The a16z Show - a16z Podcast: Startups and Pendulum Swings Through Ideas, Time, Fame, and Money

Episode Date: May 30, 2016

Everything old is new again when it comes to startup ideas and how technology innovation happens. But practically, how does that apply to starting and/or working at startups — especially since the default state of every company is “dying in obscurity”? In this episode of the a16z Podcast, Marc Andreessen and 21 co-founder Balaji Srinivasan cover everything from deciding what ideas to work on and the optimal type of startups to work at, to the funding environment and pendulum swings of deciding when to IPO. They also discuss the VC “formula” of weighting product vs. market vs. team; the full-stack approach to cracking industries that tech could never enter before; and recent tech trends and news including The DAO, AI, VR/AR and the “Instagrammification of everything”, more. And where does Andreessen stand on the “moral dilemma” of whether entrepreneurs should drop out of college or not? Would Srinivasan still do a PhD today? People’s early career goals should be about maximizing learning skills and minimizing “personal burn”, they argue. But no matter what, Andreessen believes, smart people — from all industries, not just tech — should build things. It’s also easier to get through startup hard times when there’s an ideological mission motivating you, observes Srinivasan. This episode is based on a May 2016 conversation that was recorded as part of the Annual Distinguished Speaker Series with Thought Leaders in Technology, hosted by engineering honor society Tau Beta Pi at Stanford University. photo credit: Ryan Jae/ The Stanford Daily Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

The content here is for informational purposes only, should not be taken as legal business, tax, or investment advice, or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. For more details, please see A16Z.com slash disclosures. Hi, everyone. Welcome to the A6NZ podcast. I'm Sonal. And today's episode features Mark Andreessen, an A16C board partner and co-founder of 21, Bologu Shrini Vassen. This conversation took place in front of a six-in-one of a six-in-one. a group of Stanford engineering students as part of the Engineering Honor Society, Tao Beta Pi's Distinguished Annual Speaker Series with Thought Leaders in Technology. Let's talk about one of the things I'm sure every student here at once, or not everyone, but a lot of them, you know, think about startups, think about technology as an entrepreneur as a founder, as a potential employee. How should students today, you know, graduating from Stanford think about startups in both the founder context and an employee context?

Yeah, so the traditional venture capitalists all have like a secret sauce kind of formula of how they think about what they want to fund. And then it turns out, I think the formula is all reduced to the same handful of factors. With the exception, maybe of Peter Thiel, who has like six other factors in his head that he hasn't told anybody about. But for everybody else, basically always reduces down to some combination of market, product, and team. If you talk to people who've been in venture for a long time, what they'll tell you is basically the difference between venture firms, you know, in a lot of ways, is based on how do they rank

the importance of founder of market, product, and team. You know, as an example, Sequoia was legendary and prioritizing market over team. So Don Valentine has, if you go online and Google Don Valentine's talks, he talks a lot about how the key to success of a startup is to land yourself in a giant market. Like, land yourself in a market that's about to become explosively large. And basically, once a startup is in a position where it is the leading company in an explosively large new market, the people become somewhat fungible. Like, you can swap the people out.

And he would cite Cisco as one of the great case studies of that, which, you know, is actually a Stanford spinoff, husband and wife team, very sharp founders. But they got booted very quickly, actually, by Don Valentine, who brought in, professional CEO, John Morgridge, who was phenomenal and actually built, you know, built Cisco the company. And so that's one model. The diametrically opposed model is prioritizing team over market, basically saying that, you know, the right market, whatever, can you really even know what the good markets are going to be? Like, how well can you predict? Really what you're doing is you're going into business with people, either going to business with really good people or not.

If you're going into business with really good people, one of the things that should make really good people really good is they should be able to find themselves, you know, a good opportunity. right a lot of startups end up you know they succeed based on something different than what they started doing and so if you get in business with the right people they'll be able to sniff out the opportunity peter i don't want to put words in his mouth but i think he'd probably prioritize product over market and team which is you have to be doing you have to be making a fundamental advance in technology he can tolerate a lot of flaws in the people and he can tolerate a lot of uncertainty around the market if the product breakthrough is big enough he'll make those other bets it's kind of an angels dancing on a head of a pin thing you kind of as a vc you sit around

talked about this a lot, and then if you want to invest in a company, you kind of figure out some rationalization, I guess your formula to do it. So I don't want to overstate it. But I want to go through it because I do think that is the framework, you know, as you think about startups as either a startup that you might start or as you think about a startup you might go to, I think that's a pretty good framework. In terms of where, if you're here as a student or if you're going to be graduating, my personal recommendation would be to focus much more on team. And the reason is just because I think we struggle from a distance to evaluate market, and we also actually struggle to evaluate product. But if you can get yourself in business with really good people, I think,

number one, like if it works, it's great because those are really good people to be a business with and they can, with you can build something great. But even if it doesn't work, even if it's the wrong market or the wrong product, you'll still learn so much working with the right people and you'll build such a valuable network for whatever you do next. It would also apply if you start a company, like, who do you start a company with? You may end up in this situation or it's like, do you start the company with a super genius who's cantankerous and hard to get along with? or do you start the company with the person who's like maybe not quite as incandescently bright,

but maybe it's much more collaborative. By the way, I don't know that there's a right answer. I do know it helps a lot early in your career to be working with really good people because it really gives you a sense of what good really means and gives you the ability to learn. Yeah, I would say one thing that we've talked about is that it should be exceptional at least one dimension.

Yes. It can't be like just pretty good and all these different things. At least one dimension needs to be like truly 10x and, you know, amazing to make the bet. That's exactly right. We talk a lot in our firm about, we have this concept, we say we invest in strength, not in lack of weakness. And again, it's one of these things that sounds obvious, but it's proof to us to be a pretty

big deal. So there's a lot of, there's a lot of startups you'll run into where you probably have friends who are at these companies or no people at them. And it's like, team's good, products good, market seems good, they're making some progress, they've got some customers, the customers are pretty happy. Okay, where is that really going to go? And where is it really going to go? Because what's spectacular about it, right? What's the thing that's going to cause it to jump out from the other hundred or other thousand companies where you could say the exact same thing. So then you say, okay, great, now I want to invest in strength. Okay, that's easy. The problem of investing in strength, or the problem is joining a company is that

the strongest startups, at the point of contact, what you discover is the strongest startups aren't strong at everything. They're strong at something. And then they often have, the term we internally use ironically is they have hair on them, which people always kind of surprised when I start to use that metaphor, but they often have serious team issues. Many successful startups have a founder divorce at some point, like whether the founders go to war. And you would think that would be a very bad indicator and actually sometimes it's a really good indicator because it means the things are really starting to work and like it's time to get serious and one founder wants to get serious another one doesn't or you'll have these we some of our best companies are like stellar a product

and engineering and cannot go get a deal with a customer to save their life and like labor for years under the illusion that the way the world works is that if you have the mouse trap everybody beats a path to your door and then three years later they're like oh where you have to get salespeople to go sell things and so there's these things and they'll just drive you nuts but if the strength is strong enough they can really punch through. And so much about this, another thing maybe we're saying is the default state of every company is just dying at obscurity. And so much of it is how do you punch through, how do you punch through in the minds of the people you're going to have to recruit? How do you punch through in the minds of the investors? How do you punch through in the minds of the

customers? How do you punch through to the press? Like, how do you actually get yourself visible such that you can start to attract the kinds of business and momentum and talent and money that you need to be successful? And so that sort of model of strength versus lack of weakness, I think, is pretty important. Every startup and every project starts as a as a hallucination, right? Like it's a, word on a napkin. It literally doesn't mean anything and you have to believe it can become much bigger than it is. And always at every stage it has to become, you have to believe it's bigger than it is. Yeah. Okay, so. By the way, it means in our business, it means in our business, if we're doing something right, there's something basically horribly wrong with every company we fund.

