The Playbook: Lessons from 200+ Company Stories

All right, two episodes in a row from the hotel room. Let's do it. Let's do it. Welcome to this special episode of Acquired, the podcast about great technology companies and the stories and playbooks behind them. I'm Ben Gilbert, and I'm the co-founder and managing director of Seattle-based Pioneer Square Labs and our venture fund, PSL Ventures. And I'm David Rosenthal, and I am an angel investor based in San Francisco. And we are your hosts. This episode is something that David and I have been thinking about for a long time. Years, in fact.

It is called the Acquired Playbook, and it is basically what we've learned from doing Acquired. People often ask us the question, okay, cool, you guys have analyzed 200 companies and spent an ungodly amount of hours doing that. What are the takeaways? This episode is the takeaways. It was back in 2018, I want to say, that we had a major book publisher come to us and be like, hey, would you want to do a book on Acquired? And this was the idea we had, and then we were just like, maybe at some point.

Let's just keep doing episodes instead, but maybe at some point. So consider this the first draft. We don't know if this talk was good yet. We are in our hotel rooms at Capital Camp, and we are about to go on stage and give it. So this is sort of fun. This is the first time we've ever recorded one of these before doing the episode itself. All right, listeners, now is a great time to talk about a new partner of ours here on Acquired, Lagora, the agentic operating system that is redefining how the world's best legal teams work.

Yep. It's sort of obvious that AI is going to completely change the legal industry. I bet most of you listening have dropped a contract into some sort of AI chatbot out there. Lagora took that insight and asked the question, what if you really built something with that power from the ground up for the legal industry? So the founders did exactly what great founders do, operate with obsessive customer focus. They embedded inside a massive law firm for months. They sat with the lawyers just watching how the work really gets done.

And that's how you get features that customers love, like tabular review, where you drop in a folder of hundreds of contracts and it pulls every key term into a grid a lawyer can actually work with. Lagora's bet here is interesting. Since it lets each lawyer handle more complexity, any given person can increase the quality of their work and do higher value work. And this means that the pie can grow even as each individual task takes less time.

And they recently launched Lagora Agent, offering greater intelligence and performance. The agent lets lawyers set an objective. Then it can handle the planning and the execution and delivery of the final product. Legal teams get to maintain full control and transparency since they're still involved where judgment is required. And Lagora works where you already work. You can use it within Microsoft Word while redlining or drafting. The early Lagora numbers essentially speak for themselves. When they have a head-to-head pilot with their top competitor, they win 70% of the time. Lagora now has over 100,000 lawyers on the platform from 1,200 legal teams in 50 countries. And crazily, they went from 1 million to 100 million in ARR in about 18 months.

Truly insane numbers. And that is the real test. Plenty of things demo well, but the question is whether a busy associate actually reaches for it during crunch time or whether a partner trusts it before going into a conversation with a major client. If your legal team wants to check it out, whether you're a law firm or you're in-house at a company, you can learn more at lagora.com slash acquired and just tell them that Ben and David sent you. Now, as always, this is not financial advice. Please do your own research. David and I do lots of research, but you may come to different conclusions and we may have financial interests in the things that are discussed on this show.

Indeed. And speaking of different conclusions, this would be a fantastic episode to discuss in the acquired Slack. We want to hear what your favorite lessons are from all of these hundreds and hundreds of hours that we've done at this point. This would be awesome. So acquired.fm slash Slack, if you're not already a member, we hang out in there. It's a great, great, great community, as you will hear us talk about in this talk. All right, join the Slack. And then this is 12 of our favorite playbook themes, but there are certainly more. So I'd love to hear from you. All right, on to the talk.

So we thought we would be really clever here with our first one, both because this genuinely is one of our favorite themes. And we thought, hell, this will be counter-positioned. Everybody's going to talk about, you know, it's May 2022. There's doom and gloom. It's going to be good. And then, of course, great friend of the show, Anu Harharan, came up earlier tonight and already beat the optimism drum, but we will highlight it once again. So our first lesson from all of the stories we've told is that optimism always wins. So for folks here in the auditorium, raise your hand if you know who the people are who are on this slide. Wow, this is awesome. We're getting almost no hands raised. And for folks at home, bear with. I don't know that

we have a single hand up. Wow, this is awesome. Okay. So the person on the left is Akio Morita, and the person on the right is Masaru Ibuka. And they were the co-founders of the Sony Corporation. And we told this story in about three hours earlier this year on Acquired. It is amazing, but we thought it would be the perfect story to kick off the night because it's just so perfect for this moment. So as we said, there's not a lot of reasons looking out at the landscape at the markets right now to be an optimist. But the Sony story reminds us that things were much, much, much worse than they are today in the recent past. So Sony was founded in 1946 in Japan. And just think

about that time in 1946 in Japan. You think 2022 in America might be a bad time to start a company or a tough time to start a company. I don't know that in recent history, there has been a worse time and place to try and live your life and do any sort of business, let alone start a brand new innovative technology firm. Right. So these two men decided to start a company, which is crazy in and of itself in Japan in 1946. Even crazier, they decided to start a consumer electronics company.

Crazy for two reasons. One, after the war, there was no technology left in Japan. So like, what were they going to make? Their first product was a wooden rice cooker. There wasn't a market either, because every other technology firm that was making radios and stuff had pivoted to make stuff for the military, which was no longer a customer. Yes, no longer existed. The second reason why this was a completely, completely crazy idea was they were going to make consumer electronic, electronic consumer products. The GDP per capita in Japan in 1946 was $17, not $17,000. It was $17. So there was no market, there was no technology. And I think after the war, 48% of Tokyo was homeless. Like half the

population's homes had been destroyed. Yeah. Unbelievable. And so, and yet, despite all that, despite, I can't even imagine bigger headwinds against them. They built one of the most iconic companies in the world. It's not an understatement to say that these two men and Sony changed the course of Japanese history, changed the course of world history. And again, we talked about this on the episode, but Steve Jobs was, was mentioned earlier tonight. Akio Morita was the inspiration for Steve Jobs. And he actually did this great, great talk at one of, it was not a WWDC. An Apple. It was an Apple keynote after Morita passed away where he did a tribute to him. And I think, you know, no Morita, no Sony, no iPhone. And so the lesson that we take away from this is like, you know, even if things

are at their bleakest, it's rational to be an optimist. Because if you're not an optimist, it's, it's the optimists who drive the world forward. And then if you're an investor, investing in optimism is the only way that you're actually going to make outsized returns and build great companies. So it is genuinely the rational thing to do. All right. So point one here, lesson one, touchy feely kind of feel good. But let's back it up a little bit. So we all know Moore's law.

