly higher level of sort of focus in the founding team. So when I was at PayPal, we literally had to build our own data centers. We had to buy servers. We had to have a team that would go and plug in networking gear. We had to do a deal with Equinix to find capacity for us to put our servers in and then negotiate for backhaul and things like that. And then the cloud emerged. And for a company like YouTube, you know, when I invested, they were really one of the first to take advantage of the beginnings of cloud computing. You didn't need that. And you also had the emergence of open source software by then that made it much easier for YouTube to use Memcache and MySQL and a bunch of other technologies. To enable them to scale very quickly. Fast forward to today, generative AI capabilities is making it possible for product managers and designers with far fewer engineers than might've been the case a decade ago to build really compelling services and applications. And so that's, I think, the piece which is changing, which is the toolset enables a slightly different flavor of entrepreneur to become proficient.

An entrepreneur who maybe is not as technically versed, can use these tools to sort of like get up and running enough.

Absolutely. And I'll give you a concrete example with Bret Taylor. We're an investor in Bret's company, Sierra, which is a spectacular company. You know, Bret is obviously a legend. He was a founder. He was the CTO of Facebook. He became co-CEO of salesforce.com after they'd bought his company Quip. And now he started this company Sierra. Now, he's a brilliant engineer, but a couple of months ago, maybe over the Christmas break, he decided to use what was then available in ChatGPT, and he's on the board of OpenAI, obviously has insights into what is possible, but he used the commercially available service from OpenAI, ChatGPT, and he recreated the early product that they shipped at Sierra on his own without writing a single line of code. What that required was clarity of thought, an ability to think as a product manager and be very clear with the requirements that you described, an ability to go back and forth with the chatbot in that situation to clarify misconceptions, but to be very precise in how you describe things. And he recreated what they'd initially built.

Wow. That is startling.

So, I mean, I'll be honest, when I heard that anecdote from my partner, Ravi, who's on the board of the company, I felt as though I was just a complete novice. I'd heard about prompt engineering and I sometimes wondered how much of that is real and is there real substance to that? And it's clear that if you are skilled, there is an incredible amount that you can get out of what is already available in these generative AI tools.

Given your work with Natera, I'm sure you have also spent a lot of time thinking about how AI and healthcare intersect. And I know you've talked about AI being a technology that maybe favors the incumbent more than the insurgents. I'm curious if you still feel that way. And 2, if that is the case, how does someone like Natera start to unlock a new step change in what they're able to do with AI?

The reason I said that AI may disproportionately favor incumbents over startups is that it doesn't fundamentally present a new distribution opportunity, a new channel of distribution. I think the internet and mobile were more disruptive for startups than maybe the cloud was. Now, maybe the cloud to some extent enabled self-serve software as a service companies to disrupt on-prem software companies. And maybe you can argue that self-serve nature was a little bit of a disruption to distribution, but for consumer products, The internet and mobile totally presented new distribution channels. And you could see a company that was successful at mobile completely usurp the company that was desktop bound. AI is not quite the same. I have no doubt that you're going to see spectacular companies built in AI because a fast mover who tailors the product to the needs of consumers distinctively may, you know, still benefit from the innovator's dilemma shackles that burden incumbents, but nimble incumbents have access to this tool, have an existing distribution footprint, have existing data that they could use to tailor these models to build distinctive services. So I think it sort of makes it easier for incumbents to withstand the onslaught of these, you know, wonderful companies that we back than may have been the case in another era. That said, obviously we're investing in companies that at a wonderful pace, and I love the wonderful investments we have right now. I just think we need to think about that distinction very critically. But in the case of Natera, we've started to use these large language models to incorporate health data with genetic data. And Matt, who had studied machine learning with his electrical engineering background and satellite signal processing and things like that, loves embracing this new technology. And we have a very strong team at the company under Steve Chapman's leadership, Exploiting some of these. So we've started to make use of AI to save expenses on the backend. So there's a tremendous amount of administrative overhead in the healthcare system in general, which I think is ripe for disruption with AI. So that's an area we've already deployed it, but then at the front end, actually helping us make better decisions for our patients or our customers. We're using these models to improve the quality of the algorithms that we use to make predictions about genetic disease outcomes, and we've started to use it in a way that may help us build therapeutics. Can you build personalized cancer vaccines, for example, by incorporating a person's genetic history with their health records, so the phenotype of what has been expressed, to come up with interesting insights? And that's a lot of what we're working on.