One of the reasons like the investment banks or the hedge funds don't just come in and do venture capital is because they're just horrified at every single investment we do. The one saving grace that we have with that model is with a portfolio, so we get to make, you know, basically 30 grossly irresponsible bets, right, in a portfolio. And then basically the math is, if we're doing our job, right, 15 work and 15 don't. And in almost any other area of investing or any other area of business, if you have that kind of failure rate, right, with that kind of risk level per decision, you would just throw up and go home. If there's one edge that we have, it's the ability to kind of indulge in these situations where the strength is crazy, but the weaknesses are also, frankly,

crazy. Yeah, I mean, like, the thing is, if it gets de-risk all the way, then it's just a safe investment and there's very little upside. But I think it also holds for technology in the sense that if you read about something in the Wall Street Journal or the New York Times and technology it's on everybody's lips, it's probably, not always, but it's probably started to have some of the value taken out of it in the sense that there's a lot of companies

that are already built in the space. It's very competitive and the technology to look for are often the ones that haven't gotten a lot of press yet, you know, that are near inception that are in the labs of places like Stanford. If it's a buzzword, if it's something that's on people's lips, if there's a magazine articles about it or newspaper articles about it, or God help us if it's on TV. The time has passed.

Like, we better look for something new. So, relate to this, we just talked about how people should think about pursuing startups. But what does it mean for, so folks who are, you know, employees, what does it mean when companies stay private longer? And what do you think of as the root cause of this relatively new phenomenon, really the last 10, 15 years or so? So the model for Valley startups, right, used to be very straightforward, which is you'd raise an A round, then you'd raise a B round to kind of build out your sales force. Once the product started working, you raise a C round to maybe expand in a couple other countries, maybe add another, maybe do a little acquisition or something. And then within, you know, four, five, six years get to about, you know, 30, 40, 50 million in revenue and you'd go public. It was sort of viewed, you know, that was sort of the right of passage.

And then a bunch of things became possible once you were public that weren't possible before. So one was liquidity, which is early investors and employees could start to sell stock. But there were other very important ones. One was it was viewed as a legitimizing event, especially for companies that sell products to other companies. It was viewed as an event that basically was, you know, a lot of big customers of technology would much prefer to buy technology for public companies. because they feel like they can understand the vendor they're buying from, whereas these private companies, they don't know if they're still going to be in business or not. And then also M&A, mergers and acquisitions,

it's considered a great virtue of being public is to have an acquisition currency, right, to be able to issue stocks. And a lot of the great tech acquisitions over the years were done with stock because you basically go public and you can use that value to buy things, even if you don't have the cash. The stereotype is that everybody wants to go to work for a startup in the Valley. I think the reality is a very large number of people actually don't want the true early-stage risk. They want to go to a company that's doing it.

interesting things, but they don't want to have to, like, go for another job in six months if something goes wrong because they've got, like, a family. They've got, like, a spouse, and they've got a mortgage, and they've got kids, and they've got bills they have to pay. And so there's actually a lot of talent that got unlocked once you became public that you could actually recruit. And so those are the old days. Interestingly, in the U.S., the number of public listed companies in the U.S. peaked in 1997, weirdly enough. And you might think it peaked into, like, 2000 or 2002 or something, but actually peaked in 97. And basically, the number of public companies in the U.S. is now dropped by two-thirds.

since 1997. And that has coincided with a bunch of other things. I mean, one was, you know, we had the stock market crash, and then we have the credit crisis. But it's also coincided with some other changes. One of the big changes, for example, a lot of tech IPOs actually were individual investors, right? A lot of historical investors and small tech companies were individuals

who would read about these things and get excited and invest. If you just look at the statistics on this, the percentage of ownership of tech stocks by individuals has dropped like a rock. Since 2000, it's basically now all funds, right? And funds are inherently more concerned. than individuals because funds have, you know, they feel like they have responsibility to be sober. And so they're not that excited about the next hot IPO. And so the public market, like just a lot of the enthusiasm has been drained out of it. The market's changed dramatically. And so it's sort of,

you know, Tobology's question, it's kind of become in vogue or in style to not go, either not go public or at least not go public as fast as before. The good news about staying private longer is that there is something about going public that puts you on a treadmill of quarterly results. they're like, well, you know, I'm not going to get on this treadmill and quarterly results where I have to hit all these quarterly earnings targets. I'm still going to be able to do long-term things. So the good news about staying private is that you can do these big ambitious projects over long and, you know, you either get them right or you don't, but you're not under any specific

quarterly pressure to deliver any particular set of financial results. My view is that the pendulum has actually swung too far now in the direction of not going public. Like too many companies are now staying private too long. It used to be that it was a contrarian view that you should stay private. it's now become a contrary view that you should go public. And my argument of why more companies should go public is at some point, it's good to not just have all of your results be in the future, but to actually have to deliver in the present.

And at some point, it's good to have an organization that actually, like, knows how to work properly and knows how to sell things to people, and knows how to, like, have financial plans that it hits and knows how to make money. And it's all hypothetical until you have to prove it. And I think a lot of companies that are staying private for too long, risk getting sloppy and disciplined. And in the beginning, that's fine.

But at some point, you have to get serious. And if you can go for 10 years without getting serious, I think there's a real risk that you never get serious. So that's one. And then number two, it's become massively differentiating to go public because you get these big advantages. You still can then tap the public markets for more money. People talk about Elon Musk, and SpaceX is still private,

but Tesla's a public company. So Elon Musk puts out this thing, the Tesla Model 3, the pre-orders, and it gets half a million pre-orders, and all of a sudden, everybody hated Tesla before because nobody wanted to buy the car. Now all the investors hate Tesla, because now there's too much demand for the car, right? which is apparently equally bad.

And so he just now studied he's going to do a $2 billion secondary offering, right, in the stock market. And, like, even in modern, like, venture capital, it's hard to raise $2 billion at a shop. Not very many people can do it. And so he can actually, like, raise that amount of money publicly. He can access debt. And then, you know, you go back to the acquisition currency. Like, we've probably been in a slow period for M&A for a while, but there is no question. There's going to be a lot of M&A in the years ahead.

