Invest Like the Best with Patrick O'Shaughnessy - Matt Clifford – Investing Pre-Company - [Invest Like the Best, EP.154]

Episode Date: January 14, 2020

My guest today is Matt Clifford. He’s the co-founder of Entrepreneur First, the world’s leading talent investor. They invest “pre-company” by helping the best people in cities around the world find a co-founder, develop an idea, and start a company. So far, they’ve helped 1000 people start 200 companies worth a combined $1.5B. This conversation covers their entire ecosystem and holds lessons for anyone building a business. I especially loved Matt’s ideas on the history of ambition.   Please enjoy our conversation.   For more episodes go to InvestorFieldGuide.com/podcast. Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub. Follow Patrick on Twitter at @patrick_oshag   Show Notes 1:20 – (First Question) – An overview on talent investing 4:37 – The history of ambition 10:08 – How do they search for ambitious people 12:21 – What happens early on for these formed teams 17:43 – Assigning an idea to a talented team 20:52 – Opportunities in deep technology 27:16 – A closer look at the hardware and machinery of the deep technology changes 30:54 – The geographical focus of venture capital investments 37:16 – Problems with the way early-stage investment world works 41:22 – People who are creating value in a management company and how they manage their investments 55:12 – Advice to people creating investment companies and pricing power 1:00:31 – The power of cities 1:02:46 – Topics they cover in their newsletter; technological sovereignty as one example 1:04:11 – Experience and thoughts on China             1:06:51 – A.I. Nationalism 1:12:03 – Kindest thing anyone has done for Matt   Learn More For more episodes go to InvestorFieldGuide.com/podcast.  Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub Follow Patrick on twitter at @patrick_oshag

Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest like the Best. This show is an open-ended exploration of markets, ideas, methods, stories, and of strategies that will help you better invest both your time and your money. You can learn more and stay up to date at investorfield guide.com. Patrick O'Shaughnessy is the CEO of O'Shaughnessy Asset Management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaunsi Asset Management. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaunacy Asset Management may maintain positions and the securities discussed in this podcast. My guest today is Matt Clifford. He's the co-founder of Entrepreneur First, the world's leading talent investor.

Entrepreneur First invests pre-company by helping the best people in cities around the world find a co-founder, develop an idea, and start a company. So far, they've helped a thousand people start 200 companies worth of. a combined $1.5 billion. This conversation covers their entire ecosystem and holds lessons for anyone building a business. I especially loved Matt's ideas on the history of ambition. Please enjoy our conversation. Well, Matt, this is going to be really fun, a completely unique conversation relative to a lot of the ones that I've had. Since you're doing something so unusual, maybe you could just start by explaining what it is that you do. And then we've got seven or eight topic areas to cover. Sure. So entrepreneur first is a firm that I started with a really

good friend of mine, Alice, about eight years ago, to do what we think is a totally new kind of investing. We call it talent investing. What is talent investing? Talent investing is basically the thesis that the world is missing out on some of its best founders. And so our job is to go and find those people before they have a company, pay them to quit whatever they're doing, literally like a salary with stipend, spend three months working with them, crucially putting them in a group of people like them, sort of bootstrapping a little bubble of Silicon Valley somewhere else in the world, helping them find a co-founder from within that group, helping them select a high potential idea. And then if there's something at the end of three months that looks promising, investing in

that company and then supporting them to raise C capital. We started in 2011 in London. It was a pretty out there idea, but this year we'll fund 1,000 individuals around the world across Europe and Asia. It's fascinating because it's like an entire funnel that exists prior to the normal funnels that you would consider in investing, even early stage investors. which begs the question, how do you begin to identify the talent? How do you begin to find the right people to convince to quit their jobs? One of my somewhat controversial beliefs is that there are a lot of vested interests in the world of entrepreneurship about kind of pretending that founders are really, really unusual. It's a story that founders love. It sort of creates some magic around it,

but actually talk to people who've been doing this for a long time. You say, what do you look for in a founder? And you hear them list things. And then you imagine asking the same question of, say, a public markets investor about what makes a great CEO. And you know what? They're somewhat similar. And there are some differences, and I'm not trying to pretend it's exactly the same. But one of our beliefs is that actually the biggest driver of who becomes an entrepreneur is actually culture.

And so I guess one of our starting points was, what should the most ambitious people do with their lives? One of our beliefs is that the reason Silicon Valley is so special is that in Silicon Valley, it's the one place in the world where the obvious answer to that question is, we'll start a company. Everywhere else, the answer is somewhat different. It's culturally determined. and the answer to that question in each place has a really big impact on what happens to the economy and society of that country.

So the reason this is relevant to answering your question is the first thing we do in a new location is we say, well, what's the most ambitious people do now? And then we kind of go to those places. So over time, what we've developed is a methodology for really evaluating ambition, skill, resilience, and sort of intellectual horsepower. And actually, it's somewhat predictable. Why does the UK have such a financial services-driven economy? Well, basically, because for about 30 years now, if you walk around Cambridge, Oxford, LSE, and ask the smartest undergraduates, what are you going to do next? They're all like, oh, I'm going to go work at Goldman Sachs or whatever. And you multiply that out over a country.

You get a big financial services industry. Why does Singapore have the world's most effective civil service? Because you walk around the National University of Singapore and say, hey, what are you going to do? And they're like, well, obviously, the number one job would be to go and work in the prime minister's office. And so one simple answer to your question is we just look very hard at what ambitious people are doing because they haven't yet thought. that starting a company is a normal, legitimate, acceptable, exciting thing to do.

There's 7,000 questions and follow-up that we'll get to, but this idea of ambition is so interesting. Before we hit record, we were talking about topic area that I've never considered, which is the history of ambition and how that matters for what you're doing and kind of where we sit today, both for investors, but also for talent. So can you weave this kind of a thousand-year history of ambition for us? Yeah, so our view is that ambition is probably the most underrated force in understanding how the world changes. And that's because ambitious people across all time and all space, as far as we can tell, are driven to find leverage. Wherever you grow up, whatever you do,

if you're ambitious, you're going to look around you and say, what is the resource that I can acquire that will maximize the amount of impact I can have in the world? Now, fortunately, in 2019, we'll come to 2019, there are lots of great answers to that question. But the reason I think you should take a millennial level of view is, let's rewind a thousand years. Let's imagine you're born in rural England in the medieval period. What are you going to do? If you got luck in, your dad is lord someone, fine. But actually, what does ambition mean if you're born the son of a butcher in a little town in the east of England? Well, actually, our generalized answer is, in every era and in every place, there is a dominant what we call technology of ambition.

What is technology of ambition? It's the thing that gives the most leverage given time and place. So a thousand years ago, the answer was actually literacy. If the difference between able to read and write a thousand years ago and not was the difference between having any sort of scale in your actions and not. If you couldn't read or write, your impact was limited to who did you know in your village and what could you get them to do. If you couldn't read and write, you can send a letter to the bishop. You can send a letter to London.

You can write things down that people have to do. And so what you see around a thousand years ago is the emergence of literacy as a tool of ambition for the most ambitious people. And the reason I say the son of a butcher in our... a little rural town is one of the most striking buildings in the whole of London, is in southwest London, this amazing palace called Hampton Court. It was once the biggest private residence in the whole of England. It was built by a guy called Thomas Woolsey, who was born in Ipswich, a little town in England, the son of a butcher, absolutely no prospects, but he found

his way into a new kind of institution, which was a cathedral school. He learned to read and write, and that became a technology of ambition that eventually saw him become the most powerful person in the country. He's better known as Cardinal Woolsey. He was the person that tried to get Henry the 8th, one of his divorces. And he became, obviously, massively stylizing his story, but the point is, literacy was the number one way for non-noble, ordinary people to get leverage. You fast forward 500 years, that's clearly no longer the case. You look at someone like Napoleon. What was Napoleon's like technology of ambition? Well, by then, actually, military command was a technology. If you look at the history of what non-nobles did in sort of 18th century France,

actually a lot of ambitious people saw going through the military as a technology of ambition. It gave leverage. And so he went, again, to new kind of institution, start just a few decades around when he was born, which was the Ecul Militaire in Paris. He learned to be a general, and the rest is literally history. Fast forward another couple of hundred years, I would say the dominant technology of ambition of the 20th century was probably finance. If you could write a check in New York, that reverberates around the world. It's no longer a question of it being good enough to read or write or to command. You have to know how finance works. I think when you fast forward to today, it seems very obvious to me that the dominant technology of ambition,

If you're a 22-year-old today coming out of college, you want to maximize the leverage that you have, it strikes me that technology entrepreneurship is totally unprecedented. In terms of the scale, I always say Napoleon would be green with envy if you could see the reach that Mara Zuckerberg has. No one in human history reaches ever reached as many people as Zuckerberg does every day. You look around every sector of the economy and increasingly you see that most impactful people are people that have the power of technology to expand their reach. And so we always joke to people that join us a thousand years ago, you've been training to be a monk, not because you're especially religious, but because that would have been the way that you would have sought ambition. For us today, we think that's why people are going to many more people than say 20 years ago wanted to be entrepreneurs, we'll be wanted to be entrepreneurs today. But, and this is where we come in, when you look at these phase changes, whenever the technology of ambition changes, what you see is that a new kind of institution starts to emerge.