This next lesson, you know, we wanted to basically visualize and talk about this trend in a little bit of a different way than, than it's normally talked about. So the, the number of transistors on a chip, we all know this tends to double every 18 to 24 months. And with some quick compounding math, that means you get a 10 X every seven years or so. And as you can see on this graph that we made here, the X axis is time. The Y axis is the number of transistors on a leading consumer processor.

Notice that it's in log scale. You can see every seven years or so, 10 X improvement in processing power. And I figured we'd take the sort of greatest hits examples. Intel's 386, 486, Pentium 4, Core 2 Duo, which was in my first MacBook Pro, the A7 in the iPhone in 2013. And of course, the recent Apple M1. Of course, if you look at it in linear and not log scale, it looks like this. It's way too difficult to actually observe any progress. And it seems like basically nothing happened. And then everything happened. And this is the craziest thing about Moore's law and exponential scales.

The graph always looks like this. Right. In 10 years, the M1 is going to look like nothing happened between. And in 2000, with Pentium 4, it would have looked like this too. Yeah. It totally, every single step along the way felt like this, which is wild. And because of how exponential growth works, you basically feel like you're always at this crazy top and all this progress just happened. But normally, we don't look at charts like this when we're looking at processing power, or at least like processing generations, we're used to looking at it for high growth, durable technology companies, when we're looking at stuff like their market cap. So we aggregated that too. The first thing to note is that there's been a drawdown. I don't know if anyone noticed since I made these slides.

We made these slides a few months ago. But the point still holds. This is the market cap of all global technology companies over that same time period starting in 1975. Even if you normalize this for the tech bubble and today, you'll see that the outcomes of venture-backed technology companies keep getting larger generation by generation. It's also worth observing the exact same phenomenon that basically it seems like nothing happened, save for the tech bubble. And then suddenly everything happened at once.

And the insight is that this graph and the Moore's Law chart with the processors are actually the same thing. This is actually Moore's Law at work. And so we call this lesson the Mike Moritz corollary to Moore's Law. Because we didn't make it up, there's a great story that goes with it. Around the time that Mike Moritz and Doug Leone took over running Sequoia Capital from Don Valentine, Mike looked back on the performance of the past couple of Sequoia funds that had Cisco, Oracle, Apple, these unbelievable venture returns, never before seen venture returns.

And they were asking themselves, going, you know, my God, what have I gotten myself into? How are we ever going to top this? Which would be a reasonable and rational way to respond, looking at the greatest returns in history in an asset class and thinking, okay, well, where do we go from here? But he realized as long as Moore's Law continues to hold and computing power continues to get exponentially cheaper, the markets that technology can attack should keep getting bigger and bigger. So to put some more numbers behind this, in 1990, a PC with that 486 processor cost $2,000 and only about 42% of America, that's just of America, used a computer at all.

Which is, that's wild. Right? That recently. So today, a smartphone with, you know, literally a million times of the computing power costs $200, which is one-tenth the cost, and over 6 billion people have one. So of course, this trend led Sequoia to go on to invest in Google, WhatsApp, Airbnb, Meituan, ByteDance, global markets. But I think this is like, this insight that Mike had originally of like, oh, as long as Moore's Law holds, yeah, there'll be ups and downs in the market, like we've observed in the past year. But technology should always be able to access bigger and bigger and bigger markets if the cost of compute keeps declining. And it's played out.

And for those of you in the room who want to get like really pedantic, you have to sort of slightly adjust Moore's Law in order to say that it still holds. You've changed the definition a little bit. But when you look at like what NVIDIA has been doing with GPUs, it is totally fair to say that this 10x improvement in computing every five, six, seven years, that is absolutely still happening. And so therefore, the lessons you should take from it on the macro technology scale are to stay an optimist. Indeed, indeed. All right. So number three, we talk about Sequoia a lot on Acquired. They've been involved in so many great winners. They've built such a great, great franchise.

But lest you think that they are just pure geniuses, they can do no wrong. The lesson number three, which is cue the all in theme song here, let your winners ride. This comes from Sequoia's biggest mistake in history, which... Their biggest mistake in history in one of the most successful companies, if not the most successful company in history. Yes. And I think this is probably the single biggest mistake, period, in investing history. In investing history. Yeah. I don't see... I don't think there's any way that it can't be, definitionally. So let's go on to the next slide. Now, to be fair to Sequoia, they're playing on the stage where they could make a mistake that was the single biggest in history,

so they're doing something right. But so the story goes, one day in the late 1970s, I think it was 1977, Nolan Bushnell called up, who is the CEO of Atari, called up Don Valentine, his main venture investor. And Atari was actually the very first Sequoia Capital investment after Don started the firm. And he said, hey, I've got this young kid that's been working for me here at Atari. His name's Steve Jobs. And he started a company. And I think you should meet him. I think you should take a look at him. And Don talks about this in the way that only Don can. Says that Steve came in and he, quote, looked like Ho Chi Minh. And I think this was during the phase where he wasn't showering. So he smelled

really bad. But they funded him anyway. Don invested $150,000 in Apple Computer in 1977. And then, 18 months later, they had an opportunity to realize one of the greatest venture returns of all time. They made a 40X on that investment. They sold their shares for $6 million before the IPO. And they completely cleared out their position in Apple. And of course, we all know what happens since. And we, the next slide, we just for fun, we put on where our friends Ted and Todd over at Berkshire with Warren's approval started buying. And you have the hair beating the, or you have the tortoise certainly beating the hair on this one.