And the companies that have public currencies, they're going to be able to be the acquires and able to get big and become much more important. So I think the pendulum is going to swing back in the other direction. There's a crop of companies, good companies, definitely going to go public. I think another part is also Sarbox. And all the rules, and then Dodd-Frank and so on,

has made it quite difficult to be a public company from a compliance perspective and the fixed cost associated with that. Yeah, so there's this thing Sarbanes-Oxley, which I see somebody in the audience yawning, and this topic is going to make everybody yawn. And so I'm not going to go into detail. You can Google it if you really want to learn about it. But it's the regulatory kind of threshold

that public companies need to hit on how they deal with risk and they do reporting and all this stuff. And the knock on Sarbanes Oxley has been exactly what Balogies said, which is it's basically a burden that falls disproportionately on small companies. Because big companies have huge staffs of lawyers and finance experts and so forth who can do all this stuff. But small companies, the burden falls directly on the management team. Our partner, Ben Horowitz, now argues the opposite side of this, having seen a lot of companies. But she argues, if you're good enough as an operating team to actually comply with Sarbox, then you're good enough basically to do anything.

Like, basically, not everything in it makes sense, but it sets a bar for what it means to be an operating business that's operating in a company. responsible way. So I think he's actually flipped a little bit on that. I think he would argue it's actually part of being a responsible company at some point. Interesting. Actually kind of gets into our next questions. You're going to talk about a few important technologies. One thing I've thought a lot about is that the ultimate kind of solution to this is going to be something to relate to the Bitcoin slash Ethereum crowd funds that are happening now on the internet where you have, the regulatory stuff has to be worked out about that. But you do have a very large potential pool of capital that people can use for this kind of thing. And that might be, you know, this is an

essay that Naval and I wrote a couple years ago about, like an app coin. So you'd actually start a company and actually issue a coin that could be used to redeem for calls of that SaaS service. So that's one model that might. You might just mention, Bray, is this as a whole new model for how to think about sort of crowdfunding taken to another level. You might just mention the Dow and what that is? Yeah, so this is a pretty interesting concept where, so Ethereum, it's something that was based on Bitcoin initially, and it's sort of like a more programmable version of Bitcoin in some ways. There is a thing called the Dow, which raised almost $130 million online in a purely distributed way, just with digital currency, without any stock market or what have you. There's all kinds of

regulatory hair on this animal, and people can pull their money out of it. So it's sort of like a VC fund where the LPs don't actually commit until they see the first investment. So I think there's going to be all kinds of stuff that happens with it. Nevertheless, I think there's a very interesting experiment in something which will probably be relevant for you guys, not this year, not next year, but in maybe five to ten years in terms of potentially an alternate way to get financing for something. So actually that leads us into important technologies, right? So let's get a quick riff on them one by one. So starting with maybe, you know, talk about Bitcoin and blockchain, then FinTech more broadly. Yeah, so I'm going to turn the first one around. So Balogy is the founder of one of our two big

Bitcoin investments. So, Bology, how's Bitcoin doing? How's Bitcoin doing? Yeah, so, you know, like the Gartner hype cycle, right? Something we think about a lot, we think of it is this fundamental thing in technology, that is you've got this trigger and then people get really amped about a technology and it's everyone's doing it oh you know bots are at that stage right now and then you try to actually do it and you find it's actually hard and everyone gets demoralized and they quit and you've got the trow and then it's those guys who stick it out in the trow and pull up over here that you know things actually happen so that happened like the dot-com bubble everyone was hyped about in 2000 and crashed and then actually you built all these massive businesses and it happens on like

larger and larger cycles as well carlotta Perez she's got this whole theory about why that happens and it kind of happens at different scales and we sort of think that's happening for Bitcoin in the sense of there's a huge amount of excitement in like 2013, 2014, you know, oh my God, new paradigm then, you know, like, oh, the price crashes and now it's coming back up with a lot of like the micropayment stuff and interesting things happening this year.

I think the blockchain stuff is actually right at the top the Gardner hype cycle and I think it's going to crash down like towards the second half, you know, of this year when people actually try to implement it. That's where I kind of think Bitcoin and blockchain is and I would say that, you know, in addition to our kind of point earlier, about like getting technologies

that nobody knows about it all that are in the lab right now, I think the other kinds of technologies to really look at are those that people have written off. Right. Like, you know, VR after second life. And so that's the kind of thing

to look for the stuff that people think of as, you know, dead or it didn't work or what have you and find out why. That's very funny. You don't remember the first time VR got written off. Oh, no, that's true.

You only remember the second time I remember the second time. Yes, that's right. No, actually, you remember the third time I got written off. I remember the previous two. You got written off after VPL. You got written off after the VR.

there's a whole VR wave in the late 80s. One of the great all-time hacker movies. One more man was kind of the peak of that cycle. And then we bought a VR company at Escape in 1995 to do VRML, which is VR on the browser. You may note that that didn't work. And then, right, there was second life, which was like the third cycle. One of the things we talk a lot about is, say,

two operating principles in how we think about technology. One of the things I've come to believe, there are almost no actual new ideas. Right. Basically, everything that is going to be a big deal in the next 30 years is in a lab somewhere, probably here in a lab at Stanford. And so the eureka moment is like an almost non-existent thing. Maybe every once in a while, but there's almost always a 20 or 30-year backstory of research.

That often, by the way, turns out to be 50, 60, 80 years, backstory of research before something pops. And then the second thing is just, yeah, things take time. There's this concept called the AI winter. And it's literally there have been surges of enthusiasm and crashes in AI. And I think we've counted there like we're five AI winters between 1950 and basically 10 years ago.

Even the term AI has only come back recently after neural networks themselves came back because everyone is like, oh, AI is all rule-based and ML is the new thing. And we're having another mini-cycle within that where, like, Chris Dixon and I joke that so many AI companies are just a collection of if-all statements. And, you know, it's like, okay.

Which are very compelling on first demo. Very first, yeah, but it's always on rails, right? And then when you try to get it a little bit off, then it's like, you cannot compute, right? Yeah, and so I think it's, I think, about it's a very important kind of fundamental point, which is, it's not, I mean, what's new is important, but it's often what's new where there is a track record

of intellectual depth that's gone into it over a long enough period of time that people really have thought hard about it. And it turns out that track record is almost always multiple decades. And then whatever happens to be hot or not in any particular moment is really not predictive of what's actually going to happen. Exactly. I think, you know, in particular, there's two things if you ask me, you know, what like to look at for startup ideas and so on.