We've sort of touched on just how obviously transformative AI is, but also it's clearly a very strategic technology. How do you feel, given Sequoia's global scope, but it's obviously a US sort of based firm, how do you feel about the US's ability to lead in the AI race? Are you confident about our sort of primacy there? Is that something that we need to be thinking about more as a nation?

I think it's very important for us as a nation to think about the importance of staying ahead in the AI race. I think the US is in the lead. I'm confident the US can remain in the lead, but it's healthy to be paranoid. As was the phrase from Andy Grove, only the paranoid survive. So complacency would be the death knell of us. When I think about an ability to regain or retain the lead, there are a few ingredients. One is the people, the talent. The second one is resources. And the third one is what's the regulatory framework and rules of engagement that enable you to flourish or to not. And so when I think about those 3 ingredients, the US is incredibly well-placed. We have the highest density of talent in this field, candidly, partly because we've had immigration of incredibly skilled labor. I think 40% of the founders that we've backed historically were first-generation immigrants. It's a huge part of success in American entrepreneurialism, by the way, is first-generation immigrants. When you look at the scientific research that's published in the United States in and around AI, My guess is half the names are foreign-born.

Yes. Yes. And often China-educated initially.

Often China-educated. And so I think it's important for us to continue to be welcoming of immigrants. I'm an immigrant to America, so I believe strongly in the value of being open to immigration as a way for us to continue our advantage. So that's an important part is the US has the talent. Again, we shouldn't be complacent. We should make sure we continue to attract talent. And we're welcoming to talent. And I love some of the ideas that, you know, sort of staple a green card to every CS PhD in America might be a really good idea. The second one is resources. So obviously, you know, the US has been the home of this innovation in GPUs and all the other infrastructure that you need. When you think about the footprint we have in America with data center capacity, with the right types of chipsets and the right data, I think we have an incredible advantage from a resource point of view. And then the third one is, what is the framework, the regulatory framework that enables you to flourish? And the US in general, the reason the US has a much higher per capita GDP than most of the countries in Europe, I mean, there's a stunning statistic actually that there's only one country in Europe that has a higher per capita GDP than the poorest state in America, which is Mississippi.

Wow.

Germany has a higher per capita GDP than Mississippi. No other country in Europe. is a higher per capita GDP than Mississippi. And this is because the US has built a really good system to encourage economic prosperity, protection of property rights, an efficient bankruptcy process through Chapter 7 or Chapter 11, this creative destruction idea that Joseph Schumpeter is renowned for. There's just so many of these dynamics, a flexible and mobile labor market. All of these ingredients go into the kind of dynamism that makes America so successful. And then we have a benign regulatory framework for AI at the moment. So those 3 ingredients in my mind put the US at an advantage. Europe has fantastic talent. I think they have access to the resources. I worry that their regulatory environment may just slightly hamstring them from strictly regulating AI and making labor mobility more difficult. And then I think in China over the last decade, it's just not been as welcoming to tech entrepreneurship.

To put it mildly. Yeah.

The number of companies founded in China has actually dropped precipitously over the last 5 years. And so I know that there's been a lot of excitement about some of the recent advances in China, but I just still don't think they quite rival the U.S. in how dynamic and welcoming we are to this kind of innovation.

In my sort of slightly stalkerish forensic research for preparing for these conversations, I saw that you had been interested in a video that I think was posted on X. from the historian Niall Ferguson talking about how America is sort of faring in our debt payments to military spending ratio. As a former CFO and someone who pays very close attention to the numerical parts of these equations, curious what you thought of that and which parts of it factor into how you think about the markets today, the world today. and US technology.