Tortoise beating the hair, indeed. And yeah, I think they did better than Sequoia did on this one. So, you know, because we use one gigantic global most successful technology company of all time to illustrate this, we figured we'd pick another example too, just to show it's not an isolated incident. So, Amazon IPO'd at $8 per share. And just for fun, I want to point out that subsequent run-up there in the dot-com bubble to $120 a share. Then, of course, that crash from the dot-com bubble.

So, 2001 to 2003 there, it looks like a pretty amazing buying opportunity. But actually, that's a ludicrous statement because every year for the next two decades was a great buying opportunity in this company. And so, what are we illustrating here? If you had held that Amazon IPO share for 13 years, you would have a nice 10x from the beginning of this graph to the end of this graph. But you really should have continued to hold. If you zoom out here, so you can see the little crosshairs there illustrate where the previous graph ended. Basically, any growth of the stock before 2012 just looks cute. And at that point in 2012, I think we all would have described Amazon as a mature company. It was almost 20 years old. If you had just held for another 10 years,

then instead of that 10x in 13 years, you could have had a 170x. And of course, the difference between those two on an absolute dollar basis, whatever you invested at IPO is incredibly meaningful. Incredible. And so, the key insight in this and letting your winners ride and when to let your winners ride and when not, it's not your growth rate in any given year that matters. Frankly, that doesn't matter at all. What matters is how many years of growth do you have left? That is the ultimate question. And in the case of Amazon, in the case of Apple, if you have decades of growth left, again, that's all that matters.

It leaves you in this interesting place where you're thinking, well, okay, do I always continue to hold? And this is why venture capitalists tend to be totally obsessed with market size. Because it's this idea that you basically need to be able to run forever or decades and decades and decades and continue to grow. And those markets continue to be this globally addressable, absolutely massive opportunity. Because the compounding, the funny thing about it is, all of the value tends to show up in the out years. And the trick is figuring out, like, okay, when am I in the out years?

Yep. And so, there's this great, like everything in startups, there's a great Paul Graham quote to go along with it. Of course, he remarked in December 2020 that an astonishing 99.98 of Amazon's growth had happened since IPO. And I just love this because I actually printed it out and I have it at home. It reminded me, like, how much... You did tell me that. Yeah. Just how much running room Amazon had ahead of it after its IPO.

All right. Number four. One of our very favorites. I love this picture of Jensen Huang showing off his NVIDIA logo tattoo that he has on his shoulder. I think it's from the Tegra 2 processor line. Like, name a more badass tech CEO than Jensen Huang. I think he might be more badass than Elon. I mean, they both wear leather jackets. There you go. Our number four lesson is nothing can stop a will to survive. And the reason that we put Jensen on this slide, one, is because his will to survive is unparalleled. We'll tell the story in a minute.

But two, we actually started our two-part series on NVIDIA with this great quote from him, which is that my will to survive exceeds everybody else's will to kill me. So one of the key things that we realized, looking back on all the stories that we've told, we kind of have a formula at Acquired. It just happens to be, like, the best formula of all time. And it's Joseph Campbell. And it's the hero's journey. And all the great companies, whether it's Apple or Amazon or NVIDIA or TSMC, they're all the hero's journey.

And the thing about the hero's journey is you face adversity along the way. You're fighting a dragon. It looks like you're going to die. And the thing about company building is that, unlike fighting dragons, game over only happens when you decide to quit as a founder. Like, you can't get eaten by the dragon. Like, the market can turn against you, but the market can't actually eat you. There is always, always a way to survive. It's just a question of, do you have the will to do that? And the NVIDIA story just illustrates that better than anybody. So when they were funded, Sequoia funded them. Shocking. Shocking, right? It was Jensen and a couple of his buddies from Sun. Jensen was at LSI Logic. And his two co-founders were from Sun.

This amazing technical team. This new market, graphics accelerating and gaming on PCs. Giant wave led by Doom and home adoption of PCs. This was like a great team to pursue it. Can't miss investment. No-brainer venture bet. No-brainer. Which is why the venture capitalists bet on everyone over and over and over and over again. Which is the problem with no-brainer venture bets. Everybody thinks they're no-brainer venture bets and tons of competition emerges. Was it 80 separate companies making graphics cards got funded?

Yeah, it was 70 or 80 separate companies making graphics cards all got funded. Which sounds quaint today, but that was a lot back then. And then it gets even worse. Intel came after the graphics card industry and decided that they were going to integrate graphics into the motherboard, which they had done with sound chips and networking chips and everything else. How many people have a dedicated networking card in their PCs these days? Nobody. So put yourself in Jensen and NVIDIA's shoes here. You just got funded. It's not a lot of capital.

A zillion other people just got funded with the exact same amount of capital that you have. We don't have this in our sort of discussion here, so I'm freewheeling. But it's worth knowing that NVIDIA's original approach to how they wanted to render graphics on cards was actually basically wrong. It was novel, but it was not the way that everyone else decided to go. And so it was difficult to program for. They used quadrilaterals as polygons instead of triangles as polygons.

Yes, which is not as efficient as a three-sided shape. Anyway, had a lot of merits. So not only are you not on the same footing as everyone else who you're competing against for a pure commodity on a thing that takes 18 to 24 months to ship, you are a step behind because you've burned a bunch of capital chasing the wrong approach first. Totally. So what did they do? Jensen laid off 70% of the company and they did two completely crazy things. And if you're not just focused on survival, you wouldn't do these things. One, he decided that the only way they were going to win and survive was in this brutal commodity industry was by shipping six months ahead, shipping new technology six months ahead of their competitors. And the way they did

that was they decided they were just going to YOLO it. So they designed all of their chips in software emulation as opposed to what everybody else did, which was they'd work with their foundry partners and they'd get some prototype chips made and they'd send them over from Asia and they'd test them out. They'd make sure they worked. NVIDIA said, no, we don't have time for that. They literally only ever ran the chip in software. And then once that passed, sent it to the production run.

And then the other thing that they did, which we didn't talk about this as much on the episode is, uh, of course you're going to have a lot of errors and defects by doing that. So like a large percentage of those chips, like the chips worked sort of in aggregate, but like a lot of functions that you would want to call as a game developer just didn't work. So they were like, yeah, it's a feature, not a bug. We're going to go simplify your life as game developers.

