Inside Thrive Capital: Investing in OpenAI, Wiz, Cursor, Nudge, Physical Intelligence

Our philosophy at Thrive that Josh taught me is that the people who win deals are the people who want to win deals the most.

Philip, welcome to Sorcery.

Thanks for having me.

This is a very big day. We have a very stealth private fund here. Okay. So you've been at Thrive for the past three years. You joined there in 2022.

Yeah. And since then, you've been involved in some of pretty incredible some pretty incredible investments like OpenAI, Cursor, Wiz, Nudge, and Physical Intelligence. How did you get to thrive?

Yeah, I think at the end of day, I'm just a technologist and optimist. I have always really wanted to study and be like the people who worked on really big technology products and projects that bent history in the right direction. There was a kid, my heroes were Oppenheimer working on the Manhattan Project or Claude Shannon working at Bell Labs or Elon Musk, you know, starting SpaceX when I was four or five years old. And I actually went to school originally to study physics. I I really thought that was the right way, sort of in the mold of some of those earlier figures of thinking about the hardest problems in technology.

Now, truth is, I was pretty good at physics. I probably wasn't quite good enough. And the road to make an impact on physics problems that are open in the field very, very long end up switching to a more pragmatic route, which was studying computer science. And but even so, really always inspired by this idea of technology being the right engine of history. And I think after spending a lot of time thinking about having an impact there, there are kind of two big options today if you want to actually be part of that technological engine.

One is you can go start a generational technology company. To be perfectly honest, I didn't have any really great ideas of how to do that coming out of school. Or the second is you can be a partner to these sorts of companies and help them make the really important decisions. And so over time, it became pretty clear that the second was the path that I wanted to take, and Thrive seemed like a really exciting place to do it.

I think Jeff Bezos had the same problem. He wasn't that good at physics.

Tried to do math and then physics, and then he did quant trading.

So how did you meet Thrive?

Yes. Little bit of a funny story here. So to the point of being a amateur physicist at one point, I was really into semiconductors. I think they're one of the great examples of applied physics in the world. You know, we literally have machines that zap plasma with lasers twice in order to imprint patterns on semiconductor dye.

And so I used to maintain a little substack about semiconductors. And my now partner Josh, who started Thrive back in the twenty tens, was really interested in 2021, 2022 about the idea of reshoring semiconductor manufacturing to America. And these days, I think almost all of advanced semiconductor manufacturing happens in Korea and Taiwan. This actually is a big change from history. Back in the nineteen nineties, about 40% of semiconductor manufacturing happened in The US.

Today, it's something like 10%, so drastic decrease. And, you know, as you know, and I'm sure as all your viewers know, these are probably the single most important inputs to all information technology, whether they be computers or artificial intelligence or what have you. So big question of is there a way to get America to be a major producer of these things again? Josh was exploring this and came across my substack because a a former colleague at Bridgewater where I worked before eight BC, was at Thrive at the time. And he got in touch, we started talking about semiconductors.

And I'll spare you all the gory details, but it turns out it's very difficult to reassure semiconductor manufacturing or at least would require a little bit more money than Thrive had available at the time. But this was something where I had the reaction of someone who had the boldness and ambition to think about an idea as important as that. Well, if you go back to great technologists working on great technology projects, that felt really unique and distinct. And so as it became clear that I wanted to move from being in sort of quantitative trading hedge fund world to actually investing in early stage and fast growing technology companies, I went to Josh for advice. And you know what they say, ask for advice, get a job, and now I'm at Thrive.

Simple as that. Make a sub stack.

Make a sub stack.

So no investments in semis?

Not yet. We are investors in a company called mesh optical, which is in the data center. So if you think about the great AI CapEx build out happening right now, hundreds of billions of dollars being spent each year on building out new data center capacity to train the latest generation of AI models. Within a data center, there are a few important components. There is the semiconductors themselves.