So Niall Ferguson is a friend. I'll admit he's a Scotsman, but he has a soft place for South African rugby. And he and I actually went to a rugby match together in Paris last year during the World Cup, which was a lot of fun. And I've loved his books. I mean, he is a prolific economic historian and his books are an absolute delight. And it's always fun to listen to him and to hear how his brain works. And his insight around this, I thought it was fascinating. I mean, it was written up in the Wall Street Journal as well. So it's a pretty accessible synopsis of this insight that, as you pointed out, when debt payments exceed your defense spending, the country's in trouble. And to me, it's really symptomatic of overspending. You know, there's the opening phrase in The Tale of Two Cities that really deals with this idea that if you just spend slightly more than you earn, it's in misery. And if you spend a little bit less than you earn, you end up with prosperity. And unfortunately, the US has been borrowing from the future a little bit too much. You know, The federal budget over the last 4 years increased by 45% in America in 4 years. And I don't think anybody would argue that the federal government was a lean, mean fighting machine 4 years ago. So I think the US has some real challenges around efficiency and making sure that we, we're just more disciplined. We just cannot continue to have the level of government spending we do in this country and sustaining these debt levels. It'll eventually come home to roost. And there's a lot of history that points to that. And I don't think we can avoid these sort of basic principles of governance and economics. And so that does worry me. I'm not having grown up in America, I didn't belong to either political party. And so I focus a lot more on the policies that are being implemented and I realize what's happening right now. And in Washington, you know, is not always perfect. There are going to be good things and bad things that emanate. I do think the one thing that probably useful is for us to just trim down the federal government and to make it a lot more efficient and a lot more focused to serve taxpayers better than it does now. And so we don't end up running into a debt crisis.

Agreed. As Sequoia's steward, you have sort of seen an evolution of some of the things that the firm does, you know, introducing ARK as an early-stage program. You also talked about some of the public market investing You've done. Why were those initiatives so important to securing Sequoia's future and, you know, avoiding the, the pre-mortem that, that you might've sketched out at one point?

Well, it all starts with our mission, which is to partner with outlier founders from idea to IPO and beyond, and to help them build enduring businesses. And so when you unpack each of the elements of that phrase, from idea to IPO and beyond, So if we want to partner with you from the idea stage, we have to be with you as early as possible. And if we want to be beyond the IPO, you know, the beyond piece, that explains part of why we've built this Sequoia Capital Fund so we can continue to be in business with these exceptional founders. I always thought it was quite strange that the IPO is this expiration date of a venture investor's relationship with the companies. You know, you invested in the team when they were, when I helped us lead the investment in MongoDB, there were 12 people and the company had no revenue. And this was in 2010. And then the company goes public, I think in 2017 maybe. And then the relationship ends. I mean, the company went public at, I think, $24 a share. Today it trades at about $200 a share. So the company's increased. If you just think about it, about 90% of the company's appreciation happened after the IPO. And the company's had to build some really interesting products and deal with some interesting strategic challenges since the IPO. Isn't that part of what we're supposed to do in partnership with the founder? Anyway, so that to me is an example of why the beyond has made sense. And we created the Sequoia Capital Fund to not have the IPO as an expiration date, to capture some of the sustained appreciation for our LPs. So in the last 3 years since we launched the Sequoia Capital Fund, the gains in the fund over and above what we would have distributed those shares for to our LPs is North of $4 billion.

Wow.

Just the gains. So in the last 3 years, we've made an extra $4 billion for our LPs by holding onto these shares in the Sequoia Capital Fund.

So this is so interesting because I think one argument that someone could make about something like the Sequoia Capital Fund is, well, okay, once these companies go public, do you still have an edge in analyzing them? You know, maybe your edge is in the private markets and once they go public, you no longer have some asymmetric understanding or information, but it sounds to me like there is some sort of deep reality or understanding of the founder team or DNA of these companies that you can generate by partnering with them so early and seeing them for so long that really does stand you in good stead as a public market steward of capital. How do you think about that? Did you have to challenge, convince yourself of that in any way?