What those institutions do is they harness this new technology of ambition and one make it much more widely available than it was before, but two, amplify the outcomes of the people that go through it. So actually the rise of universities was sort of in response to literacy. Literacy became a thing and so you needed more institutions that could kind of teach it, but also amplify the outcomes and the opportunities for the people that did it. Military school in the same way, business school in the same way in the 20th century. And we felt that there was a missing institution today. And that's really about how do you make technology entrepreneurship a viable career path for the world's most ambitious people. Now you could look around and say, well, come on, that already exists. That's what seed funds are for.

That's what I combine is for big fans of both those things. But the interesting thing about both those things is they assume away the problem of how people start companies in the first place. And so if ours, you think the most important unit here is the individual. How do individuals growing up wherever they are in the world come to access the opportunity that will give them the most leverage? you can't have a filter on, well, cool, well, come back when you found a co-founder, found an idea, got a product, got some traction. You have to be able to harness the raw power of individual talent and ambition. And that's what entrepreneur first is.

An unbelievably interesting history. And now I'd love to talk about how you do all this. So I get the application of ambition is sort of the ambitious type searches for leverage. How do you search for the ambitious type? What are the markers of the ambitious type? Yes, we have, I would think of it as channels. We have three channels that we think about in finding these people. The most obvious one is we've been doing this a little while, being fortunate to have some relatively prominent successes,

and that means that now we're something of a magnet for these people. I think particularly if you're an aspiring CEO that knows that they need a world-class CTO in order to achieve your ambitions, I think we're the best place in the world to find that. Partly because if you go talk to most VCs, they'll tell you, if you Google how to find a CTO, It's one of the most derided questions on the internet. The answer broader that people give is, ha, if you don't know one, more full you. That's a crazy thing to say to a world where we know

that bringing these two skill sets together is a really powerful thing. So we don't say that. We say come to entrepreneur first. So I'd say a big chunk of these people today come to us. That's the first channel. The second channel, which has only started to exist as we scaled up, is actually referrals. I talk a lot about network density.

We're a big, big believer in creating network density. What turns out to be great about this business is great people know great people. And broadly, people have a really great experience at entrepreneur first. And so when they graduate, actually recently did an evaluation of where do all our best CEOs come from? Huge number of con because someone they knew did the program before. Now the third channel, which I guess is the one you're really getting at and is probably the most interesting is we do massive talent scouting at scale. So we probably employ 30 people full-time talent scouting around the world. Their job is to make friends with professors at universities, to go find

student leaders, to be at the right events, to find really differentiated access to talent. And what we do not believe in is persuading people to be entrepreneurs. That would be crazy. That's the one piece of conventional wisdom that I subscribe to. What I do think is showing the opportunity. I consider it the same as turning up in Ipswich and saying, hey, have you heard about literacy? You should not persuade someone to learn how to write. But to the person that it's right for, it will be a very obvious opportunity. And so what we find is actually sourcing these people, almost like a head hunter, but monetized by charging a fee, we monetized by investing in their companies. That's sort of actually been where some of our most impressive people have come from.

I think people will be familiar with sort of the accelerator or incubator model, the tech stars, the YC you've already mentioned. Tell me what you do to collide these people once you have them, very specifically, like in what kinds of spaces for what lengths of time. You use this phrase investing pre-company, which is a great phrase. And not what I've heard before, right? So it tells me you're doing something unique. So what is the primordial soup to begin with and how important is that? So we believe that physical co-location is really important, at least to begin with.

So you think of entrepreneur first as two, three-month segments. There's three months where people come in as individuals and the goal is by the end of the three months to have a co-founder. If you have a co-founder at the end of that, we're happy, you're happy. At that point, we have to decide these nascent teams, is there something there? Is it worth their time, which is actually our biggest concern? their opportunity cost is or should be very high, and is it worth our investors' money to actually take them a little bit further. For the ones where we say yes, we then spend a further three months,

so a second segment of three months, which, in that point, it is much more like a conventional accelerator. We're really just helping them develop the business model, find some early customers, get ready to raise seed capital at the end of the sixth month, so three plus three. But I guess the most interesting bit is the first three months because that's very different. So how do we do it? So there's a few learnings that we've had from doing this many, many times over the years. So I think the first embarrassing mistake that we made early on was saying, okay, so the whole value proposition is find a co-founder. We've interviewed all these people. They don't know each other. So we should matchmate them. We know way more than they do. So I remember

actually drawing out with Alice on a sheet of paper, oh, you know, John can co-found with Sally sort of thing. This is a total disaster. I mean, we were terrible at it. I do not believe. Maybe we'll eventually invest in a company that can do this with some sort of machine learning model that's a lot better than we are, but we no longer believe at all that you can top down, say, who should work together. So instead, I think the way I would usually frame is people say, how do you build good teams? We say, well, we just build lots of them and help break the ones that are bad, and the ones that are left are good. And it sounds facetious, but it really works. So a lot of what we do and a lot of the value, I think we add for the founders, is we create a new set of social norms that exist only in the

bubble that is entrepreneur first, in that physical location, in that city. An analogy that my co-finding Alice users, which I really like is she met her husband online on OKCupid. When she first took him to meet her parents, she wanted him to tell the parents that they'd met at a bar because it was embarrassing to meet online. And she's married to him now. She's like, in retrospect, so crazy, why would it be better to meet at random in a bar than have this carefully filtered matching process? That's sort of how we think about co-founding.

We think one day people will go back and say, we let these important resources of highly innovative companies kind of come down to who went to Stanford with whom? That's crazy. we can do so much better than that. And so one of the norms that we've had to create that is unusual within Entrepreneur First is if you and I were starting something afresh and we decided we might want to work together,

we'd have a very high bar to making that decision, which would mean that we'd then have a very high bar for reversing that decision. It'd be really awkward. It's actually something that we see happen outside Entrepreneur First with teams where people are kind of selling. They're working with a friend

because they're the only person they knew. Actually, the friction of getting out of a bad team is one of the most damaging things. I think in a co-founder's trajectory. It's very under-discussed because VCs don't observe it. By the time that's a problem, the VCs probably already passed. This is everything that happens before people turn up on your doorstep. So what we do, and this is the only really, I think, kind of smart bit about team building

is we just say, get into a team quickly, don't overthink getting into the team, test it only by the artistic of productivity. And this is our big, big learning, by far the most important predictor of success in that first three months when you don't really know what they're going to work on. It'd be crazy for us to be like, ah, we like them, but the gross margins on this sound low. I mean, they had 12 weeks in and they only met 12 weeks ago. That would be a ludicrous way of thinking. What you can absolutely say for sure, though, is there is no such thing as a good team that isn't productive. And broadly, there are very few productive teams that aren't also good. So what we say is get into a team in week one,

don't overthink it. Set yourself a goal that you think is commensurate with what you operating at max productivity would look like, and then in some very short period of time, maybe a matter of days, decide whether or not you're operating the best version of yourself if you are stick with it. If not, twist. And actually lowering the bar to saying, you know what, Patrick, you and I shouldn't work together. This isn't working. That is super valuable. Because it means that on average, people iterating through teams really, really quickly. So that sounds good, except then the critique we get a lot is like, well, these teams must be the most flaky, fragile things, they must just break up all the time.