So first I'd say, don't do a startup unless you're ideologically driven to make it succeed beyond the economic motivation. because it's actually very hard. But if you do want to just find startup ideas, there's this book, The Sovereign Individual, came out in the late 90s. It's the most prescient thing in the world. Most bestsellers, you can take the 300 pages

and compact them into like a one-page summary, and there's actually websites that do that, right? Whereas this book is the opposite. You can take, like, a page and turn it into a PhD thesis. And what's awesome about it is, you know, we kind of think Satoshi read through the sovereign individual and actually made Bitcoin in part on that basis because the description of it is so lucid.

But what's interesting is there's other pages of it which haven't yet been implemented. So it's like the book of prophecies and you just flip through and oh, let me do that one, right? So then the kicker would be, you know, that book ripped off another book. An older book. Oh, what's that? It's an older book called The Twilight of Sovereignty. Interesting. Which was written by a guy named Walter Riston, who was the founder of Citibank, who spent 40 years in banking,

40 years in like big New York institutional banking, and his conclusion at the end of it was it was all bullshit. And he basically wrote a book predicting basically the rise of networks and distributed finance, distributed money. This is like 30 years ago. Yeah. So, I mean, what's interesting is a lot of those guys got the general direction right, and then there was some aspect

that actually turned out to be much more difficult than they thought. For example, like autonomous robotics. Well, actually, that's really hard because of the number of degrees of freedom and the probability so on, but it's doable with enough training data. I think the other thing that, you know,

when I think of like a back-to-the-future thing that's very important, is this thing called T-Bow sorting. So, like a while back, we found this guy done it in 1956, and he had a bunch of assumptions for this model of how people could sort into like basically many governments around the world

and he assumed like, okay, you have search, you have perfect information, you have perfect mobility, you have this, you have that. And he basically like assumed the smartphone. They wouldn't have put it that way at that time, but 1956 he assumed the smartphone and he's like, oh wow, you can solve all these problems with governance and so on. It's like literally 60 years later you can go back, you know, dust off this

Raiders of the Lostark stuff and just, you know, go with it, right? And you'll sound really smart because you can just like read off the book of prophecies. But, okay, so other important technologies. All right, so AI, right? We just kind of talk about this a little bit. So autonomous cars, drones, ML and software, what is your take on this? Yeah, so magic is happening, and I think everybody here probably knows this by now,

but something has changed, and actually what that something is is a matter of some debate, and it's probably multiple somethings. But an entire battery of techniques that people have known about for a long time, plus some new techniques in machine learning and deep learning have really started to work. 2012 was kind of the tipping point for that, and now it's really building steam. And then it also feels like something changed. Part of the passage of time in our industry is just Moore's law, allowing processors to kind of catch up with our ideas.

And the rise of this new generation of GPUs that are able to run these, are able to run neural networks and deep learning algorithms is a really big deal. And then, you know, we now have existence proofs of, you know, fully running autonomous cars

using deep learning. We've got autonomous drones with deep learning. We got, you know, AlphaGo, the great accomplishment that Google recently had, the Deep Mind had. Like, significant breakthroughs are happening. I would say something

both very dramatic happening, but also something very real happening. Yep. I would add to that, actually, just data. Like, because, you know, like many of these algorithms you just put 10x of data at them and they work,

and one tenth of they don't. And so, like, just the easiest of collecting massive amounts, right? Yeah. So, VR and AR, so, you know, Oculus and Magic Leap and stuff like that. What are your thoughts on that area? Yeah, so very exciting.

So VR, right, is the idea of the headset of you basically are in a completely computer-generated world. I like to say the world's now divided into two groups of people. People who haven't tried the shipping consumer version of Oculus who think VR is stupid, and then people who have tried it who think it's the future of everything. And so if you haven't tried it, find somebody who, they just started shipping,

find somebody who has one and tried it. It's a really profound thing. The other idea people are playing with is augmented reality, or AR, which is the idea of you still see the real world, but you have computer-generated imagery kind of populating it, and there's a company called Magic Leap in Florida that's doing this, and Microsoft has a thing. We actually argue there's two kinds of AR.

There's the kind that people are talking about because they find VR too scary. And that's why all the news articles in VR are all very emotionally loaded, because it's invariably a picture of somebody with this thing strapped of their face, right? You don't actually get to see what's inside the VR. You just get to see the idiot sitting there in the chair with the alien face hugger like this,

and then everybody thinks it's funny. To a lot of people who find VR too weird, AR feels like it must be more normal because I still get to see everybody. And I think it's actually a little bit of an intellectual crutch for people who just can't quite come to grips with VR. That said, there's the other form of AR, which is, like, if we can get AR to really work, right?

And if we can get to the vision that I think everybody in the industry has, which is get a pair of very light eyeglasses or even better contact lenses and overlay computer imagery on the real world, like, that is a big deal. Yeah. And there are teams, there are a handful of companies now

that have teams that are super focused on this. Two thoughts, one on AR and one on VR. One thing about AR is, if that kind of thing can work, I think you can have what we think of as like the Instagramification of many more things. In the sense, what is Instagram? So, yeah, it's a photo app. But what's also is something that takes somebody

who has no skill in photography and gets them to like an eight. Because you've got a programmer on your shoulder and, you know, he's like, oh, you know, put the F stop there and whatnot and don't, you know, jutter it and so on. There's always at least one filter

that makes any photo look good. Exactly, that's right. I actually think like the next version of Instagram will make people prettier, right? Like I call it Tinder for Instagram. Just keep swiping until you get attractive enough. Well, yeah, exactly. You've just got a filter that just morphs it just a little bit, right?

Come in handy. Exactly. The thinking is, though, that Instagramification, you could apply to many other areas where they are, right? So the classic examples are you're a mechanic and you put on the glasses and now, you know, every part lights up and you see the 3D schematics and you tap here to order the replacement from Honda and so on.

Or you're a surgeon and you can actually see the person's x-ray superimposed on them. And so it's like you've got a superpower, right, in that sense, which actually tweets from you head a while back. And then on the VR end of things, you know, one thing when people kind of dismiss VR, I always ask them, okay, how much time do you spend looking at a screen? How much time do you spend looking at like a laptop or a phone? And they'll say, you know, okay, maybe six hours a day. And so they'll say, okay, well, that's like 50% of your waking hours.

And we're probably going to replace a significant percentage of monitors with VR with something to the 2D world, right? And there's going to be a new Windows that's based in the 3D universe, which has totally different GUI metaphors. So that's an interesting kind of company to build. That doesn't exist yet. But that company, okay, so when you're wearing this VR thing to do work, not just to play video games, well, actually most of your life is in the Matrix.

So that's going to be kind of interesting in like five or ten years. Everyone's wearing these kind of things. It's coming. Great, great. Okay. What should Stanford students be thinking about doing after graduation, or dare I say instead of graduation? That's question number one.

And then related, what advice would you give if you're at Stanford right now, and what's the student walking out of this hall do right now? Yeah, so I used to people, people used to ask, you know, should all these examples, Mark Zuckerberg and all these founders who dropped out, and so therefore, you know, everybody should drop out and start a company.