Yes, because there's another counterbalance to that, which is, are you too close to the company to take a step back and see some of the challenges and maybe understand the competitive dynamics? You know, are you too close to the management team that you, you know, drink your own Kool-Aid, so to speak? So there are, there is a tension there, uh, no doubt. But our history has shown, and the reason we created the fund is we just looked at the data. And the data was that we would have made a tremendous amount of money for our limited partners if we had been more patient in distributing shares in general. Now, admittedly, some of those companies didn't accrue a tremendous amount of additional value, but some did. And even if you just kept the entire basket of every single Sequoia IPO, you'd have been better off waiting than distributing when we did. And then the claim or the challenge for us is, can we actually do better? Can we discriminate and figure out which of these companies that truly have legendary potential that we might want to hold onto for another 5 or 10 years and let them compound? We were the original seed investor in NVIDIA. We were the first investor in Google. Today, one of the trillion-plus companies, right? But we made it, you know, we distributed those shares very early on. We received shares in Facebook from our sales of WhatsApp and Instagram. And in both cases, we were patient. We waited a while before we distributed those shares. But if we'd been, if we'd had a fund structure like this, maybe we'd have held those shares much longer and we could have accrued much more in gains. For our limited partners. So that's the spirit of it. Now, at the other end of the spectrum, we want to partner with founders as early as possible from idea stage. When my partner, Jim Goetz, helped us partner with Palo Alto Networks, it was Nir Zuk and him ideating and thinking about what the future of firewalls might look like, I think in 2004, uh, when we first met Palo Alto Networks. Uh, when we invested in Natera, there were 2 people. When we invested in YouTube, there were 3 people that actually moved into our office. You know, when we invested in Airbnb, there were the 3 founders. We have this history of partnering with founders very, very early. And there's so much joy in helping shape and build these companies from the earliest stages. And by the way, when I say build, the credit goes to the team that's inside the building. You know, and I understand that having been on the other side of the table, but I think we bring a tremendous amount of value and perspective as the business partner to these founders. So we have a seed fund that's dedicated to helping us find these early stage companies. We've always been in the seed business, but it used to be that we'd make seed investments in our venture fund. Now we have a dedicated seed fund, a dedicated venture fund, and a dedicated growth fund. We're also one of the first firms back in 2005 to really build a dedicated effort in around growth investing with a dedicated team so that it wasn't an afterthought for the venture team to make some growth investments. And they've been distinctive in the way that they've pursued that business. And so we have this ability to support you from idea stage all the way through. The ARC program we built was a way to bring company building expertise in a batch fashion to existing Sequoia companies. And that's a very important distinction. And the idea is that you can take, you know, half a dozen or 10 founders at very similar stages. And in 4 to 6 weeks, we can have them go through a program where we share some of this accumulated company building knowledge, really helping them see around corners. You know, instead of waiting until an incident occurs 3, 4, 9 months down the road where they have to deal with an interesting challenge, you know, give them some of the tools in advance so they can deal with that, you know, when the time comes. And it has the benefit of building community. We love having our founders build this network. I mean, Sequoia's biggest asset in my mind is this network and this community of founders we have, and they love helping each other. And so when they go through a community experience like this, they'll end up picking up the phone or sending each other emails and they didn't always ask us for help. They'll ask each other for help, which is fabulous.

Invaluable. Sequoia has been, I think, really forward-looking, uh, from, from what I can tell from the outside, at least in, in being very data-driven, using data to sort of improve decision-making, you know, spot trends or companies earlier. I think there was a, a program that you guys had for a while called Early Bird. I'm curious how AI has, has altered the sort of parameters of venture for you and, and how you you use it and might use it in a few years from now?