I think what's interesting is if you actually put the default to be no, as in default, don't work together. Default every week, someone from entrepreneur first is going to say to you, this probably isn't the right team for you, right? Are you sure? If you get to the end of 12 weeks where every couple of days, someone's like, get out this team, get out this team, and you're like, no, they're actually pretty robust. Obviously, we do have co-founder breakups.

I like to survey seed funds and say, what proportion of your seed investments lose a co-founder before Series A, it's actually pretty high. The average number I would say people give me is about 20%. So in our data, if you make it past six months of EF, only about 10% of the team is a co-founder. And I think it's just that if you reverse default on to default off, you actually create a very powerful incentive to kind of figure out if this is really, really, really the right co-founder for you.

Another thing that seems strange to me is the lack of an idea. So one of the, whether it's a narrative or a myth, I don't know, but a nice romantic narrative that exists in the world of entrepreneurship is that very often the founders have this burning need to do the thing that they're going to do, whether it's deep domain expertise or some intractable problem that they're trying to solve for themselves or others. There's this kind of romantic seeding of the idea, whereas in this case it sounds like in many cases that there is no idea to begin. There's really just more talent and ambition. Yeah, I mean, I don't wholly disagree with that piece of conventional wisdom. What we've had very little success with,

is taking like totally blank slates. I think early on we almost went too far that way and were like, hey, it doesn't matter they'll figure something out. I don't think that is true. So now what we look for is, I would almost call it a proto idea. What does an idea look like before it becomes an idea? I think it's one of the most important questions in our business. And the answer we've come up with is it looks like an edge. An edge in our language is like a personal competitive advantage. So if I'm interviewing an entrepreneur, the biggest mistake I could make is saying no, because the idea isn't fully formed. Because that's the whole opportunity is to be with them on the journey as they form it. But what I do want to know, and what I have to try and imagine is I have to fast forward

six months and say, let's imagine this person standing on the stage at Demo Day. What in their personal background, what in their story, is going to be the plausible platform foundation for an idea that is venture-backable. And so an edge for us is usually one of two things. It's either some sort of domain expertise. Great example in the the last London cohort, we had a guy who was actually very successful, a global head of data in a big hedge fund. And he came to us and he's like, I'm pretty clear that there is a big problem for people like me in financial institutions around data. I don't know exactly what the product is yet. I don't think I can personally build it myself.

But I know that with the right co-founder, there is a hugely valuable problem here. And then our job is to say, okay, so six months from now, can this person stand on a stage and tell a story about what it becomes and why that edge kind of led them to this idea. In that case, it was kind of a no-brainer. The more interesting one in a way, or interesting because more challenging for us, is when it's a technical edge. So we found a lot of people from very deep tech backgrounds. And so sometimes we'll get someone who's like, I did my PhD in Computer Vision at Oxford University. I said, well, I think there's no dispute these days that Computer Vision is a really interesting technology with a lot of valuable applications. So then the question is, does this person have the

commerciality and adaptability to, when paired with someone like the first guy, figure out something that's interesting. And that's where a lot of the risks that we take on lies is, is will these people figure out something that's more than the sum of their parts when it comes to these two edges? But when I look at our companies that go on to do well and either be acquired or raise series A's and B's from well-respected investors, it's very often that there's something really exciting at the intersection of two edges. Someone with domain expertise, someone with technical edge. I think it can be more than the sum of its parts. Let's talk about deep tech. It's obviously hard. You're always dealing with sort of the frontier of understanding and knowledge and skills.

What's your take on the opportunity in deep technology and why are you such a fan? And what does it mean? I think one of the challenges of this phrase is five years ago, no one said it. Now, loads of people say it and mean totally different things by it. So to simplify, what do I mean when I say deep tech? Broadly, the way I would frame it is I think every great startup needs a good answer to why now? Why is this only just become possible? There are good answers that are nothing to do with technology. So platform change. Now everyone has a smartphone in their pocket. What's that enable? And that's where Uber came from, for example, or social change. Arguably, Airbnb's why now is that for the first time there's a generation of people who are willing to use sort of

presence on the internet as a great proxy for trust. That's just like a social change. And before, that probably wouldn't have worked. Plus some platform changes, et cetera, or regulatory change, like a lot of these marijuana startups. Why now? Well, because before it was illegal. For me, a deep tech company is where the why now is something to do with technological change. So it's like this is only just become possible. We really like that. We like it for both macro reasons, as in we think there's a lot of opportunity there,

and we like it because it's a really great fit with our model. But let me take the first one first. So I think it is increasingly difficult to build large platform scale consumer internet-style businesses. This is a very much discussed topic all around the world now, can you build anything that Facebook won't just buy or out-compete in some way? Our view is that the place where there's the big opportunity to build $10 to $100 billion companies is sort of the vast areas of the old economy that are yet to be disrupted properly by technology.

So Mark Andreessen's big idea of software is eating the world not only seems true, but it feels like the next layer of that is machine learning is eating the world. And when we look at how biology, chemistry, energy, manufacturing, health care are being changed a really fundamental way by what is effectively software, we just see that this is a trillion dollars plus of added value around the world that is going to be disrupted. And that just seems, even in the last couple of years, that seems more and more obvious. And we're really excited about that. But in a way, for us, more importantly,

it comes out of talent investing. It's like for us, it's a necessary condition of talent investing to really care about deep tech. Let me try and explain that. So the biggest worry we have, the thing that keeps me up at night, is adverse selection. So the problem with potentially with a model like this is in the same way that you don't want to sell, someone runs up to you and says, I really, really need fire insurance from my home just for tonight. They're probably not the customer you want. The danger in VC always is that the people that are most desperate for your product

are not the customers that you want. That's particularly true in something like town investing where you're starting really, really early. We are, I would say, a luxury product in the sense of high end. We're high quality and we're expensive. We end up owning 10% of every company that goes through the program. The same way that YC is expensive, but I think hopefully most of its customers and hopefully our customers think we're great value as well.

But it does actually constrain what kind of companies you ought to be going for. I would not want to invest in an entrepreneur who didn't need our service, but still wanted our money. That would feel very weird to me. And yet, if you think about what I would call light tech companies, because the cost of starting up has got so low now and because the technology isn't differentiated, if you're the world's best CEO for a particular light tech product category, you don't really need a world-class CTO on day one. I'm not saying that later you won't need someone who can run an engineering organization. But on day one, you don't need someone with a PhD from MIT. You need someone who

can build an MVP, get up and running. And so I almost question, if you want to build e-commerce play, why come to us? In a way, I suspect you because you can't find someone to do this for you, build the quick, cheap prototype, raise a small amount of money from angels or whatever to get it done and get going. Deep Tech's nothing like that. The world's best CEO for a, I don't know, protein discovery and generation company could well not know the best CTO for that. Well, they certainly may not have them so readily in their network that they can start tomorrow. And these things are a little bit more capital intensive. You can't just knock up an MVP in a couple of weeks. And so I think one of the exciting things about deep tech for talent investing is that unlike a lot of

light tech consumer products, you avoid the adverse selection issue. But also, as importantly, I think what's quite interesting is you're not getting into this problem of anyone can do it. If you think about, I like to think about companies like Snap or Instagram, great companies, but companies we will never build our entrepreneur first. Why is that? Because basically, I don't think it was possible really to identify the winner in advance. I think, the people that built those companies are great entrepreneurs, but in a way, the mapping between seeing the team on day zero and the outcome is much less clear. You know, there were probably a thousand companies in the broad photo sharing space, and actually probably the right strategy

was to invest once there was traction. By nature of talent investing, you're always investing pre-traction. So then the question becomes, what kinds of companies maximize your ability to predict success purely on team quality? And so you want to find markets with three characteristics. One is that there should be an unambiguous problem. One of the reasons we'd never do snap is it kind of turns out it's a bet on whether ephemeral messaging is a thing. Turns out it's a massive thing and that was great. But that's sort of not really the bet that a talent investor is set up to make.

Whereas can we build 70% better video compression? Yeah, if you can do it, there's definitely a market for that. It's deep tech. It's hard. But one of our best outcomes so far, a company called Magic Pony Technology did exactly that and could identify in advance. Yeah, this is a real problem. Second thing, how good a predictor of the eventual outcome is team quality?