And so people used to ask, you know, should I stay, should I drop out, what should I do? And it used to be a very, I used to feel like a real moral challenge answering that question, because I felt like if somebody was meant to, if somebody really should drop out and start a company and I'd tell them not to,

I'd be committing a moral crime, but most people probably should stay in school and actually get degrees, and it feels immoral to suggest otherwise. So I felt trapped. I thought about it. And the absolute straight advice, 100% of the time, you should stay in school, finish your degree, not drop out.

And I've concluded that because the people who are going to drop out and start a company are going to do it regardless of what I say or what anybody else says. And so it's by definition, it's good advice. I can't possibly stir anybody wrong. In general, actually, not only is a good idea to get the degree, it's the thing that is the most underrated right now. I think the archetype slash myth of the 22-year-old founder

has been blown completely out of proportion. The thing that is underestimated now in the valley, frankly Stanford, is at ground zero of this. I think skill acquisition, literally the acquisition of skills on how to do things, is just, like, dramatically underrated. People are overvaluing the value of just jumping in the deep end of the pool, because, like, the reality is most people

who jump in the deep end of the pool drown. Like, there's a reason why there are so many stories about Mark Zuckerberg, it's because there aren't that many Mark Zuckerbergs. Like, most of them are still floating face down in the pool. Cool. And so for most of us, it's a good idea to get skills, your degree or whatever, but then there is a lot to learn, if you want to, like, ultimately start a company or go to a startup, there's a lot to learn about how companies operate, right? There's a lot to learn about how to manage, how to deal with people. There's a lot about how to manage. There's a lot about, you know,

leadership. There's a lot about, by the way, finance. There's a lot about legal. There's a lot about marketing. There's a lot about sales, HR. Like, there's a whole skill set. Like, if you, if you meet, you know, the really great CEOs, if you spend time with them, and if you would find this to be true of Mark today or of any of the great CEOs of today or the past, like, they really are encyclopedic and their knowledge of how to run a company. And it's just very hard to just kind of intuit all that in your early 20s. And so I think the path that makes much more more sense for most people is to spend five or 10 years getting skills. So the problem with going to raw startup house school, it sounds great, but like most startups are like really screwed up. Like

like I said, most of them just die in obscurity. And I don't know exactly what you learn from dying in obscurity, but it's not very much. A lot of people are at startups that don't work well. They actually don't carry away a lot of useful skills. Conversely, you know, you leave school, you go to a big company. A lot of what you learn in a big company is how to function at a big company. Right. But the problem with people who have been at a big company too long

is in the cold light of day when they go have to do their own thing. They literally don't know how to function without all the infrastructure and support of a big company. And so I think there's a sweet spot, a new high growth company or the company that's scaling. That's probably the best place to go. And of course, you're at Stanford, you have a huge advantage of being in the environment. You already know who those companies are, and, you know, you have a pretty good chance of getting jobs there. So I think that's generally really good advice. The other thing that I would say is I have a favorite book I've never read.

And I'm actually, I'm worried about reading it because I think it can only disappoint me at this point, because I like the title so much. And the title of the book is smart people should make things. And like, as far as I'm concerned, like, that's the entire value of the book. Like, I don't even care what else he says. Like, just for engineers, it's very obvious. like engineers, engineers should build things, should build products. And that could be open source. It could be, you know, working with a, you know, with a friend of something,

but like going to a company that's building something. But I think the same thing is true of everybody else, right? And people build all kinds of things. And by the way, the things that people build might be art, right? The things that people built might be, you know, businesses. The thing that people built might be, you know, an organization inside a company, or it might be, you know, a great, you know, explanation of something. But tangible output, it just always kind of really encourage people,

like, when in doubt, fall back on building something tangible. Yeah, and like we've got that thing at Andrews and Ars, right? Like works in practice, not in theory. So much stuff that I saw, you know, as a scientist, a PhD at Stanford, worked in theory, but just not in practice. And there's lots of stuff that's just the converse. And only if you actually build it, you see that. Yeah. Why did you and Ben then decide to start a VC fund

rather than doing another startup? Yeah, so, well, we were customers of venture capital, or at least I thought about it that way. They thought they were giving us the money. I thought we were the customer. We had maybe occasional disagreements about that. And so we were customers of venture capital. I first raised venture capital in 1995 with my partner, Jim Clark, from John Doer, who was actually,

you know, an excellent BC for us at Netscape, and then we raised money from Benchmark in 99 for LoudCloud, and that went really well. And then between Ben and I, we also helped probably 100 friends of ours over the course of sort of a 15-year period raised venture capital. You know, we were angel investors, or we would just, we would help our friends go through it. And so we kind of, you kind of viewed, like, I was like almost going to the same department store every day for 15 years or something. After a while, you're like, you know, I think maybe I could do this. this and I think maybe I have a few ideas from being on on that side of the table. So we started really thinking about entering the business and then we thought really hard about, you know,

the traditional way to enter venture capital is to join an existing firm because the history of venture capital is that the successful firms have all been around for 30 or 40 years. And we consider that and then we basically got bit by the startup bug, me for the four and a half time, and we decided that it was actually a good idea for a startup. We spent about a year and a half actually thinking about Andreessen Horowitz as a startup. And we spent a lot of time studying the models and talking to people who had been in the industry for a long time. And we ultimately resolved on what we thought could be two big differences. One was actually a little bit of a back-to-the-future thing, which is we decided that the general partners and Andreessen Horowitz would all be people

who had been founders or CEOs or both of tech startups. And that kind of sounds like it might be obvious. Like if you're going to have somebody on your board and they're going to give you advice on what to do in your company, that maybe it would be helpful if they had actually done it before. It actually turns out, first of all, it had been a good idea in the 60s and 70s. The top BCs in the 60s and 70s when venture capital was created, had for the most part all been operators. And they had been legendary characters. Gene Kleiner had been one of the famously one of the Fairchild, one of the original Fairchild people,

one of the famous Traderess Eight, left Shockley to start Fairchild, left Fairchild to start Intel. Tom Perkins had actually been a general manager at Hewlett-Packard, which was actually at the time a source of a lot of the CEOs of the new companies in the Valley. And actually himself had been a founder. He started a laser company, which was the kind of thing people did in the 1960s. and he actually raised venture capital himself and was a founder. Don Valentine, you guys had, I think Mike Morris here last year, the founders of Sequoia Capital were Don Valentine, Pierre Lamont,

both of whom are famous Chip executives and entrepreneurs. And so it actually was how venture capital got formed. Our analysis was basically over the course of time, a lot of the traditional venture capital firms had evolved where the successors to the founders were, in many cases, very successful investors, but were people who had not started and built companies themselves. And so we kind of decided to bring that idea back.

The other big idea that we had that we've really pushed hard is the idea of giving founders, and especially founders who have not been CEO before, we use the term sort of give the founder superpowers in the form of basically the world's best network. And this is an observation that we made when we, you know, we've seen over the years, we've seen founders start companies, and then at some point the founder gets fired, and you bring in a professional CEO. One of the questions we always had is, what's the catalyzing thing that causes the founder to get fired?