You know, NVIDIA is a $4,500,000,000,000 company as a result of being the greatest semiconductor designer in the world. But there are also a lot of other technological components. One of these is called the interconnect, which is what moves data from one point in data center to another. And MESH is a pair of founders from SpaceX named Travis and Cameron who actually knew back from college and then went to work on the Starlink Photonics team, so the team that uses lasers in space to pass data from one satellite to another to give us Internet. And they are bringing that innovation to the interconnect space in data centers.

And so we led the seed for that company at the beginning of this year. So that's that's where we've invested in data centers thus far. No chip companies thus far.

Okay. Alright. Well, we'll cover the whole stack because I I definitely wanna get your take on where the value accrues in AI. But before we get there, let's talk about your portfolio and your thesis around that. So what companies are in your portfolio and what board positions you have?

Totally. I'm pretty lucky to work with a few really, really exciting companies. I think one of the great privileges of this job is that you don't just get to work on one really exciting problem, you get to work on a few with several founders of the potential or are generational. A few companies that I work very closely with, Cursor, automating a lot of the drudgery associated with coding and being the ultimate AI pair programmer for a lot of developers. I think when we invested, there were a couple tens of thousands of users and, you know, low single digits million ARR.

Fast forward to today, I don't think the company publicly publishes revenue, but call it in the many, many hundreds of millions of run rate revenue and many millions of developers using the product. And that has just been an incredible growth story in a span of just eighteen months. I think one of the really wild and exciting things about the AI era is that the timelines are getting compressed in a really radical way. I had the privilege of speaking to Michael Dell actually a few weeks ago, and as one of the great CEOs out there who has lived through both the Internet era and the AI era and played a big role in each, I asked him how he thought about the difference between these two, and his line to me was, in some ways, very similar in magnitude of impact. But whereas the Internet era was like playing chess, the AI era is like playing speed chess.

And I think that's what we're starting to see with those companies. And Cursor, founders there, are some of the greatest technologists I've ever worked with, and really exciting to see them change how an entire discipline and way of work is done in a small, small window of time. Worked very closely with a company called Wizz, which does cloud security. If you think about the internet created the first vulnerabilities of web technology, you could actually access documents and files and servers through the open internet, so we got firewalls. The next wave of information technology was the cloud, so we moved all of software workloads to the likes of AWS and GCP and Azure.

But in doing so, we create a lot of net new ways in which software could be accessed and be made vulnerable. Wizz was started in 2020 with the goal of securing cloud software for the world, as started by a really incredible team of Israeli entrepreneurs, Asaf, Roy, Yinon, Ami, all who had actually worked on this problem for a little while earlier, but acquired by Microsoft, built out the cloud security business at Microsoft, and then built Wizz, another sort of amazing success story in a very short amount of time. And Google announced the acquisition of that company back early this year for, I think, what was the largest sum, a startup has ever been acquired for. So another really exciting one. If you talk about, OpenAI or or physical intelligence or Nudger others as well, but those are a few that I've had the privilege of being, close partners to founders for.

So cursor is super hot right now. If you didn't know that.

Yeah, it's it's news to me.

I'd love to know how did you meet Michael and their team?

Yeah. So Michael actually met when he was working on a different idea. This is I think one of the great lessons of early stage investing is ideas change a lot. People are really the constant that you want to be focused on. So I met Michael back in late twenty twenty two.

But even in that moment, I think with great founders, there's this almost electric energy you can sense in the first meeting. And shortly afterwards, Michael and Aman moved to San Francisco. They actually merged with another company where they got their other two co founders, Swale and Arvid, and they started working on the first AI IDE, integrated developer environment, which is sort of the text editor where coding happens. And when they put that out, I tried it and was an early user of the product, And it was definitely one of those magical one way door moments. Like once you walk through a door like that, you can't knock through a door like that.

And so, you know, myself and my partner Miles spent the next year trying to see how we could ultimately partner with them. And fast forward to May 2024, we finally convinced them that we were the right sorts of people to bring on to the cap table.

That's wild. And to the point of just, I think, like going hard at it, You were cited at the Colossus profile of flying into a war zone. And this goes after, you know, the second company that you mentioned, Wiz. So what was that like? And tell us everything.