Just how many people in the world can build this and how good do we think this one is? Third thing, some sort of objective standards for success. So in a way, it's hard to say on what dimension, a snap or an Instagram or whatever won. It's very clear that they did win. It's very clear they executed extraordinarily well. In a lot of the problems that we work on, particularly in machine learning, it's clear that it's either speed or quality or cost. And so we can in advance say, well, do we believe that,

this methodology and this person has an edge in getting to a superior outcome on that dimension. And so we just think the fit between deep tech and talent investing is really, really strong. A lot of the examples you gave of, I agree by the way, that this deployment era of applying these fantastic techniques to kind of old line industries. We've seen this movie before. Happened coming out of the kind of World War II period too, where utilities and railroads and boring companies applied all the new technology from the auto age and got better, right? And so it seems like something that repeats kind of the Carlo-a-Praise idea. I'm curious how much of that you mentioned in each example that it's sort of the use of software to affect change in whatever it is, health care, energy, et cetera.

What do you think about the more physical side of deep technology? So I don't know what the proper examples would be, but hardware or machinery or faster planes or the kind of SpaceX style deep technology, where does that fit in the entrepreneur first model? We've done a lot of non-software. I mean, we always say we believe our core should and will be software. So about 70% of everything we do, we aim to be software. 20% we aim to be non-software technologies that we've done before and know something about. And 10% we call Wildcard as in like, hey, if this works, it's totally asymmetric. So let's try it.

We've done a new kind of Silicon Photonics company. It's not software at all. If it works, it will be huge. I think my personal kind of favorite bet, though, for the next time. 10 years is that it's really about vertical integration built on a software layer, but having to build a lot of non-software to make that work. We have a number of companies in our portfolio that I think are pulling this off really nicely.

It's a company called Cloud NC, which is an end-to-end automated subtractive manufacturing company. And they started with a pure software play. And then they found that actually the customers, the manufacturers, were really difficult customers to try and sell an integrated machine learning play to. So they're like, oh, man, we're going to build our own factories. And that's what they've done. And it's amazing. It works. Have you heard the Keith Rabeau idea here?

He said when I talked to him, this is one of the coolest lines I've heard, something like every major success of mine, this is him talking, was some sort of company, a software company that built for a customer, found it hard to sell or integrate with them, and then use the software to compete against them. Right. Yeah, I hadn't heard that. But yeah, we see that as a very powerful trend in deep tech. I mean, actually, I think one of the interesting things about a lot of the industries that I'm talking about is that if you think about,

startup culture, operating cadence, operating style, and customer behavior, it does mean that a lot of, I think, the successful place will be where you don't have to deal with this sort of incumbent as customer at the beginning, because that will just slow you down in an already slower. A lot of what we're doing is going to take three years before it shows anything. And then hopefully it's suddenly, in fact, one of my favorite entrepreneur first companies, it's actually a company that's been discussed on the podcast before because when you had Ash Fontana from Zeta, he got to. the seed round in one of the companies that we helped build called Tractable, which is a

computer vision for insurance company. That's a great example. I mean, they were like three years before really they had almost a penny of revenue, but then suddenly, once something like that works and it's better than a human, suddenly the revenue kind of goes vertical pretty quickly. So we're pretty bullish on these sort of end-to-end integrated solutions. I mean, they require a lot of executionability as well as tech. We certainly don't believe that you can just sort of ignore the entrepreneurship side of that it's not like, oh, cool, well, scientists can solve every problem. But we think that if you have the right team fit, you can do something really, really powerful. Can we talk about geography? So when we met just a few weeks ago, this was kind of

the major topic of conversation, which is a couple of places get all of the attention in entrepreneurship, certainly in technology entrepreneurship. And I think you've got an interesting take on this, you know, an opportunity, we'll call it, in geographic dispersion. Yeah. So one One of our beliefs is that talent is truly globally distributed. I think that's not controversial. But I think because of this, I would call it sort of myth, that there's something almost like genetic about entrepreneurial talent. The belief is when we first said we were going to go and open an office in Singapore,

people said to us things like, Singaporeans aren't very entrepreneurial. That's an absurd statement. It's like saying Americans aren't very tall. It's like, well, some Americans are tall. And our belief was we're not trying to pick the media in Singaporean. We're trying to pick outliers. I mean, outliers is a theme that runs through everything we do. And so because, as I say, what we're trying to do is bootstrap a little bubble of Silicon Valley of network density in each of these places,

I think you can actually take talent that would be completely missed as being entrepreneurial in a new place, activate it, and then support those people to do really amazing things. I think what's really exciting is that this is why I love the talent scouting model. Our talent scouts, within that, people who work on our talent team, often then discover networks of individuals who are totally looked over by the venture industry for a bunch of reasons. And the example we were talking about before, which one of my favorites is about one in 12, maybe nearly one in 10 of the entrepreneurs that we funded in Singapore is Iranian, which is pretty remarkable when you look that there's less than 500 Iranians in Singapore. It's like one in 10,000.

So how does this happen? Well, broadly, if you were to write a list of the world's top 20 universities, and then you should just cross off the ones where an Iranian student, however smart, is going to really struggle to get a visa, the number one university remaining in the world, is a number one university remaining in the world is the National University of Singapore. And so there are 500 Iranians in Singapore, but they are unusually concentrated in the grad student population in STEM subjects at two amazing universities. So we must have funded, I think we funded probably, I don't know, 10% of Iranians in Singapore or something. I need to check the exact number. But that to me is one example of once you abandon

the idea that everyone who could be a great founder already knows it, then there's the opportunity to find dislocated networks. Because, of course, I would wish that on day one we'd been like, do you know what would be a great thesis for Singapore, Iranian grad students? We did not do that. What we did do is spend a lot of time hanging out at those universities. And as I said, we become a magnet for those people. And then actually, we're now six cohorts in in Singapore.

Most of the Iranian grad students were now referrals from their Iranian friends from the earlier cohorts. And so I think one of the really interesting things about talent investing is much more, I believe, than conventional VC. it has these interesting network effects where actually being part of the community becomes more valuable as more people join. And the sort of strong and weak ties that exist prior to joining us become really key to people's journey through the program, but also bringing in their friends and contacts afterwards. What are some other interesting places, specific places other than

Singapore that you found interesting stories emerge? So one of my, as I was talking about this sort of history of ambition, I really believe that we're at this inflection point. Glover. where many places that have historically not had this sense that starting companies an ambitious thing to do are about to flip in that. So actually, one of the things I like to say to people, which I think people find surprising, is that two of the cities that we work in that have very similar talent markets are actually Paris and Singapore. And in some ways, you'd think Paris and Singapore couldn't be more different.

But let me try and lay out some of the similarities. So both have a highly stratified, I'm trying to think if they'd like me to say this, rankings obsessed, let's call it education system. You are ranked at every level. It's highly selective. The prize is to go to the next elite institution and keep going up the ranks. France has this series of Grande-Col and the idea is you just keep going through them. And then at the end, you become prime minister sort of thing, slightly but not very much exaggerating. Singapore actually has a similar thing. They rank everyone. The top prizes, you win the president's scholarship to come study at Harvard or whatever, and then you go back to Singapore and work for the

government. And so both are going through this interesting period where they've created pools of elite talent, which are typically, certainly compared to the UK, much more engineering-oriented. So a lot of that path in France is going through engineering school. And again, in Singapore, maybe not quite as much, but there's a big emphasis on science and technology. I think Lee Kuanian, you said something like poetry is a luxury we cannot afford. And so what it means is you've got pools of elite talent that for 34 years have been funneled into the public sector as being what ambitious people do with that. lives. And then at broadly the same moment, there's this realization, I don't actually have to do that. I don't have to go be a civil servant in the Depont for Energy in Paris. Actually, I can

build stuff. And they've got the skills to do it. And so one of the things that we love is we love that moment, that point where actually you get this flip between elite talent with the right skill set going into what we consider to be a probably less impactful, less leveraged use of talent, the opportunity for them to flip into technology and entrepreneurship is actually enormous. So I think that would be like one example of how we think about it in the macro sense. One of the things I'm personally obsessed with is how do global macro forces shape what happens locally. So an interesting example is Bangor. So we have an office in Bangor, it's our newest office.