So they would ship them broken and they would just disable that. They would make it so that you couldn't access that in software. And then they would go around all the developers and say, yeah, you just actually don't want to use that blend mode. Trust us. Trust us. Like I feel like instead of all 24 blend modes, those eight are just going to be really good. So you should figure out how to write your, your games using just those eight blend modes.

And like, I can't imagine unless you are actually forced with your backup against the wall to decide, sure, I'm going to only ever emulate my chips before running a production run. And sure, I'm going to ship them broken and then tell the market to deal with it. Like these are, uh, I mean, I guess it goes back to the necessity is the mother of invention. There was a lot of necessity. Yes. A lot of necessity. Uh, so Jensen and, and NVIDIA are just the OG goat story at this. Um, but there's another, uh, great example that we had to include because we literally just talked to the CEO a week ago. Uh, and that's Eric Yuan from zoom. This is from our interview with him a week ago.

And after I started a company, I realized, wow, it's so hard to raise capital, right? And by the way, the money that you see they give to you, don't think about that money. You know, that's a trust, you know, every dollar matters, right? That's why every day I was thinking about how to survive, how to survive, how to survive. Even today, seriously, I still think about my work over the night, you know, how to survive. So the interesting thing about that comment is I asked Eric the question, did you try to create a gigantic multi-billion dollar world beating company with zoom? Or were you just thinking about sort of, um, how can I make a great product? And he like, didn't even really answer my question. He was just

obsessed with this notion of survival and that when he started the company all the way even through to today, what he's thinking about is how do we, you know, ship great product and survive. Yep. Yep. It's such a, it's the mindset of so many great founders. Yes. Number five. Strength leads to strength. So there's a chance that we picked this one mostly just so we could show Mark Andreessen on this very, very large screen, uh, on the cover of Time Magazine at the height of the dot-com mania on a throne, uh, barefoot, uh, simpler times. I feel like there needs to be some sort of, uh, similar image for 2021. Yeah. I have to think about what that is. Yeah. We'll have a

little contest later. Uh, so long time acquired listeners will know this one. Well, this really starts with the idea of reflexivity. So if you go acquire new resources, your company, um, you know, if you go get more capital or that next most important customer, uh, or a, a great key hire, you bring in the right executive to your team, you are now by definition more valuable than you were before you acquired that resource. And so the question becomes, well, how do you leverage your now more valuable asset into getting the next resource and becoming even more powerful, even more successful? And an extreme example that, uh, I always think of about this comes from a conversation that I had right here at capital camp last year, uh, with Michael Mobison, which was if

you looked at Tesla's market cap in 2020, you would say that there's no way they're worth that. And that would be a very reasonable thing to say, but what they definitely did do is use that share price to sell new shares, uh, at very little dilution and raise over $10 billion of cash to the balance sheet that year. So whatever you thought they were worth, they're definitely worth more now because they have a fresh $10 billion in cash and they know how to use it. So it really comes down to sort of the ability to uniquely marshal resources and to bring it back to Mark Andreessen in 2009, when a 16 Z raised their fund one, they came out swinging for folks who were sort of observing the

tech industry at this point, they raised $300 million for fund one in 2009. So Mark and Ben knew this principle very well. Uh, they realized when we made this huge splash, we've got this big brand, people already think we're like a top venture firm just because we did this crazy thing out of the gate. How do we solidify that position? So the very next year they raised a $650 billion fund. It million, million, sorry. I forgot what decade it was.

We're not at 2022 yet. No, but I mean, as you can tell, like they basically kept going with this mindset of just yesterday, they raised another four and a half billion dollar crypto fund. And they're somewhere between 30 and 40 billion under management now in, in what, 13 years since founding. They basically never, uh, took their resources and took that as like a static notion of like, oh good, now we can, you know, do some interesting things with this. They basically always looked at everything they had and say, okay, we're in a strong position. How do we get stronger?

How do we do more faster and, and compound what we have? So I think there's really something to just always thinking, okay, I just got more valuable and that puts me in a position to get even more valuable again and always just be really thoughtful and super aggressive about seizing that next opportunity. The other example that we have to mention on this one from, uh, the acquired Canon is literally the OG, OG, OG American capitalist business, which is standard oil did this, ran this playbook to a T. It's like the OG. John Rockefeller was like, when you say OG, like he's like actually a gangster. Yes. He may actually have been a gangster. Uh, you know, he was never satisfied no matter how

big standard oil got. It was never big enough. No matter what competitor he would acquire into the fold, uh, by whatever means necessary, or no matter what railroad, uh, he just did a, uh, a deal with, um, he would always use that to say, okay, tomorrow morning I wake up and we figure out how to use my new, more valuable company. All right, listeners. Now is a great time to tell you about a long time friend of the show, Vanta. AI has scrambled the whole security picture. It used to be that you prove that you were secure once a year on audit or a static PDF, then everyone would nod and you're done. But in an AI first world that doesn't hold up anymore. Yep. Your risk surface changes every week.

Now a vendor turns on an AI feature or someone writes in a new model without telling it and your posture is different than it was last week, let alone at your last audit. Vanta's own research found that around 70% of companies have this quote unquote shadow AI running with no security review at all. Right. And that's where Vanta comes in. They're the leading agentic trust platform, meaning they've built the thing that closes the gap. And the way that they close that gap is Vanta agent. Think of it as a GRC engineer. That's governance, risk, and compliance, except that it's software and it doesn't sleep. It finds the issues, drafts the fixes, and cuts the time that you'd spend on vendor assessments

in half. In half! Which is exactly why more than 16,000 companies today run on Vanta. Companies like Ramp, Cursor, and Snowflake all stay audit ready and catch the risks that crop up between audits across every vendor, every AI tool, the whole environment. And that's the real value. Trust has to be continuous now, which is why Vanta automates your security, your compliance, and the work to earn and prove trust. We're huge fans of Vanta over here, and literally hundreds of acquired listeners have become Vanta customers at their companies over the years. So you can get $1,000 off Vanta at vanta.com slash acquired. That's V-A-N-T-A dot com slash acquired for $1,000 off, and just tell them that Ben and David sent you. All right, number six. This is another one that is near and dear to my heart.