Yes, it was it's definitely one of the more memorable moments of my career. I think it comes down to we are willing to do anything for our companies. And we want to show our companies that if we're gonna be the right partner, they should know that we're willing to do anything. And so story with Wizz is I actually met them shortly after I joined Thrive for the first time. Actually, if you want a fun story, join Thrive.

Josh had this really great idea of everyone at Thrive should go to its city outside of core of venture. So not New York, not San Francisco, and explore it for a couple of weeks. So I went to Tel Aviv. I'd never been there in my life. And if you're in Tel Aviv in 2022, the talk of a town is this really buzzy, exciting new cybersecurity company, Wiz.

And so I just spent two weeks trying to figure out what was the right way to meet this really cool company. And eventually, got a meeting with Asaf and Josh, I remember to this three way zoom where I was actually back in New York at the time, Asaf was in Tel Aviv, Josh was in Tokyo at the time. So you were really spanning time zones. And to the point of electric founders, I mentioned with Michael, it was immediately clear this was not your mom's security company. Very, very different.

I think many great security companies in the world, they're often a little bit more sort of risk mitigating, you know, might say cover your butt if you want to be a little bit risque about it. Wizz is not like that. It is a software infrastructure developer platform. I think one of the most shocking things I learned on that first call was that 50% of Wizzes users at the time were software developers, not security people. Very different than how security is traditionally done.

And so I think we were pretty quickly sure of the fact that Asaf was this wildly humble, charismatic and brilliant founder. And he was working with three other co founders who complemented him in incredible ways across product and technology and marketing. And this was among the most unique security products we had ever seen. So similar to cursor, wasn't like we wrote a check that day actually spent a year or so building a relationship with the company, trying to simulate acting like partners well ahead of actually being partners. That's just sort of how we operate.

And then we get to December 2023, 2024. Asaf gives us a call and walks us through the latest numbers, and Josh and I look at each other and we realize we absolutely have to invest in the company. It's one of the most beautiful software businesses we've ever seen. Now the problem is, the Israeli Gaza war is going on at the time, and it's not super easy to get into the country. And so by hook or by crook, we make our way to Tel Aviv in, you know, twelve, twenty four hours.

We land, a soft and generous enough to get dinner with us for four hours, and we talk about the future of the company and their ambitions. And, again, immediately clear they're thinking about Wiz on a different level than trying to just build a tool, really a different way to sort of build cloud software. And by the end of the dinner, we definitely want to invest. So handshake on a deal, and we're lucky to be investors in the company.

I definitely have a bunch of questions off of this. But what was mentioned in the Colossus piece was that no other investor would fly there at the time. So was this a highly competitive round and you felt you needed to go there to close the deal?

Yeah. I I think it's a great question, and I would frame it a little bit differently, which is certainly, I think our philosophy at Thrive that Josh taught me is that the people who win deals are the people who want to win deals the most. And so we always have a leave it all in the field mentality. At the same time, when we're partnering with companies or we're discussing with companies whether we're the right partner, we don't really do it thinking about other players on the field. You you play against yourself, you don't play against others.

If our founders were going to be in Israel during what was a trying time, we wanted to be in Israel and show them that that mattered to us too. And so I think it was much more a statement around the types of partner we wanted to be to the Wizz team versus, you know, the competitiveness of the deal.

And then walk me through diligence. So you said that it had amazing numbers, but like what does that mean?

Yeah. So Wizz, I think, exemplifies like one of the key things in enterprise software that I'm surprised not more people talk about. But oftentimes enterprise software, they're all the classic things you might care about, margins, retention, etcetera. Wizz looked, you know, 11 out of 10 across all these. I think they'd almost never churned one customer in the course of all the time between when they started the company and when we were looking at this round.

But a really special aspect of the business is often what is the size of the deals you can sell versus the speed at which you can sell deals. I actually think often looking at this ratio is a really, really powerful metric of basically how many dollars can you turn as a company and how quickly can you change a market. We just had I think the very best ratio of deal size to speed to implementation of almost any company I've ever seen. And it makes total sense. If you're a sales rep at Wiz, you can get on a call with a customer, you would ask them for their cloud API keys, you can pull it into their side scanning product, they will scan your environment, they will give you a list within a few minutes of all the vulnerabilities you didn't know you had.