We opened it about a year ago. Now, Bengal has always had a big tech sector. But historically, there has been an element of brain drain and actually a lot of the very smartest and most ambitious people out of India. of wanted to go to Silicon Valley. I think one of the interesting things about what the current administration's doing around immigration is it's actually made that path a lot harder. And that's probably a bad thing for America, but it's a great thing for Bangal. At least if you're a talent investor in Bangal, because suddenly you have a pool of people whose default path. And I think that idea is really important. The idea of what is the default path? If the default path changes,

then there's an opportunity. The inspiration, why did we start entrepreneur first? Alice and I met at McKinsey. Why were we working at McKinsey? Default path. I mean, I don't even remember filling out the form. I graduated from Cambridge in 2007 and that's what you did. I'm kind of embarrassed that that's my answer, but it's true. You know, I had a great experience there. But one of the weird things about McKinsey is it's full of ambitious, competitive people who all swear they do not want to be management consultants. There's an opportunity. And I think you see that in different ways reflected all over the world. What are some of the things we've talked a lot about this, we'll call it pre-VC, pre-company talent aspect of what you do. That's kind of the court proposition.

upstream of this is a traditional default path, which is take money from one of now a massive number of professional early stage investors kind of up through public markets. And I think that there are now very commonly held beliefs. There's a lot of convention in that world where maybe 10 or 15 years ago there was a lot of very unique thinking now it seems quite conventional. And just like it would be hard to pick the next big consumer business, I think it's, it would certainly be hard to pick the marginal VCC. company that's going to do a good job. So what do you think are some usefully incorrect things about the way that the traditional early stage investment world operates? The two that come

most to mind. I mean, one, we've talked about a bit, but I think we talked before we start recording about this idea of gold miners versus alchemy. So one of the challenges in VC is that one of the pieces of conventional wisdom that maybe I'm being unfair, but you know, you see on Twitter a lot is, oh, there's no such thing as value investing in startups. Price doesn't matter. All that matters is being in the right companies. It's like, I don't know. Price matters quite a lot. And so when you start to take that lens, you realize that the belief that price doesn't matter drives a lot of things that I think are unhelpful broadly for returns, like font size. Price doesn't matter, then, hey, you better be prepared to pay more. So, hey, you better raise bigger funds. So hey, you better have a very

particular type of business that you can invest in, which is going to kind of be that sort of deco-corn level that returns the size of fun. And that's kind of unhelpful because actually, I think if you can find a way to invest at a fair price that reflects the level of risk early, you don't have to have crazy font sizes to make things work. And we don't end up with this kind of weird dynamic where the kinds of companies that you'll now see pronounce as VC backable or not becomes the ones that VC backable seem to become a narrower and narrower portion. I think we are going to see some backlash over that over the next decade in that it just

seems crazy to me that you wouldn't be able to manage kind of meet the returns expectations of LPs if you're simply willing to have a smaller font size. So I think that's one that I think is pretty powerful. I think another one is we talk a lot about long-term thinking in VC, but a lot of the incentives in VC are to report markup to your LPs in time for you to raise the next fund. And actually, that creates some really perverse incentives. It means that it's actually better to sometimes, unless you have very experienced high-quality LPs, and there's only so many of those to go around. I think we're lucky to have some of them. But a lot of new LPs, and there are a lot of new LPs, would rather see a markup on a new round than a

company that doesn't need to race. And so again, because it's pretty much the only yardstick that you have to measure in a journey. Or like a linear revenue growth curve versus a convex one. Yeah, right. Well, and that's the interesting thing about you see sometimes that it's better to have no revenue because then you don't get valued on the shape of the curve. So I think to me it strikes me that if you relax any one of these constraints, there's an opportunity to build a different kind of VC. And we're starting to see that with things like India VC where they're saying, you know, we're not going to just obsess over exits. We're going to try and build real businesses. I mean, I think the constraint that we relax that is most important is just founders don't need

to have known each other 10 years before you can back them. But the thing that I wonder whether will change, I think, in a good way, we're now living in this sort of slight sense of being in a post-soft bank vision-fond world. And I think that is going to put rightly the focus back on building companies that can be successful over the long run, which should re-emphasize creating real economic value, which should reemphasize not just saying, who will price the next round at a price that I can report. It's funny.

I think a lot of people talk about long-termism. There's actually a lot of impatience, I think, in VC. I think one of the reasons that deep tech is such a big opportunity is there are not many LPs and not many VCs that have the patience for investing. and then having three years with no revenue, maybe no markup, because actually, that's uncomfortable. What do you think about from thinking about the value of your own business? So entrepreneur first, the business, as something which, as we discussed before, like most

management companies of any kind of asset manager, either trade at really low revenue multiples or really are effectively worthless. They can spit off enormous amounts of value in the form of cash, but they're not really things that gets sold. Their partnerships kind of, they get passed along. So it's an interesting question to say, who has created value in a management company? And I'd love to hear your thoughts on whether that's possible. And if so, how might someone try to do it? Yeah, I think this is really important. And we, from day one, more or less in Entrepreneur First, said we want this to be a multi-decade thing, that we want to be valuable, independent of me. I think we were lucky in that when we

tell the company, no one wanted to fund it. We went and saw a lot of investors. They were all very polite, but it was sort of like on the lines of good luck, you have fun there. And we got very lucky, although it was a couple of years in. We met a guy who runs a big hedge fund in London. He loved the idea. He was like, I want to back this. He's like, but I want to warn you that I know what it's like to have a management company that's actually not worth very much. Because even though it's a very, very successful hedge fund, he's like, if I leave, all the value goes. The reason that there are LPs is because people trust me to pick stocks. So it's like, from the moment I invest, I want you to think about how do you maintain investment performance,

rigor stock picking, which in our world means talent picking, without you and Alice being able to be there. And I think that's because we got that advice with our very first investor, and that's framed a lot of what we do. So I think there are two reasons primarily why management companies historically have not been invaluable in VC. I think it's worth footnoting that some of it, I think, is an ambition thing, frankly. I mean, if you look at the big private equity groups that have got public management companies, it's very striking. No one's done that in VC for reasons that I think are partly driven by, I have a friend, Oren Hoffman, who has written about this. He's like, why are VC so unambitious? And I think that's a good question. The irony is

the thing that VCs hate most in the world is lifestyle businesses, except when it comes to their own GPs, which are the ultimate lifestyle businesses. But what are the things that you need to do to have a valuable management company. Two things. Make yourself not the superstar, because to the extent that the returns need to accrue to superstar pickers, the company is worth nothing. And second, have some pricing power over the long one. There is a huge winner's curse problem in VC. If you're the highest bidder, again, sometimes you get lucky and it's Uber and it doesn't matter. But a lot of the time, if you're the highest bidder, that just means that you've overpaid. If I think about the one, to me, really ambitious, amorable, long-term franchise that has created a

disconnect between superstar pickers and values why Combinator, which now for, what is it, 15 years, 14 years has sort of been able to maintain pricing power. They have amazing entrepreneurs all over the world come and take their deal, which is much lower than they could get in the market. How we think about that is it's not enough for us to be good investors. We have to create massive value for our founders as well as the capital that we provide. Otherwise, rightly, all of the returns should accrue to the LPs and to the superstar pickers. So how have we done that? Two ways. One, we've created a very data-driven way to invest, even though you'd think there is no data. So we now will fund, as I mentioned, a thousand individuals in the next year. I'll meet a few dozen of them. But actually, I think if you look at our data, it looks like the quality of decision-making certainly hasn't decreased since I was less involved, if anything, embarrassing is probably increased. So I'll come back to how we do that. And secondly, we think very hard about how we create pricing power. So let's take the data thing first. So I think, One of the mistakes that people make when they think about why there's been so little data in VC,

there are very few as like a couple of quant-driven VCs, but they typically focus later stage when there are metrics. You could say there's nothing to measure in our business. We actually disagree. So I think one of the things that would terrify me about being a conventional seed VC is having to make a decision after two meetings or three meetings. We've structured our business so that we don't have to do that. So we do have to make a decision on whether to accept someone into the program after one 30-minute interview. But from an LP's perspective, the amount of capital we're putting at risk for that is just the stipend we pay for three months. So it's about $10,000 grant effectively.