And then what is the new, what is the professional CEO? So the professional CEO is always a type, right? It's always like, you know, square shoulders, blue suit, six foot two, great hair, fantastic teeth. Like, it's a type. And what do these professional CEOs have that the founders didn't have? And actually, some of it is they have experience running a company, and we think we can help with that. But the other part is they have these networks. They've been in the industry for 20 years longer.

They've got 20 years worth of basically network built up, right? And so they know customers and they know other investors and they know all the big tech companies. And if the company used to get sold, they know all the buyers, and they know all the reporters to cover the space. And they know all the, if it's a regulated business, they know all the government regulators. And so they just, they have these giant networks that they've built. So what we decided to do in our firm is basically essentially pre-billed the best possible network that any startup could have. And then basically let our founders plug into it and basically get the superpower of having a giant network. The way that we did that is we actually have, we have a very kind of non-traditional structure.

We have full-time professionals in our firm who are not general partners or investing partners, who are operating partners in six teams that build and run networks across categories, customers, investors, acquirers, executive talent, engineering talent, PR, and now policy and regulatory affairs. So we've got 85 people in the office every single day, and what they're doing is they're basically building a grooming network on behalf of the firm, which then works on behalf of all the portfolio companies. And Richard Schnaz is actually a network as a service.

Yeah. So then one interesting point is E6 and Z was actually started in, you know, O.AXNZ, 2009, it's been like seven years now, right? And the industry has changed, you know, the firm has changed, VC more broadly has changed. What are your thoughts on kind of that evolution? Well, I would say there's been more change in venture capital in the last seven years than probably in the preceding 20. And I'd also argue there's probably been more change in the tech industry in the last seven years than probably the proceeding, at least 15 or 20. There's a bunch of new firms now that people are starting that are exciting. Another thing is seed investors,

angel investors have always been important, like a big part of the history, the Valley the willingness of people who have made some amount of money to write a check and sort of fund the next idea. And a lot of the original companies in the valley, there was angel money involved. And so angels have always played a very critical role. In the last seven or eight years, it feels like a lot of the angels actually have become professionalized. And when they do that, they rename themselves angel investors to seed investors, because angel kind of implies an individual, whereas seed kind of represents a sort of an investable asset class. And so a lot of the best Angels have now actually raised funds instead of just investing out of their own pocket and they actually run these seed firms.

And so actually we see kind of a restructuring happening in the industry where a lot of companies, companies used to just raise venture capital as their first round. They would just go straight and raise a series A and you could either raise a series A or you couldn't, but it was only a very small percentage of founders could raise an A round right out of the gate. You know, these days it's much more common to raise a seed round, you know, raise $500,000 or a million or even $2 million as a seed round and then go for a year or two or three before you actually have to raise full venture capital. In fact, the seed phenomenon has now gotten so widespread that now the seed investors are trying to differentiate against each other. So now there's, now there's seed, there's also pre-seed, there's seed extensions, there's post-seed, there's early A. And then actually below all of that, there's incubator, accelerator kind of phenomenon. And so we'll actually sometimes meet companies that have raised like five rounds of seed capital in different forms. And so there's just a lot more support in the infrastructure for a much larger number of new companies.

I think that maps to what's happened in the industry over the last seven or eight years, which I think is really remarkable. Either we're just taking it for granted or we haven't really wrapped our heads around it, which is the valley, the history of the valley for 50 years from, so 1960s through the mid-2000s, you know, the valley was kind of the best place in the world building, you know, literally computers. So chips and then computers and then software that runs on computers. But fundamentally building tools, right? Computers or software as tools.

And then we would, you know, these giant companies, Oracle and Sun and Cisco and so on, would build these great tools and then would sell them to the customers and the customer might be a consumer at home, but the customer more often was a big bank, right, or a big insurance company or, you know, a hotel chain or somebody like that, or a car company. In the last seven or eight years, post the financial crisis, something has changed. Either the valley is about to grow to become a lot bigger and more important than the valley's ever been, or we are completely smoking crack. Many value companies still build technology and sell the technology as tools, but a lot of the best new Valley companies build technology and use it as a wedge to enter an end market, right? And so as an

example, the predecessor company to Uber was not, you know, a ride-sharing service that failed. The predecessor company was a little boutique software company that built dispatch software that got sold to taxi cab operators, right? And there actually were companies that were in that business. It's just, it was a tiny little business because it turns out taxi cab operators actually aren't that excited about adopting new technology. They don't buy very much IT. They don't buy very much software. If they did buy software, they wouldn't know what to do with it. And so that was just never a very big business. And so Uber and Lyft just come in and basically say, let's just do it. Let's just provide the ride. Let's take complete responsibility for the customer service. Elon Musk, of course, has pushed this to its logical

conclusion, which is, you know, why not just built the car. I think that Elon gets tremendous credit, both for the car company and the rocket ship company, both of which are things that nobody 10 years ago thought was possible to build either kind of thing as a new company, and it turns out that it is. It feels like the valley is really expanding, basically, certainly expanding an ambition, and quite possibly, we believe, expanding a capability to be able to actually go directly into a lot of markets that historically you would have viewed as, you know, much more of the province of existing banks or existing car companies or existing incumbents. I think a big part of that is actually the fact that if you're selling IT to somebody versus

actually using it yourself, you can just recognize the benefits, you know, more obviously. Like, oh, if you've got your entire thing in a database, well, you can push out like a report of all ride times and so on and so forth, then they can understand and think about data, but the customer wouldn't necessarily do that. So it's a major efficiency. If you're selling technology to a company that's then implementing, it's a layer of indirection. And there are companies. I mean, look, there's, you know, Oracle got built to do this, and a lot of Oracle customers have

gotten great results with Oracle. And Salesforce.com just had a great quarter. And, you know, they sell their stuff to lots of companies with big Salesforcees who do great with it. So it works. But, yeah, we see this sort of, the term we use this full stack, which is, we sort of see there's a particular magic, exactly to Bologi's point. There's a magic that kicks in when you actually have complete responsibility for the end

customer experience and how the product or service is delivered. And then especially these, days, right, in the era of big data and machine learning and all these things, there are things that you can do to optimize both the experience and then ultimately the economic model of the business. It's become a very open question or a topic, okay, so how many industries are opening up where you could possibly do, you know, the equivalent of an Uber, Airbnb, or a Tesla in these industries from the Valley. I guess let's start time for questions, yeah?