It's never too late. And there are actually two meanings to this lesson. One is also another great Marc Andreessen piece of wisdom. So there's a great famous quote of his from an interview, I think this was in 2014 that he did, where he said, I came out here in 1994 to Silicon Valley, and the valley was in hibernation. My big feeling was I just missed it. I missed the whole thing. It had happened in the 80s, and I got here too late, and Silicon Valley was over. And obviously, that was completely not true.

And what's cool about this is that, like, Silicon Valley and technology moves in waves. It's related to Moore's Law. Every time there's a 10x in computing, there's a new market, there's a new paradigm, there's a new technology that gets created. And so, yes, Marc was right. He missed the PC wave. It was too late for that. But he was right on time for the internet wave. And as long as Moore's Law holds, if you work in technology, if you invest in technology, if you build technology-enabled products, it's never too late. You are always right on the cusp of the next generation that's coming.

The other meaning of it's never too late, folks who are viewing the video and here in the auditorium will notice we have not Marc Andreessen on this slide, but Dr. Morris Chang, the founder of TSMC. And so this is, I think, the other lesson that I've really taken from Acquired, which is that, in this vein, which is that Morris Chang was 56 years old when he founded TSMC. And TSMC is today, I believe, the 11th most valuable company in the world. And it's so easy, you know, the flip side of the coin of there's always another generation, there's always another wave. And we should say, it may be the thing keeping geopolitical tensions at rest. Like, it may be the force that nobody wants

to destabilize and therefore we have peace. Like, it's not just a company. But it's easy to think, you know, if you listen to Mark or that there's always another wave, that's for young people. Like, it's Steve Jobs, it's Mark Zuckerberg, it's Vitalik Buterin, it's these young kids who get these new waves of technology. And the reality is that's just not true. It's just a mindset. Like, you have to be willing to dive in and do it. And you can do it at 56 years old and still build the 11th most valuable company in the world. When we were doing this, you know, putting this together, I was arguing with David that, like, this isn't novel, you know, that this is only novel recently.

Like, if you think back to what venture capital was in the 60s and 70s, it was funding veterans of the Cisco's of the world and, you know, the Fairchild's of the world who had designed, you know, five chips before to go start a new company and build the sixth chip of their life, you know, in their 50s. Yeah. And it's only the advent of the internet with cloud computing, with, you know, super low cost to start a company, that there has been this wave of very young founders creating these consumer internet companies. But that's actually a blip in history. It's funny that now the pendulum has swung so far to the lore being, oh, these young hotshot founders that we have to even make this

crazy point of, wow, a 56-year-old can start an important world-changing company. Yeah, the Trader S8 were, you know, not in their 20s. Yes. All right. This is a familiar face that many of you will recognize. Point number seven is don't mistake options for cash flow. This is from our episode with Michael Mobison, who we mentioned we met here last year at camp. So what do we mean by don't mistake buying options for investing in cash flow? Well, there's this word investing. It's come up a lot this week. It is used for multiple purposes. This is sort of an overloaded word. And classically defined investing in the Ben Graham sense is that you are looking at a series of cash flows

that a business generates from today into the future. You apply some discount rate. You value those, you know, cash flows at what they're worth in this present day. And you look at things like characteristics of the business, like potential margin expansion or their growth rate. And you make all sorts of assumptions based on, again, the cash flows that you know to exist today. And you try and come up with some price that that business is worth. And you try and put some money in and invest at that price. But Ben, that doesn't sound at all like what we do. No, David and I are professional seed stage venture capitalists and people call what I do investing. But while it's the same word,

it doesn't involve literally any of the things that I just mentioned, you know, in that previous comment. It is funny to me that it is called investing. Like it's typically just a founder and an idea on a napkin. So how can you make any assumptions about the cash flows? And then we're like, well, that founder and that idea is worth $20 million. Oh, it's so funny to me that people think it's complete voodoo math how venture capitalists come up with valuations. This is where I think that the sort of Michael's comment and his thoughts on this make a lot of sense. Because once you admit that there is no DCF, and you stop trying to say, in what world is that worth $20 million or $10 million or $70 million at an idea stage,

which we've seen recently? Well, then if you're willing to let that go, and you meditate and take your deep breath and say, okay, well, how do we price this thing then if it's not based on, you know, classic investing DCFs? Really, venture capital in the early stage is not at all cash flow based investing. It's actually options investing. And as you sort of think about it that way, the world starts to make more sense. Because how do you value an option? Well, you look at the range of potential outcomes, and the probabilistic likelihood of that option, and the entire range of outcomes, which is actually what venture capitalists are doing, whether they're cognitively thinking about it that way or not. You're basically saying, what's the chance that this is a billion dollar company,

or a hundred billion dollar company, or zero? And of course, this leads to the idea that you need diverse portfolios rather than just investing in single large companies, because this range of potential outcomes is so wide that you need to find ways to sort of smooth that risk while still benefiting from the potential of an asymmetric return. It also completely explains why venture capitalists are so obsessed with TAM. It was one of the things when I first got into the industry, I was like, why does everybody care so much about the TAM? Like, aren't there other aspects that you should care about? Well, that's what's most sensitive to the valuation of the option. It is the magnitude of the outcomes that are possible. Like, you can then debate the probable weighting of it,

but the higher the magnitude of the outcomes, the more valuable the option is going to be. Right. If I think there's some X percent chance that this thing becomes the next Apple, what should I pay for it now? That is actually the question you are asking, rather than DCFing your way to something there. But of course, it's sterile, and kind of terrible, to talk about people's life's work as buying an option. So there's an important corollary to this.

Yes. And this is from our friends over at Altos Ventures, and in particular, Ho Nam. And he makes this great point. He actually just remade it on Twitter the other day, which is, yeah, okay, like, you probably should think about valuations and venture capital investing more like options than you do thinking about investing in public companies on a cash flow basis. But don't mistake startups for lottery tickets. These may be options to you from an investing standpoint, but these founders are real people with families and lives and bank accounts and employees. And the other thing that is fundamentally different about venture capital investing versus, say, public market investing, is it's a multi-turn game, not a single-turn game.