What the grant buys us is an option, an option that we have to exercise or not within three months on whether to invest in any company that they do create. But of course, what we get in that three months is the opportunity to have them in our office and to work with them. So on average, we've had over 100 interactions with an individual before we make that investment decision after three months. Now, one thing that is a bit of a bog bear of mind is people often tell what's impossibly subjective. It's like it's subjective but rigorous. And those are not opposites. Actually, you can be super rigorous while being super subjective. We think of it as an apprenticeship model.

You can teach people how to evaluate entrepreneurs over that period. So by the time we come to make a decision, the decision I'm making today as the CEO is not, what I met this team and I did my due diligence. This is what I found. It's like, do I trust the data generating process? do I trust the consistency of the process? Do I trust the stack rank that comes out of that process? And if so, where do I draw the line on the stack rank? Not an individual decision. And that I think is very powerful because it's repeatable and scalable. And we found a couple of things that are just incredibly

strong signals in that first 100 days. I think the most important and obvious one in a way is productivity. But I think what people mistake is they think of productivity as being about long-term useful outcomes. we actually don't care about that. So we would rather fund a couple of people running really, really fast and hard in the wrong direction than people who we love the idea, but it feels like they're sort of crawling in the right direction. And so my favorite entrepreneur-first stories are people who kind of had nothing when we had to decide whether or not to kind of call that option, exercise that option. But they were just running so fast.

So one of my favorite stories is a company called Accurix, one of our London companies from maybe three years ago now. two guys, Jacob and Lawrence, standard EF story they met on the program, to your question about, is there an idea? Jacob had got a total passion for healthcare. He'd worked in healthcare. He saw a ton of problems and he was obsessed with the problem of antimicrobial resistance, which is a huge problem.

And so he and Lawrence set about trying to think about how could you solve this problem? And the initial hypothesis was we need to give family doctors better decision support tools. How do we get them to make better decisions about what to prescribe and when? So they spent the first 100 days of the program running around, talking to general practitioners, and basically they got a load start. I mean, they must have spoken to, like, sort of making the number up, 100 dots in 100 days. And these are people who typically don't keep a schedule to meet with entrepreneurs. And we sort of came to our investment committee and we were like, well, it's not really obvious how you either going to create or capture value with this idea. But man, these guys have got so much done.

And the people that work with them and have those 100 data points system, they were like, this is the hardest working, most determined team. we've got. So, okay, we fund them. The typical amount of money that a company raises in our London program coming out of EF, I think the average these days are something like 1.4 million. These guys managed to raise, I think, 275K. And it's basically because everyone's like, there isn't a business here. What is it? I was like, trust the data. I love these guys. So they spent a year around talking to doctors. Remember having breakfast with them once a year in, and they somehow made this money last. I mean, they'd got grants and stuff, but well, they'd made it last, which I always thinks a great sign. And they're like, you know, the problem is that the doctors kind of like the tool,

but they say that the patients don't do what they tell them. So we've built this little thing, which is sort of just a reminder thing, texts, you know, SMS to patients to remind them to take the antibiotics. It's like, okay. But the doctors are using it for stuff that isn't the antimicrobial resistance. I was like, huh, that's kind of interesting. Anyway, I don't want to claim any credit because they basically, after that meeting, made that their whole business.

I'll fast forward and get to the punchline, which is within nine months of that, they were in 30% of all Dr. Straters in the UK. Today they're in 50%. They've texted over 8% of the UK population. So they went from raising a 275K, what could only be to called a pre-seed round to I think like a $10 million series A from one of the top funds in London.

And what's really interesting and sobering for me, but I guess a bullish sign for the value of the GP, is, and I've said this to them, whenever I met with them in that first year, I was like, oh man, our ranking was so wrong. These guys are just like they haven't figured. it out. We should really revisit what we go around here. And every time this has happened to me, every time I thought, huh, I've got signal here. I'm sitting down with these entrepreneurs after.

So this is more powerful. I've been wrong. Every company that I've mentally downgraded from our sort of talent ranking, our productivity-based ranking, because of some idiosyncratic signal in a meeting I had with them, I've been wrong in the day it's been right. And basically what I've come to believe is it's just very hard to beat 100 continuous data points because you see the shape of the curve, you don't just see a dot. And so one of the reasons I think EF can be a multi-billion dollar business in its own right is I just think that's an incredibly powerful thing. But doing it at scale in a rigorous way around the world is actually very operationally complex. We employ, we have $200 million under management, and we employ about 100 people.

On a conventional model, that's really tough to make work. And that's one of the reasons that we've raised capital into our management company. So having said, Silicon Valley VCs, I think wrong about X, Y, and Z. We raised that from Silicon Valley VCs, of course. So, Reid left that round and founders fund and all those participated. And I think it's because they also believe there's a multibillion dollar opportunity in building a scalable way to evaluate people and then to capture some of that value. Because that's the second piece that I discussed is why pricing power? Why do we pay less than market price? Well, it's not that we pay less than market prices is that the market doesn't exist. What is the market for investing pre-company?

We always say in one of our mantras internally is the customer as the entrepreneur. So what we would not want to do is kind of get rich, taking more equity than we deserve from these entrepreneurs. What we do want to do is say, how do we not just be capital, but actually be part of value transforming moment? In a way, it's kind of an easy sell because we're effectively a co-founder in each of these companies. One of the founding team, an entrepreneur first, a guy called Alex Crompton. He has this great blog post about this where he talks about a lot of investors say they want to be there on day one. But there's a huge difference between, say, zero and day one. And actually, the value transformation in saying to an individual, today you're an individual,

to morrow you're a company, that is a zero to one to use one of Pietil's phrases. And so we just capture a small amount of that value as what I would call a return on operations rather than a return of capital. And that, I think, allows us to capture a lot more value than a traditional VC would. What percent of the options to the exercise? Around 50 percent. Really? That high?

It varies. I mean, one of the interesting things is, our starting point in this business was so much that everyone thought it was a bad idea, that one of our ingoing assumptions was we just don't know. We shouldn't trust any of our instincts on these things. So historically we did a lot more and said, we just don't know, we should buy these are relatively inexpensive options, we should buy a load of them. Then over time, we found that that stack rank was actually pretty accurate,

and so we kind of raised the bar a little bit. So yeah, these days, somewhere between 40 and 50%, depending on the cohort. I think what's striking is that even though we're doing that after 100 days, with people who only just met, somewhere between 60 and 70% of those people will raise a seed round from an institutional investor within six months. What do you think the biggest risk is to your model? Like if you and I are hanging out three years from now and this whole thing is gone, why would that be?

How could that be? Yeah, I mean, there's a bunch of things. I mean, I think one is that you have to just stay totally obsessive about quality. If you think about how you build a business in general, the obsession is growth. And I think a mistake that it's easy to make is to say for Oz growth is maximizing the number of individuals that we fund each year. That's not the number that I have in my head. It's like maximising the equity value of the companies that we're helping to create. So I think one way we could get this wrong is if we basically, if the flywheel starts to turn in the opposite direction.

So right now, I would say broadly we're in the fortunate position that our flywheel is great talent, which yields great outcomes. which yields a great brand, which yields great talent. And then the flywheel turns. And in the place we've been operating longest, London, that's definitely happening. And that's why we get the organic applications, particularly in London, are incredible. I mean, people who probably shouldn't say this, and I'm like, why are they coming to us? We're so lucky with the quality of people we get to work with. But you only have to lose it a little bit.

You only have to have a critical mass of people and be like, ah, the people were kind of good, but I've got better friends. And the whole flywheel unravels. Now, I believe that the antidote to that is culture. I believe that the way you solve that is you build massive respect for the customer, i.e. the entrepreneur, into your culture. And so every GM around the world has totally ingrained the idea that, like, talent is the most important thing we do. It's like glamorous sometimes to think like a VC.