So we use AI. We actually have an engineering product design and data science team at Sequoia that's basically as big as our investment team. And that's an investment we made starting in 2019. And just to give you a quick sense, we had this offsite in 2019, the pre-parade, pre-mortem exercise we apply to ourselves. We actually asked every single member of the team to write up a full-page pre-mortem and pre-parade. And then we anonymized them and we circulated them and we read everybody's view on premortem and pre-parade. And the value of anonymizing it is that we want the triumph of ideas, not the triumph of seniority. I don't want people to think that my idea is the best just because I'm the one who wrote it. Maybe somebody else has the best idea. That's fantastic. I want us to win.

Yes.

And so we did that exercise. And one of the conclusions we had in this premortem, and literally we had this image that was the autopsy of Sequoia in 2030, what went wrong? Why, you know, why did we end up losing? One of the things amongst a few others was we didn't adequately invest in technology. And so we've endeavored to build a lot. I don't want to share too much publicly because it's a little bit of our secret sauce.

Yeah, that makes sense.

But we use technology very aggressively internally. And that's part of why the investment team we have today is the same size as it was a decade ago.

Wow, really? You're able to get that much leverage that you can really power these people up.

Yes. And Jess Lee, who runs that team, has done a phenomenal job building out that team for us, and she leads that effort. And she whimsically actually used superhero figures, an Iron Man picture with one of the partners' heads superimposed, you know, sort of say, my job is to turn you into a superhero by giving you these tools and capabilities to just totally propel our productivity. You know, that's the spirit with which we're building this technology. It's not building technology for its own sake. And so, you know, if you think about it, it's probably pretty easy to anticipate at the growth investing stage, there are usually some signals that you can pick up. You might be able to get credit card panel data to show you revenue momentum. You might look at employment momentum or job postings, the size of their sales team and the rate at which it's growing. You can look at references on G2 Crowd or things like that. There are signals that you can pick up that help show when these companies are growing. And that's obviously something that public investors in the hedge fund space have done tremendously. You know, know Netflix's, you know, subscriber numbers and revenue before they actually release earnings, you know, because that's how cleverly people are able to pick up these signals. There's a version of that in the growth business. In the venture stage, there aren't those sort of signals. It's about the people. And so then we have to think very creatively about the ways in which we pick up signals about people. And the networks, this wonderful network that we've built up historically, you know, so if you think about it, I might know somebody from PayPal days, certainly earlier in my career. And that was a very strong signal that if somebody from my network at PayPal left something and I knew how good they were, that was a valuable signal into whether that might be an opportunity for us to pursue. So that's the kind of spirit of things we're building on our venture stage. And then I'd say the last category is helping us think through how to interpret things that come in through the transom. And large language models have this fabulous ability to synthesize and summarize. And so, can you have AI augment your ability to look at a company's website or their presentation and help you tease out some of the key insights that you need, help you quickly surface the competitors for this category to help you quickly assess, is this worth an hour-long meeting or not? And that's the kind of way in which, again, we're using AI to propel our productivity.

You can also, I'm sure if you're not already using it this way, imagine it acting as your sort of Kahneman bot and dispassionately analyzing whatever biases might be at work as you, uh, as you, you know, write a memo or things like that.

That's interesting. Um, that's a really good idea.

Um, well,

uh, I'll incorporate that. Thank

you. I'm glad to contribute. Roelof, we love to end each episode with a few philosophical questions and So I'd love to ask you, if you had unlimited resources and no operational constraints, what is an experiment you would love to run?

So one of my favorite movies growing up was Groundhog Day. Maybe you're too young to have seen it.

Oh no, I've seen it.

You've seen Groundhog Day?

Of course.

So when I was younger and I was a student, my fantasy equivalent of Groundhog Day was that I could study every degree at the university where I went and that I could read every book that was in the I wish I could just learn all that stuff. And so when I think about where I sit today, the experiment that I'd want to run is I'd want to be able to meet every single company, listen to every single founder, think about my predictions of what works and what doesn't, and then see how I get it right and how I can get better at that decision-making. Because today I have the constraint that, you know, I only have so much time and we only get to see so many companies, but now I have this training set, my AI model of making decisions, which is the companies that I've seen historically at Sequoia. And I try to use that to help inform the decisions I make every single day. I wish I had an unlimited dataset of meeting every company and understanding all the industries that they serve and all the qualities of entrepreneurs and market dynamics that I get right and get wrong so I can get even better.