And so how you behave and how you treat these founders, even if it's clear that your option is going to expire worthless, you don't know what those founders are going to go do next. You don't know who their friends are. You don't know who they're going to talk to. You don't know what the other investors around the table might think about the way you behaved or didn't behave during that period of time. So it's this interesting, I think these two dynamics really explain the culture in Silicon Valley a lot, which is you're doing options-based investing, but it's a multi-turn game.

Yeah. And in practice, nobody's actually just doing one or the other. Everyone's style of investing is somewhere on the spectrum here, because other than the pure play value investors who are, you know, looking at the book value of a company, or the seed stage investors or the pre-seed, like me, who are looking at a napkin sketch and a founder with an idea, or sometimes even no idea, most people are actually in the middle. So most people have to blend some notion of, what are the chances this could be big and how big with the idea that, hey, they're actually generating revenue and sometimes even, you know, cash flow as a startup, and I actually can apply some multiple to that. And obviously the multiple can change rapidly on you, and then you have to

adapt. But everybody's doing a little bit of one and a little bit of the other. All right. For our next lesson, focus on what makes your beer taste better. So we brought up this little vignette on a whole bunch of episodes on Acquired, but this is in the image of Jeff Bezos at the 2008 Y Combinator Startup School, which was a, which is a, um, which is a moment in history. A very important moment in history. So YC, at least used to, I don't know if they still do, it's probably virtual now, would put on these physical events in Silicon Valley.

I went to one in the Bill Graham Civic Auditorium. That's right. I went to one too. Um, and they would bring founders and, you know, luminaries to come and talk and inspire the next generation of founders and basically to inspire applications to YC. And so in 2008, Bezos came and this was right after AWS had launched and he used it as a, uh, marketing opportunity to market to all of these startups and future startups about why they should build on AWS instead of rolling their own infrastructure. Which we should say this strategy worked ludicrously well. Like AWS got probably a five-year lead on cloud by piling people on the plane from Seattle, going down to the Bay area, evangelizing like crazy to all these startups.

To all these tiny startups who in that very room at the 2008 YC startup school, a startup that had not even been built yet was Airbnb. The three Airbnb founders were at that YC startup school and that's why they decided to apply to YC that year and the rest is history. Worked for Bezos and it worked for YC too. Indeed. But if you go watch the talk, which I highly recommend, it's really great. Um, Jeff uses this sort of, uh, odd analogy for AWS where he talks about European beer distilleries, beer breweries around the turn of the 20th century. And you're like, all right, Jeff, where are you going with this? And, uh, the point, the analogy he makes is electricity had just been

invented. And this was this massive boon enabling technology for consumer, you know, products, CPG, like, like beer. Uh, they could now brew vastly more quantities of beer than you could before using electricity. But the first breweries to adopt it, they built their own power generators. They made their own power and, uh, that, you know, worked fine for a few years, but it was super capital intensive, required all this operational labor to run the power generators. And then the utilities companies came along and the next generation of breweries, they didn't make their own power. They just rented it from the utility companies and they, you know, ran roughshod over the first generation of breweries to use power because guess what? Whoever makes your electricity

has no impact on how your beer tastes. It literally making it yourself does not make your beer taste better. But it does raise your cost structure. It does raise your cost structure. And so Jeff's argument to all of these startups was, you know, focus on what makes your beer taste better. So there's two lessons here. One is what he's arguing that as a startup, you should focus solely, not just startup, any company, you should focus solely on the attributes of your product that your customers are going to care about. Everything else, your infrastructure doesn't matter.

Outsource. The second, perhaps more important takeaway from this, if you look at what Bezos did, not what he said, is that being a utility company is an exceedingly, exceedingly great business. And particularly being an unregulated utility company. Yes. I mean, that's the reason that Amazon became a profitable business. It absolutely is. And not just Amazon. If you think about, you know, I should say profitable company, you know, where they piled up too much cash to reinvest all their cash flows.

But if you think about this model of like, what is an unregulated utility company and technology, it can be so defensible and powerful. Like that's what Square is. That's what Shopify is. That's what I think two thirds of our sponsors on Acquired are. You know, that's what Vanta is. Modern Treasury, Vouch, even Mystery, all of, you know, if you can provide a critical, mission critical piece of infrastructure that other companies can use that they need, but doesn't make their actual beer taste better, it's a great place to outsource it.

I was thinking about this, just to go off script again, because it's fun up here. I think the, this is actually the same thing as like the economic theory of specialization of labor, but applied to businesses, where it's basically well understood at this point that GDP tends to go up when people get really good at a thing, focus their time on doing that thing, and then turn to their neighbor who's good at a different thing to provide that service back to them, rather than everybody doing everything for themselves in their lives. And this is just that on a business scale.

Totally. All right. The next one is one that is near and dear to my heart, and I had a lot of fun illustrating this, so bear with me on some of these visuals. So this one is scale up or niche down. And I want to start first by talking about niching down. So this photo is ripped with love from Brooks Running's website. It's a great Berkshire company. We had Jim Weber, the CEO on stage with us for our arena show a couple weeks back in Seattle. So for folks who don't know, Brooks is a pretty special company. Back in 2002, when Jim came in, they weren't, frankly. They were everything to everyone. They didn't just make running shoes. They made everything shoes, including $20 shoes that you would wear at a family barbecue.

And they made all sorts of apparel for all sorts of sports. The company was losing money, I think, $5 million a year in the red. They were doing about $60 million in revenue, but obviously not able to capture a lot of value out of that. And so when Jim came in to turn the company around, the first thing he did was decide, we are going to be a running company. And we are going to be a running company for performance runners, for people who care about their running. And so immediately went to a bunch of their distributors, big box stores, slashed entire product lines. So they went from $60 million in revenue down to $30 or something like that. They got rid of all their unprofitable product lines.

They got rid of anything that wasn't performance running. They blew up their whole distribution channel. And they started caring only about these performance running shoes, focusing on R&D, and really investing in building brand with runners. Well, I'll save you the whole story and just flash forward 20 years, it worked. They grew slowly at first, but then over time, it really started to pay off. And they really started to be known as one of the best running shoe companies in the world.