That's not what we do. We partner with entrepreneurs before they have a company, and we work with extraordinary people. And our bar is opportunity to cost, as in we say, we want to be in a situation, where we are so nervous about the opportunity cost of this person being there. We know that if they weren't starting to accompany, they'd be doing something else that's incredible. We only accept people where we feel we're taking that risk, but also where we feel we can deliver such a quality of service

that it's not that we're meeting our side of the bargain. So that's a worry of scale. As you scale, can you keep that super intense? We think the answer is yes, but if I had to identify a single executional risk, that would absolutely be it. So you've yourself created a very unique investing, business. We talked about pricing power for investing businesses, which maybe you could argue Warren Buffett and maybe a few others have Seth Claremont, a few others have the equivalent of

pricing power in public securities because of their arbing their own reputation sort of thing, but it's certainly more rare to have some sort of pricing power as an investment firm in public markets, maybe in distress situations, et cetera. In private markets seems more possible. What advice would you give to, let's say you had a pool of talent where they weren't trying to go create companies, but we're trying to create investment companies. What advice would you give to people interested in creating an investment company that would maximize the chances of their success? And is it mostly around pricing power? Yeah. So I wouldn't presume to know anything about any other kind of investing. So let me think about what I would say to a aspiring VC. So I actually have some

interesting data on this, which always slightly shocks people. One of the advantages of scale, having just talked about the risks of it, is that you just get a lot of data that is almost literally impossible to gather any other way. So after Dema Day in Europe, we would typically see maybe a thousand meetings, maybe I'm slightly exaggerating, somewhere between 600 and 1,000 meetings happen in the first month after Dema Day between founders and VCs. One of the things that we ask the founders to do after every meeting is grade the VCs. Oh, lovely. I love this. Both on a three very simple kind of quantitative questions that we can just do one to three, and then qualitative feedback. I recently gave this talk in London to a group of visiting VCs.

It's on maybe 50 VCs. They're on the Kauffman Fellowship program, which I think is pretty good and has some great people. I asked them to guess, what is the number one driver of I would want this person to leave my round? Everyone is guessing all the things

that you would read about on Twitter. Oh, you know, help with hiring, market access, great relationships with all investors. No, punctuality. Number one thing that founders want from VCs. Now, obviously all those other things are important, but when I think about pricing power,

one kind of pricing power is being the first and therefore only bidder. Founders love speed. They absolutely love speed. One of the biggest challenges we have as we've scaled into ecosystems that are maybe a little bit less developed than London is not quantity of capital around. It's the speed of capital.

And actually London is slow compared to Silicon Valley. So if I were starting a VC today, I'd probably start it in Southeast Asia and just optimised for speed. Because I think Southeast Asia... So one thing we didn't talk about when we talked about geography, that I think is really important. and I think a lot of people disagree with me on, is I think we'll look back in 10 years and say, wow, the role of geography in driving seed prices was so ridiculously overstated back in 2019.

If you were to do a regression now of seed prices on a bunch of variables globally, by far the biggest driver is geography, by far, as in are Singapore companies raised at roughly 50% of the price of London? Now, very smart people tell me, yeah, but this is because of the exits. The exits are 50% lower. To me, this is like the exact wrong data point to try and see in a rearview mirror. And actually, it's another argument for deep tech. In deep tech, you're much more likely to have global winners. You're not going to have, this is a great autonomous vehicle for Singapore.

Like, it's like if it's the winner, it's going to be a global winner. To me, it seems like a really obvious bet to make is that particularly for deep tech when you're encouraging the entrepreneurs to think global from day one, we'll get convergence to global outcomes pretty quickly. We see that even in who leads the series A's and B's now. increasingly in Europe anyway, the series A's and Bs are led by US firms. So to me, wow, that just means Singapore seed rounds are massively underpriced for the right founders in the right spaces. And if you're fast, you'll win every round.

So if I wasn't doing this, I would go build a seed fund. I would invest in Southeast Asian deep technology companies and I would write them a check within a week. And that's a kind of pricing power. As in you could probably get the geographic pricing arbitrage, but you certainly get the speed uptros. I think I've said a lot on the podcast that we have never made a personal family investment as an LP in a early stage fund, despite I'm fascinated by this world. I have tons of conversations with people on the podcast, et cetera. We recently decided to do our first one, and it's Seed Bangladesh. And the reason is like you said, okay, the addressable markets are huge and the prices are like one third or one fourth or a series A company raising at a preseed price.

It seems to be sort of, obviously, there's tons of risk associated with that. that's unique, but it seems right. I think if you look at the history of Y Combinator, I mean, they did a lot of things right, loads of things right, but I think the most powerful thing they did was become the gatekeeper that is the on-ramped to Silicon Valley. Actually, having an application form is a really powerful thing

in a world where every other VC says, get introduced by someone who knows as well. It's like, cool, well, that means I guess you're never going to fund anyone from Iowa. YC actually figured that out. I actually think there's a similar opportunity now, which I believe we're taking, which is YC is a great on-ramp if you already have a company. What if you're the top physics, PhD in Mongolia or whatever?

What is your unrap? We want to be that unrap. One of the reasons we took money from Reid Hoffman and these other investors was partly because they're great company builders and we wanted their advice. But also, we wanted to be a very credible onramp to Silicon Valley for the best companies globally. Now, we don't think that needs to happen at Seed. The path to scale, I think, still does run through Silicon Valley.

And we want to be able to facilitate that for our companies. What other controversial or contrary opinions do you have that we haven't talked about? What have we left out? Relating to investing. Period. One of the big bets we've made and continue to make is the power of cities. And maybe that sounds really obvious, but we're in the business of talent aggregation, and cities are the all-time most powerful technology for talent aggregation.

So we're very, very long cities. We're so long cities that one of my sort of controversial beliefs is that actually we will see, if you're to list the top 20 countries in the world by GDP today, I reckon at least five will see cities or regions secede in the next 30 years. I write a weekly newsletter that is broadly not about startups. It's called thoughts in between and it tries to take a broad view of how the world is changing. I wrote about this recently and I think people really disagree with this. You brought this up at our dinner.

Yeah, it was the most animated that everyone else got. Yeah. It's just a sign you're on to something. I feel like the broad economic compact between megacities and their hinterlands is breaking. because of the increasing returns to extreme talent. And so in a world where you have increasing returns to talent and increasing talent aggregation in cities, it's actually really tough to make that work as a political economy.

Because particularly when the first form of resistance from the rest of the country, in the case of say something like Brexit, comes from people who say, we want to actually hamstring that city's ability to play its role in the global economy. That's like maybe an unfair caricature of Brexit, but it's one approximation of it. I think that's going to become harder and harder to tie together. One of my all-time favorite anecdotes is talking to a very senior government figure in Singapore,

where we say we do a lot of work. I made some somewhat banal admiring comment to him about how well Singapore performs on all these indicators of development. And he turned to me and he said, yeah, but London would look similarly good if you could just rename the rest of the UK and Malaysia. And, okay, say what you will about that, but it's a pretty powerful idea. I call that the relabeling temptation. I think a lot of megacities around the world will feel pretty tempted to say, this deal doesn't work for us anymore. But I think that for me, coming back to investing, that's the reason to bet long on cities

and long on talent aggregation. I think it's only going to become a more important force in the world. What other topics do you tend to return to in that non-investor-focused, startup focus, weekly letter? I'm looking forward to reading it. I think one of the most important and under-discussed ideas in the world, although it seems to, I'm pleased to see, be more discussed in the last six months, is the idea of technological sovereignty. So what I mean by that is I think we sort of operated in a world for a long

time where we've not really thought about at the national security level, we haven't really talked about ownership of technologies. But I think increasingly, AI in particular has really kind of sharpened people's hopes and fears about what it would mean for a country to be dominant in that technology. If you look at recently Emmanuel Macron in France, you gave this long interview for the economist. And it was sort of like reading something out of the different decade. He was talking about how crucially it was for Francis Security that it had an independent leadership in AI and independent leadership in 5G. I think this has like vast implications for how we think about investing, how we think about aggregation of talent. It actually means that

you probably need to be aligned geographically to places that are technologically sovereign, where that means that they have an independent capability in the area. So I think that is an area that's just going to be, he's creeping in now. And actually, it's interesting. When I spend time in the US, I hear more and more people talking about sort of syphous and constraints on what you can and can't explore and foreign ownership. It feels like this was for the last 10 years the dog that didn't bark. And now it is front and center for a lot of people. What's been your experience if you have worked in China? So we have worked in Hong Kong. We've decided not to open an office in China. I feel somewhat vindicated over the last few weeks, as my commenters announced,

that it's decided to pull out China. And they are seven or eight years ahead of us, and I am a huge fan of theirs. So if they can't do it, we definitely can't right now. I think it's fascinating in the, I think my naive view, say, a year ago was ultimately it's a separate market that is just going to be big enough to sustain a bunch of technology companies that are huge and can provide amazing returns for investors, but it's almost completely sealed off from the world. I think what we've seen over the last few months is actually that's just not the case. and increasingly the top Chinese companies want to project influence into the world, and the Chinese government wants to project influence into the world,