Hi. So, I'm for a first-time founder who's bootstrapping a V-1 product, when do you think is the most appropriate time to first approach investors? at what level? Is having a business plan and a team reasonable, a prototype to show potential, or a demonstrable customer traction? Thank you. Yeah, so it's hard to give general advice because it really depends, but unquestionably, it's better to have something working. Coming in with something working is a gigantic edge over coming in with nothing working, like a huge edge. Even, by the way, for people who have done it before, people who have successfully ran companies before, coming in with something working

is a really big deal. And then it is like absolute magic. I mean, it's like catnip to VCs. if you can walk in and you've already got both the product and customers. Just rub it on us and it'll drive us crazy. And this is another thing. Probably what's overestimated right now is just raising lots of money to be able to save, raise lots of money. Probably what's underestimated is the bootstrapping process of getting in position with the core thing that you're doing

and both the product itself and its value to customers before you start raising a lot of money. And with that customer traction and MVP already, like what level, Angel seed A? If you're a first-time founder, first-time founder, it's almost always better to start with angels or with the early seed investors. It's, again, contrary to the myth and archetype,

it's very hard for the first-time founder to raise a straight A-round. It's almost always the case that they're coming up through seed. I mean, as an example, you know, Mark Zuckerberg raised literally angel money from Peter Thiel was how he got started. He didn't go out and raise an A out of the gate. Sergei and Larry, same thing, they raise angel money. And so I think that that's almost always the best thing for a first-time founder. Thank you.

You mentioned all the progress in AI and new input output and all the language processing. So I have a very, if you had to pick, In third years, what's the chance that we have a bot that does a better job in picking companies than Andrewson or always? I hope to God we invest in it because it'll be the last investment we ever make. So, I mean, this idea is out there, right?

And so there are actually people literally trying to do this. And there's actually a venture firm called Correlation Ventures that literally is trying to do this or a version of this. And then, you know, there are people who are like data mining angelist and trying to figure out how to do this. and there are other people who are going about this. The computer science, computer scientists in me, would engineer me would like to believe this is possible,

and I would like to be able to figure it out, and I'd frankly like us to figure it out. The thing I keep running up against, the cognitive dissonance in my head that I struggle with, is what I just see in practice, talk about in theory versus in practice. Like in theory, you should be able to get the signals, like, you know, founder backgrounds and this and that,

progress against goals or whatever, customer satisfaction, you should be able to measure all these things. Well, we just find what we deal with every day is not numbers, right? And there's nothing that we'd be quantified, but we deal with every day. idiosyncrasies of people. And under the pressure of a startup, like idiosyncrasies of people

get magnified out to like a thousandfold. Like people become like the most extreme version of themselves under the kind of pressure they get under a startup. And then that's either to the good or to the bad or both. But people have their own issues and then the interpersonal conflicts between people. So the day job is so much dealing with people that you'd have to, you'd have to have the AI bot that can like sit down and do founder therapy. Maybe. Yeah, I mean like just... My guess would be we're still ways off. Yeah, like just to add to Mark's point of that, I mean, the fundamental issue from like a machine learning standpoint is you have a very few events that are most of your returns, which are like these Facebook-like outcomes, right? And so it's like almost like a rare event detector like the large Hadron Collider, right?

You've got all these particles coming through and you have to be able to predict, okay, which one of them is actually going to make a lot of money. That's number one. Number two is, especially at the very earliest stages, you don't have features in the traditional sense, like you don't have a lot of really good data to work with in terms of prediction. So the later it gets, probably like Series C or thereabouts, you have enough systematic data to work with, but early on it's actually pretty challenging. Hi, thank you. How are you guys thinking through your fund structure

and the types of investments that you have to make as you raise more money? And can VC be like a winner-take-all market? There is a bunch of challenges to it. The central challenge is any top-end venture capital firm that has a reputation that it wants to maintain, which is, I think, very important. Can only invest in one company in a category?

You can't, practically speaking, invest in competitors. The company you've already invested in will feel its betrayal if you invest in the new one. And then the new one will think if you're willing to invest in them, you must be very dishonorable, that you're willing to betray your previous one. So it just, it doesn't work. And so, like, the minimal number of venture capital firms has to be the number of firms required to fund the number of competitors, right, in each new market. And then we can debate is that three or five or 20 or 40 or 100?

And, you know, certainly we have too many venture capital firms. Like, we've got, like, 500 venture capital firms in the U.S., and certainly there aren't 500 competitors in every market, or at least, There need to be at least a half dozen, dozen, 15, you know, good firms to fund the competitors. We would love to make venture capital and winner-take-all. I have a question with regards to blockchain in the financial services industry.

So it seems like there's a lot of low-hanging fruit and a lot of far-fetched ideas that one could pursue using blockchain. I was wondering, like, what advice would you give for someone who's trying to see what is the best, I guess, niche area to target when you're given such a wide array of potential use cases for the blockchain. Yeah, so we actually shy away from giving advice like that. So there's two reasons for it.

So one is there's a concept called product market fit, right, which is become fairly publicized now, you know, right product in the right market. There's another concept we call founder market fit, which is the founder of a company, is that the person who's born to do that idea? And so that question we tend to defer to the founders because we figure the really great founders

are going to figure that, like part of what makes it founder great is they're going to figure that out. The other thing we found is that it's very, very hard, if we have ideas for companies we like to fund, but we try not to talk about them too much because we don't want somebody, we don't want founders who pick up somebody else's idea. And it goes back to what biology said, which is it is so hard to make a startup work. You have to be so irrationally committed to it. I mean, this is another thing. Like, startups are over-glorified in the sense of, like, people think they're fun. Like, they're not fun.

Like, they're not even remotely fun. Like, they're punishing as hell. I think it's Bill Lee for at Lawn Moss. It's like chewing broken glass and staring into the best. That's right. It's starting a company is like chewing broken glass. It's like, after a while, you start to like the taste of your own blood. Yeah. It's a very vivid quote. Yeah.

But like it's so hard and it's so hard because people are saying no to you all the time. It's just no, no, no, no. Constantly being told no. And then, you know, and then your idea is stupid and like I would never do that. Why would anybody do that? And so their company's going to kick your butt.

And then your lead engineer quits. And like there's, it's just like endless. It's got to be an idea that they feel so deeply about that there goes to like biology's term ideological mission. It's got to be something where people feel so deeply that they have to do it, that they're willing to tolerate the level of pain. And in our experience, most people aren't willing to tolerate that level of pain for somebody else's idea.

And so I respectfully declined to answer the question. Okay, I see. No, it just seems like for blockchain, like there's so many use cases. And like, for many of them, like the timing could be completely off. Whereas, for example, like, for like remittance payments, like one could easily see how that's a very easily applicable, like, use case of blockchain. So, yeah. I'll come on on this briefly.

Basically, I think that remittances are to Bitcoin, what VoIP was to the internet. In the sense of it will work at some point in the first five years or 10 years of the thing, it's not high enough quality with the obvious alternative, namely VoIP versus Landlines or Remedances versus a legacy remittance system to win. I think that, you know, Bitcoin, like Bitcoin as opposed to blockchain, but Bitcoin is good for transactions

that are very large, very small, very fast, very international, or very automated. And you have to try to envision transactions that are like two, three, four, or even more of these kinds of things to think of things that cannot be done with the current system. If you think of things that cannot be done

with the current system that are still useful, well, then that's 10x, right? So that's one way of think about it. The other way I think about it is like Evan Williams' thing, which is sort of vague, but it's actually very useful. So on the one hand, oh, a new technology 10x, something what people haven't done before. On the other hand, Evan Williams' thing is take a behavior that humans want to do and allow them to do it faster, better, cheaper, over and over. Take something that was once a rich man's thing and make it accessible to the middle class or take it from the middle class and make accessible to everyone, right? And so if you kind of combine those two things, the technology allows you to go and in a way that was not possible.