In fact, they're one of the top couple at any big marathon that you'll see when they take the high-speed cameras. Brooks, Brooks, Brooks, Brooks, and of course some Asics and some newer brands too, and of course the new crazy Nike shoes. But they just realized, we are not going to beat Nike. We are not going to beat Nike at the everything game. So we have to niche down and play a different game. So I mentioned that $60 million to $30-ish million in revenue. Last year, they did close to $1.2 billion and had a great year last year through the pandemic and are continuing to ride this wave of running becoming one of the largest and fastest growing athletic apparel opportunities in the world.

It's such an amazing compounding story and Berkshire story. They've been growing at 30% to 40% a year for like the last 20 years. It's amazing. Duration. Duration. So it also works to scale up. So a quick case study. We did an episode on the New York Times a couple years ago, and while every mid-sized newspaper in the U.S. was going bankrupt thanks to disruption brought by the internet, the New York Times became gigantic and a healthier business than ever. And the Times saw the idea to be sort of the one national brand and one of a few trusted global brands in the space. The internet, as we know, can be brutal to people caught in the middle because it enabled everyone in the world to access any reporting

basically for free pretty easily. And so then whoever has the best reporting in the world on global or national stories, of course, sort of gets all of the traffic and everyone in the middle is stuck. So this obviously has an enormous cost associated with it. You know, you need to basically hire all the best reporters. You need to have the most reporters. You need to build out, I mean, massive technology investments. The New York Times is truly a technology company at this point. So super high fixed costs. So you got to believe that you're actually going to be able to operate at that global scale to justify all of these fixed costs. So the point here is, sure, you can niche down,

sure, you can scale up, but you really don't want to get caught in the middle. Now on the media side, it's kind of funny. You've got these tiny little businesses like Acquired, Stratechery, our good friends at Colossus. The internet, while being extremely punishing to the middle, also enables these deep niches to form. It's sort of this interesting barbell effect, where if you keep your cost structure low and you're super, super focused on a niche, you can aggregate all the people who are weird on the internet about your niche in the entire world and basically aggregate them together and create community of people who like three-hour business technology podcasts. And I think it's important to realize that this may not happen overnight.

For Acquired, it's taken seven years for us to get to a quarter million subscribers. But if you're just repeatedly loud and specific about the value proposition that you can bring to people by following your media publication, people find their way. Time and enough distribution and enough content kind of does its thing. So I always sort of focus back on, I'm glad that we didn't decide to be a mid-scale media company. And it's really like, all right, it's you and I and some microphones, and the New York Times can have that market.

So a couple other points here. I don't think this is unique to media. I think media was the first to experience this sort of squishing in the middle, but it's going to happen to everything. The internet is still rippling out in all of its effects. I mean, you can see it in venture capital for sure. You've got big funds like Sequoia and Andreessen that get massive. And then niche funds, especially for the early stage, emerge. And there's great opportunities for small funds who are very focused. Those caught in the middle are in a tough spot.

And they're super undifferentiated. And you can imagine this happening with universities. Harvard and Stanford brands are going to be just fine. Like those will continue to probably grow in value as they're able to address more and more people using the internet. Obviously, that happens slowly because no one wants to devalue their brand. But as that becomes more and more widely accepted, I think those brands will just continue to get more powerful. You could imagine this happening in a bunch of other industries too, besides just media, capital, education. So as a final little illustration at this point, I just want to pull up a couple of market cap slides. So in 1997, there were three companies in the top 10 in the world that were

technology companies. Today, it's eight of the top 10. What happened between then and now? Well, the internet penetrated the whole world. And obviously, the returns to scale got massively concentrated here, where you can see that the most valued companies in the world, not only are they technology internet companies, they're much more valuable than they were before. So there's this sort of counterintuitive thing that the internet was a decentralized network, it started as servers at universities, and then somehow it massively concentrated the returns to scale for the platforms that underlie everything that we do all day, every day. And on the flip side, it also enabled the viability of the long tail. It's not, you know, that we have 30 mid-sized retailers in the

US anymore the way that we used to. Not at all. There's Amazon. And then there's how many merchants are there on Shopify now. We've got something like 2 million Shopify merchants and over 30 million Amazon sellers. The platformification that the internet sort of brought really enabled viability of the long tail at the same time. All right, listeners, now is a great time to thank our longtime friend of the show, ServiceNow. If you are running a large enterprise, AI agents are likely spread across every team. And deploying them is no longer the hard part.

Yeah. The hard part is knowing what permissions they have, what employees are using them for, or what decisions AI is making. AI security for an enterprise at scale is not a small concern. Like, the risks are real. Exactly. And the challenge with AI is governing it, securing it, measuring it, and making sure that it actually delivers value. That is why ServiceNow built the AI control tower. Yep. AI control tower gives enterprises a single place to see, manage, govern, and optimize AI across the entire business. And it works with any AI, not just theirs. Every device on your network, every permission across every system, every AI agent visible and secure in one place.

And ServiceNow can do this because they've spent more than 20 years building the operational backbone of the enterprise. The workflows, governance, approvals, security controls, and institutional knowledge that power how work actually gets done across IT, HR, customer service, finance, and security. ServiceNow already runs more than 100 billion workflows annually and trillions of transactions for more than 85% of the Fortune 500. So when companies need a place to govern AI at enterprise scale, they're building on a platform at the center of how their business already operates.

And in a future that isn't going to be one AI, it's going to be thousands of AI agents working across every function of the company. But the question is, who's managing them all? So if you're trying to turn AI ambition into real business outcomes and make it work safely, securely, at scale, go check out ServiceNow.com slash acquired and tell them that Ben and David sent you. All right, coming down the homestretch, staying on the media theme. So we did this episode on Oprah two years ago now and Harpo Studios and it was so great. And what our big takeaway from that was a line that was said to Oprah right as she was starting her own show and made a momentous business decision,

which was don't be talent, own the business. And the sort of way that I like to think about this is if you want to be a millionaire in the media business, you should work really, really hard, you should own your craft, you should become must-see content, totally unique, the opposite of a commodity, you should be Steph Curry, Leonardo DiCaprio, you know, what have you. If you want to be a billionaire in the media business, you should do all of those things and you should never, ever, ever, ever give away the rights to your content.