I love that. I always say that if given the choice to pick a superpower, I wish I could read every book just by touch. And I imagine sort of walking the library of my old college and just Yeah. For us, most of us—

Geraldine, leaving it under your pillow doesn't work. I tried that.

Yeah, unfortunately not. What's a tradition or practice from another culture or time period that you think we should adopt more widely?

There's a Japanese concept called kodawari. It means the relentless pursuit of excellence. And it was the theme of an offsite that we held in Japan a few years ago. And we resurfaced this theme when we had our limited partner meeting last year and sharing this idea of kodawari. And for me, it typifies how I think we should pursue our business at Sequoia. It's, you know, relentless pursuit of excellence. We want to write the best investment memos, have the sharpest insights, be the best prepared when we show up for board meetings or partner meetings. And the idea is that you take incredible pride in the work you do. And part of how you see it manifest in Japan is The people who clean the Shinkansen, the high-speed rail, are incredibly proud of the work they do. The person who's the sushi chef, and this is the, you know, I Dream of Jiro.

Yes, Jiro Dreams of Sushi.

Jiro Dreams of Sushi, just a relentless pursuit of excellence. He's invented some of his own equipment in this pursuit of the perfect sushi bite or the fruit that you might see in Japan where, you know, you might pay $100 for this melon, But they literally prune all the other fruits off the plant. So all the nutrients are packed into this one. They surround it with tin foil. So it has perfectly evenly distributed sunlight to help ripen the fruit. And it's just perfect. I wish we had more of this relentless pursuit of perfection.

That's a new word for me. I love that. Final question. If you had the power to assign a book to everyone on earth to read and understand, which book might you pick?

It's the book I do hand out to people. It's called Man's Search for Meaning. By Viktor Frankl.

A great one. Why does that one resonate so much with you?

So Frankl was a Holocaust survivor and the book doesn't detail the horrors of what he endured, but it really talks about the insight he had into human nature. And there are competing views of what motivates us. There's sort of a hedonistic view around, we pursue pleasure. There's Adler who thought that we pursue power and that's where we derive value and meaning for our lives. Frankl's view was something called logotherapy, which is purpose. And that purpose may be a mission, it could be a family member, it could be a pursuit, but there's something else that really keeps us going. And he had that insight before he went into the concentration camp, but it was honed by his experience there. And he saw, for example, that the death rate increased around Christmas and New Year. Not that any of the captives were Christian, but it was a remembrance of time with family. And many people lost hope in those windows and they basically would give up on life because they had no reason to live anymore. And he has this phrase that, you know, someone who has a why will bear almost any how. And so for me, when I think about your own personal life experience, you need to understand meaning. Because money is not going to bring you happiness. You know, it buys luxuries, but it's not going to bring you happiness. And so it's very important for people, I think, to define their personal happiness. And then when it comes to building a company, mission-driven companies just do better. And you can't staple a mission onto a company if it's inauthentic. It has to be truly authentic. And I gave you the example of Notera that Matt wants to help people have healthy babies originally. And what, you know, the company's now expanded, but it is such a mission-driven company. It defines the the kind of decisions that they make inside the company. It gives people comfort when they're pulling in all-nighters or doing incredibly hard work to remember the higher purpose that they're serving. It's part of how we think about it at Sequoia, where our purpose is to help budding entrepreneurs realize their dreams. Our job is to help them fully realize their potential by harnessing our collective experience. And the other part of our purpose is to help our limited partners do great things with the gains we generate from them, truly change people's lives in world. And when you put those together, it provides a very powerful mission to keep you going when times are rough. So Man's Search for Meaning is the book I recommend.

A great choice. And I can't thank you enough for your time today. I have learned a huge amount from your wisdom and stories and enjoyed it so much.

Thank you.

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