So I think, you know, hunt in that general area. That might be something. Thank you. I co-founded two companies that faded into obscurity too quickly. You identify problems and issues and opportunities that might take a startup, you know, weeks, it's not months, it's not years to identify. And I'm kind of curious why Injuries and Horowitz and others

don't explicitly identify opportunities and problems or even issue challenges or competitions. And so I want to delve in a little bit deeper. One of the things you've been talking about, more specifically, is like the cloud versus the land and the increase, you know, software in the world, like the emergence of the cloud. And I'm kind of wondering in that world where ownership seems to be more centralized, there could be some risk associated with that.

I'm wondering if you could speculate about ownership in the future. I'd be interested, especially talking from a blockchain perspective on asset management. So there's two separate questions there. I think the first one is why doesn't VC pursue like an XP-style model? That's one. And then number two is what happens with like the future of ownership, right? Kind of interrelated. So the first one, I actually think.

to be a very interesting model for a fund. The reason I think that's interesting is one of the points Mark made is, and it's one the most counterint of points about VC, no matter how innovative it is an idea that comes across your doorstep today, there'll be two more like it. My best example of that is Hyperloop, right? So Hyperloop company comes across

our doorstep, and like a few weeks later, we have like two more that come in there. And so what it means is that VC is all about filtering winner take all. So the more that you can kind of push the tournament to inception, the more you can push the tournament earlier and earlier before you invest, the better. So a prize model, I think, could work. The problem is, of course, grading the prizes, judging the prizes, all the type of stuff.

That's one. Number two, in terms of the future of ownership, I do think that basically the interface to every physical object will be ultimately digitized in the sense that you won't own a car. You won't have, you know, so we already don't have books. You have Kindle, right? And you don't have a house. You have an Airbnb and so on and so forth. And all that stuff becomes extremely mainstream. And what that means is that actually your mobility is vastly increased.

And right now we think of mobile as, oh, I can just go to Starbucks and I can work from there and it's as much as I could work at home. But I think in the next five, ten years, it's going to be as easy to just jump up and move to another country as it is to just go down the street. What that means is the more internationally flexible you are. So one of the big aspects of that, by the way, is the bank accounts that impacts a blockchain aspect. One of the big things that's a pain moving between countries, your Gmail works, your Facebook works, all your Internet services work. Those are IP-based, right? But all the nation-state-based things, like your bank account, are not quite as portable or as easy. And so those kinds of things, I think it's useful to identify all the prerequisites.

So as a thesis for kind of startups to look at, chop the things that anchor. people to land. I think you'll have some interesting things there. Hi, this question is for biology. I'm a freshman studying physics at the University of Illinois, and I was just wondering, what convinced you to continue on to do a PhD, and what were the skills that helped you on, like, in regards to entrepreneurship and whatever you're doing today? So, I would not do a PhD today, so that's my, that's my quick answer. So why did you do a PhD? Why did I do a PhD? Because I wanted freedom in the sense of I wanted to do math and, you know, computer science and so on my own time, right? But what?

What I would have done instead is I think the single most important metric for you guys to measure is your personal runway. In Silicon Valley, people think a lot about, you know, okay, how do I get an exit and get the money on top? But they think much less about how do I minimize my personal burn. So today in the world, it is possible to just find a jurisdiction that is amenable to your preferences, that is warm, that is safe, that has good internet. And it's really, really cheap. And so, you know, what I would do instead of getting a PhD, if I was just doing it today. First I'd work for a year at a Google or Facebook or a GitHub, I would. have a job that permitted remote work, I would sacrifice the advancement to be able to work

remote for the next three years or so on, and I would just save enormous amounts of money and live very, very cheaply. Every year that you work, you've got three years of runway. And so that's actually freedom once you have the ability to have like three, four, ten years of runway and you have the discipline of the grad student, but the earnings of an engineer, right? So that's what I would have done instead. So I wouldn't do the PhD. I think you can learn and self-learn faster on the internet than you can in grad school. I think a bachelor's degree is fine, like I'm not saying drop out or what have you right now, at least.

But I think you can do better than a PhD today. So I've got a question for biology. So biology is for those of you who know him by reputation or know him. Tonight he's done this. Very big advocate for entrepreneurship outside the valley. Very big advocate for a developing world entrepreneurship. Very big advocate. Why am I still here?

In this case, for actually literally moving from here to someplace else. I can't help but point out that biology, lives. Where do you live? Yeah, I know. Unfortunately, I'm in San Francisco now, but, but, but. Interesting, interesting. Interesting. Literally, like, if you drew like a circle around San Francisco, he's like right in the middle. Let's say that sometimes you have a goal that you have, it takes a while to get to because

there's a bunch of prerequisites that have to be met. Right. He's working on. He keeps saying he's thinking about it. I'm working on it. All right. He also, though, he now is married and he has a lovely little baby. I do, I do.

Those are all anchors. And the two of them are going to have. I think they get votes. They get votes. It's my understanding of how this works. they get to contribute to the decision. Thanks, Mark. I'm from China.

I work for Google China. I'm now a current student in the Stanford GSP. I'm really inspired by the entrepreneurship here. But I know there's a lot of challenges for the immigrant entrepreneurs to start the company here. So I want your advice for the immigrants' entrepreneurs here, especially for the first time. Right. I'm going to turn that question over.

Sure. Okay, yeah, sure. To the immigrant entrepreneur on the stage. Yeah, yeah, sure. So I've thought about this a lot, and I've discussed this with Mark and Ben a lot. What comes after the dorm room entrepreneur is the developing world entrepreneur

and the immigrant entrepreneur, but especially in the developing world. And I think, you know, one thing, depending on what country one is coming from and so on, obviously, there's a wide range. But for someone coming out of India, for example, frequently making $100,000 is like making a million dollars in the sense of, like, the impact on quality of life and so on, right?

And there's actually a much lower risk ways to make $100,000, thousand dollars than to do a startup which is just extremely stressful and you're going for infinity and so on right and so um i think that we're going to see new kinds of things particularly as you get another billion two billion people with cell phones right like that i think we're going to see new kinds of business models that are based on knowledge that folks outside the us and in the developing world have about their local economies and also have maybe less in the way of upside more predictable returns and they're not quite as much of a you know roll the dice kind of thing in some ways If you start at zero, it's easier to get to infinity

because you just have nothing to loose. Good, good. Thanks, everybody, for coming.