Or sell the rights to your content. And that's what Oprah did. We also told the Taylor Swift story earlier this year. You know, Taylor started as just another country music artist and then just another pop artist. And then in the past few years, she's completely changed the whole structure of the industry by figuring out ways to get back the rights to her original music, which is an incredible story. And this is fairly unique for media, right? Like for content, it's, this is easier to do than if you were, say, a basketball player.

Yes. Yeah. It's hard for athletes to do this, at least in their sports. Like athletes can own their personal brand and they can leverage that into building something on the side. But the thing that they do, they're playing within someone else's game. The interesting thing about content is you can always just make it your own game because the internet enables this distribution. That's the last, you know, cool thing about this, which is that thanks to Substack, podcasting, YouTube, TikTok, Instagram, it's never been easier.

You don't need NBC. You don't need Universal Music Group. In fact, they might hold you back. Anybody can publish anything on the internet. All right. This one is reasonably self-explanatory, but it's another Bezosism. And so I want to bring up in the very first shareholder letter in 1997, he wrote, because of our emphasis on the long term, and people probably might know how to recite this by heart at this point, we may make decisions and weigh trade-offs differently than some companies.

We will focus on growth with an emphasis on long-term profitability and capital management. At this stage, we choose to prioritize growth because we believe that scale is central to achieving the potential of our business model. This is absolutely Bezos's way of basically saying, if you're not on my bus, get off, because this is what we're doing. They stayed true to their word for 20 years without turning a profit. As we talked about earlier, you could argue they still wouldn't be profitable today if it weren't for AWS.

They've reinvested every dollar of the retail business for two decades. There is zero chance that they would have been able to execute the strategy that they did if it weren't for their ability to be loud and proud about their intentions. And as we sort of drift toward the close here, I'll be a little bit less bashful about acquired specific examples. I've wanted to highlight other businesses, but this one's sort of too close to home. We're obsessed with this idea of treating our audience like they're smart.

And this wasn't the fastest path to growth because I think we could have listened to what everyone told us. Podcast episodes need to be a half hour. Podcast episodes need to drop every single week so you keep this content cadence. But we wanted to be weird on the internet about something. And we wanted to basically be unabashed about it. And so I'd say that the people that we get to interact with now in the community and all the folks that we met here who mentioned, oh, I've listened to the show.

We ended up with exactly the listeners that we wanted and the people that we want to spend time with because there is a long game to play. If you're saying if you don't want to be on the bus with us, that is fine. Please get off as soon as possible. Indeed. Which is the perfect lead-in to our final lesson from seven years of Acquired. Speaking of getting on the bus, we all need to do that to go to the party.

And what are we going to do at the party? We're going to have fun. And that is what this is all about. If you can find something that you can do with your business, with your life, where you genuinely have fun doing it, and for other people who do the same thing, it's work, you are going to run farther and longer and faster and better than everybody else. And there's actually another takeaway to this. So we put an image of us and our friends, Paki McCormick and Mario Gabrielli at our arena show the other week up here.

It was just such a blast. This whole thing, this whole journey has been so fun. But one, you're going to work harder than people for whom this is work. And Bill Gurley makes this great point in his Running Down the Dream talk, which we've talked about on Acquired. Everybody should go watch that on YouTube. But the other point is that it's so much easier to evangelize and grow and market and have people attracted to whatever it is you're doing if you genuinely have joy in doing it.

And joy is not something you can really fake. So that's our biggest lesson. We have had such a blast doing these past seven years. We've gotten to meet amazing folks like Patrick and Brent, the whole Capital Camp team. And we're just so thankful. All right, listeners. Now is a great time to talk about one of our favorite companies, Statsig. Yes. Long time acquired partner. There is a reason why the best product teams at companies like OpenAI and Notion, Atlassian, Figma, Rippling, Brex, and more rely on Statsig, whether they are iterating on their core product features or shipping AI-powered experiences at scale.

Yep. In the crazy speed of today's AI world, shipping fast is just table stakes now. It's basically trivial to build and deploy your app constantly. The real advantage is how quickly you learn what changes actually created value for customers and how fast you can use that signal to guide what you ship next. Whether it's a feature tweak, a pricing change, a performance improvement, or an AI update like a model change or prompt adjustment, they're not relying on instinct.

They're measuring what actually moved engagement, retention, and ultimately revenue. And as more teams build with AI, that learning loop becomes even more important. Building with LLMs introduces non-determinism into your product experience. The same input doesn't always produce the same output, and behavior can shift in subtle ways in real-world use. So doing offline evals will give you part of the picture, but you can really only understand the impact once your product is live with real users, and then you can measure how their behavior actually changes.

It's very different than the way that you would ship features in a pre-AI world where you knew exactly what the software was going to do in production. Yeah, exactly. So this is where Statsig comes in. It brings experimentation, feature flags, and product analytics into one unified system so teams can ship safely, test rigorously, and directly link what they changed to how users actually behaved. The result is a tighter feedback loop and learning that compounds over time so you don't just ship more, you ship better.

So if you want to make learning your competitive advantage, whether you're building new AI experiences or just evolving your existing core product, go to statsig.com slash acquired to get started. All right, listeners, hope you enjoyed our talk from Capital Camp. Please let us know your feedback, acquired.fm slash slack. Would love to hang out with you in there and hear some of your favorite themes from all the playbooks over 200-ish episodes. I actually didn't count exactly, but it's a lot.

I didn't either. I think it's well over 200 when you include all the LP episodes. Yeah, it's 250 with those. Oh, wow. So we definitely skipped a lot. I had 18, and David made me trim it down to 12, so I'm curious if some of the ones that we didn't talk about are ones that you want to bring up. I originally wanted 10, and Ben was fought too hard that I gave him two extras. Yes. Well, thank you so much for being with us this season and on these special episodes.

It's been an awesome six months. We're super pumped for the next six months. We have some great stuff planned, and we'll see you next time. We'll see you next time. Who got the truth? Is it you? Is it you? Is it you? Who got the truth now? Huh. Who got the truth now? Who got the truth now? Who got the truth now? Thank you.