and I think that's going to cause a lot of dilemmas for people that didn't have to confront them before. It's fascinating that Mark Zuckerberg's new line of defense in Congress is, hey, Facebook is the national security asset against China. That is an argument that no one was making broadly any consumer company, what, three years ago? And that's changed really fast. So the topic I write about most of them when you say it's probably China, and China? What are the implications of if China becomes technologically superior in key domains to the United States? What is your high-level view on that? So what dimensions matter? So let's just say

binary, they're better or not than the United States and some technology dimension, AI may be a great example. What other dimensions matter and what concerns would that generate for you, if any? There are two things I think about a lot on this. One is just the race to the bottom effect. So I think you could argue that there is a structural advantage, and I'm saying that in a empirical rather than normative sense to having top-down authoritarian governments in some of these areas. So if you look at anything like genomics, facial recognition, if you are willing and able to do things that we, I think, rightly, would not want to do in the West in inverted commas, then potentially that gives you a structural advantage in developing

those technologies. That's something we've not really had to confront before, at least I can't think of an analog. And if you think about the last technologies where technological supremacy really mattered, it's probably nuclear weapons. They're clearly huge ethical issues around nuclear weapons. They're not race to the bottom issues, as far as I can tell. So I think that's just a domain the world hasn't really operated in for a while. And so I think we talk a lot now about ethics around technology in the West, and that's absolutely right. But I see very little discussion of what does it mean in a world where there probably just is an alignment of values on that. I think that's actually a really troubling thought, and I've yet to see a really

compelling treatment about why I shouldn't worry about that so much. So that'd be the first thing. The second thing is an idea that I stole from a good friend of mine called Ian Hogarth, who has a really great essay called AI Nationalism. And what Ian argues in the essay is that basically AI is not like all the technologies. If we get to artificial general intelligence, which a lot of smart people think we will, one of my investors is Demisor Sivas, the founder of Deep Mind, and this is his life's work and he's probably the smartest man in the world. So let's assume we get there.

Ian's argument is this not like having faster internet or better wireless signal. It transforms every area of geopolitical competition. And if that's the case, then what flavor of AI we get and who controls it actually becomes a really important thing. The sort of facetious, but I think insightful way of thinking about it is let's imagine that the Manhattan Project wasn't a project of the US government, but it was like General Electric. We wouldn't be like, oh, we should really think about regulating General Electric. We should nationalize General Electric yesterday. In the same way, does it make sense for private companies to develop these geopolitically destabilizing technologies? and just be like, cool, we should regulate that to avoid bias.

Man, that is a big problem. It's the least of our problems. One of the things that Ian and I talk about and he writes about in the essay is this idea of how should states think about whether or not they can have an independent capability in these technologies, particularly AI. And if they can't, does that mean that you end up getting AI client states where we have to affiliate with, you know, and this is going to shape a kind of geopolitical conflict and competition that I just don't think the analogs we have are very good for. Partly because I also

think that AI thought about this a lot, but there may be a counter example, but I think AI is the first sort of strategically important for national security reasons technology where the private sector has just had such an obvious talent advantage. So if you were to look at what's nice about these very cutting edge emerging technologies is you can literally count the PhDs. It's hard to hide them. We know which are the best universities. We know which departments exist. We know which professors supervise and we know who their PhD students are. So we can simply ask, where are they going?

And I think if you go back to famously the Manhattan Project had them all. That's the kind of fascinating thing about the Manhattan Project. Just the sheer concentration of talent. It's come back to my favorite topic. If you think about how people talked about the NSA 20 years ago, it was kind of very clear that the technological edge on cryptography and signals intelligence was just highly concentrated in the NSA. It wasn't like Google had hired all those people.

That's just not true, machine learning. We know where they are, and they're not working for the NSA. They're working for Google, and they're working for OpenAI. They're working for DeepMind. This is a new dynamic. I don't think this has ever happened in history before where the private sector has maybe been monopolized as strong, but has a large majority of the world's best talent in a cutting-edge area. Now, what that means is to go back to my macro theme about talent.

Talent is now just supremely important in determining the outcome of these things. So I think one of the most fascinating phenomena, again, under-discussed, I think, something I've written about a bit is talent is now the only, maybe not the only, the most effective constraint on some of these big tech companies. You see the things where you get like the Google walkout or you get sort of discontent in the employee base in Facebook. Facebook and Google can now afford to piss off the US government. They cannot afford to piss off the 100 best machine learning engineers. And that's a fascinating dynamic. I have a friend who I won't name because I don't know if he would want me to. say this, but he said, he was looking at this project Maven stuff. This is Department of Defense

deal with Google, which they eventually pulled out from because they had the pushback from their talent. My friend said, imagine you work for Chinese intelligence and your goal that you're given is to try and ensure that China ends up with a long-term strategic advantage in AI. What would be the smartest move? Basically be to sow the idea among sort of socially liberal Google engineers that collaborating with the US government is a really evil thing to do. Guess what? In China, that's no what happens. There was a great article about this. I forget in which publication, where someone asked the senior Chinese official, oh, can you imagine in China a similar thing where people walk out in protest of collaboration for the government? And the sort of chilling answer was

not for long. And I just think we're not talking about these things. Talent is the scarce resource. It's superbly powerful in changing leaders' behavior. In these strategically important technologies, it's highly, highly leveraged. And for the first time, we don't, none of our ultimate tools of how we think about national security really mapped to it. Just to bookend the entire conversation with where we started this sort of amazing history of ambition. I love that idea where ambition flows towards leverage. A friend of mine who also won't be named talked about the sort of the importance of, let's say, the best person in cyber warfare, we'll call it, within a given government. They're not twice as good as the second

best person. They're like a hundred times as valuable as the second best person. The leverage that is accruing to fewer and fewer talented people. It's both fascinating and sort of terrifying and reading the history of this era 200 years from now or something, one imagines that there will be some interesting individual stories being told. Right. Well, this is why when people ask me, oh, how long do you want an entrepreneur first? I say, well, if we're right about a core thesis, then entrepreneur first could become one of the most important organizations in the world, simply by being the default path for the world's most ambitious people. Wonderful. Well, my closing question for everybody is to ask what the kindest thing that anyone's ever done for you is.

In a professional context? Interpret it how you will. I'd take the professional one because it's almost certainly in the personal context. It's sort of something my wife did in not leaving me while I was building this business. But in professional context, I actually go back to the guy that I mentioned, who was our first investor in an entrepreneur first. The reason I say is the kindest thing is we were so clueless. I mean, whatever you're imagining, it was worse.

And we'd been so conditioned to believe it was a bad idea. I think we actually lowered our ambition about what to do. And so we were trying to raise 250K in 25K increments from just anyone we knew who might have 25K. And we went to see this guy and he was so kind. He was sort of like, hmm, I don't think this is the best way for you to fundraise. He's like, how about? He was even kinder than I mean.

He was like, how about you go away, spend a month thinking about what you actually need to build this into the thing you want it to be. Come back. We'll have lunch. Let's talk about it. So we came back and literally over lunchy, wide as a million pounds. And it changed everything forever. Incredible. It reminds me just to throw something out there to the people listening just to send it an example. So at the same event where we met, someone raised the question, I think it was Daniel Gross. Someone raised the question, can you think of one of the major massive tech outcomes that didn't have a very cheap first round? and I'm sure there are some, but it was interesting as you go through the big names. There really weren't many that you could name that didn't have a very cheap first round. I hope your outcome is similar to some of these massive outcomes, but it is fascinating how often

the best ideas are so hard to get going. So a great closing story and an awesome hour and a half. So thanks for your time. Thanks so much. Hey everyone, Patrick here again. To find more episodes of Invest Like the Best, go to Investor Field Guide. If you're a book lover, you can also sign up for my book club at investorfieldguide.com forward slash book club.

After you sign up, you'll receive a full investor curriculum right away and then three to four suggestions of new books every month. You can also follow me on Twitter at Patrick underscore Oshag, OSHAG. If you enjoy the show, please leave a quick review for us on iTunes, which will help more people discover Invest Like the Best. Thanks so much for listening.