And what customer is not going to look at those and say, Oh my God, I have a bunch of vulnerabilities, but I'm not going to buy the product that showed me the fact that I was super exposed. And so Wizz was closing on these like very healthy 6 figure deals in a matter of weeks or months, which was just unprecedented. You normally you have small deals and fast cycles. You have big deals and slow cycles. We had more or less figured out how to actually cut the Gordian knot and get both.

So that felt really special. I think the second was I mentioned this developer population on the platform. It actually felt more like a software infrastructure tool, like a Datadog or a Cloudflare or the like than a traditional security tool. It wasn't a check the box compliance workflow. It was actually how do you surface issues to engineering teams, provide them with a context to fix those issues, and then remediate them.

And that that felt very unique and special too. And I think finally, most products like to say they're platforms. Very few products are actually platforms. Wiz was actually a platform. If you looked at the number of products that were being adopted across different areas of the stack, they had code security on the left hand side of the stack.

They had cloud infrastructure security in the middle of the stack. They had runtime security. So actually looking at the live software workloads running on the platform and seeing all three of those getting really healthy adoption rates in an end to end way for a company that was barely four years old at the time, that was really, really unique to you and gave us a lot of confidence that the company is going to have not just an act two, but probably an act three and four as well. And I think the mark of a lot of great companies is that their first product gives you the right to go do and build some really exciting second and third products.

So these are both software companies, but I've heard you might be the hardware guy on the team.

I do have that reputation a little bit. Why? Physicists? Yeah. When when you're growing up as a physicist, like, you really come to appreciate hardware and, like, tinker around with it.

I also think if you're a technologist and optimist in this moment, the barriers to entry to hardware are coming down a lot. Okay. You know, input costs are getting a lot cheaper. And these days, LIDAR costs are a couple $100 a sensor. Back in 2014, so barely ten years ago, there was something like 75,080 thousand dollars a sensor.

So wild decrease. Software is making it a lot easier to build hardware tool. I mean, you live in San Francisco. We have self driving cars that I think increasingly outnumber the number of human driving cars in the streets. So we just build a lot more interesting things with the software intelligence layer than we used to be able to do.

And then in addition, there is a generation of founders that have been trained at the first wave of really great technology companies. You know, if you were Elon starting SpaceX in the early 2000s or Palmer and Brian and Trey and Matt starting Androle in the late 2010s, there wasn't actually a huge population of pre existing startup hardware trained talent to go draw on. So they did amazing works of heroism and built really important businesses. The nice thing today is that those companies have now trained a lot of really amazing engineers that know what it means to build software and hardware technology that became scaled to very, very high volumes. And those founders can now look at these host of new problems that are available to them because of the changes that have happened in technology and go chase them.

And so I think as an investor and someone who's really excited about companies that can counterfactually impact the world, that can make the world look physically different in some meaningful way, the number of opportunities now in hardware are far greater than they've been any time in the last twenty years.

I think you were cited, and we talked about this before, but you were cited that you wanted to become the CEO of Lockheed Martin.

I when I was a kid, this was a this was a childhood dream. Now not not still a childhood dream, I think, too. I was born the very late nineteen nineties, and then there was no SpaceX. There was no Andoril. There was no Tesla.

So where I'm born today, I'd like to believe I'd like to be CEO of one of those companies. But at the time, if you're, you know, a hardware nerd and you're a physics nerd, what are the companies really excited about? The companies that take on really big technology projects. And, you know, say what you will about Lockheed Martin. I think they did take on some of the most ambitious technology projects of twentieth century, the SR 71 Blackbird, large amounts of the stealth fighter program, large amounts of the missile program.

And so I think really incredible technological accomplishments. And so probably what I really meant, you know, when I was early teens, young kid thinking about that stuff is I just wanna be at a place where I can push the envelope on how really great technology gets built.

Who knows? Maybe you'll take over Lockheed Martin and, I don't

know, become CEO. One day. It's never too late.

It's never too late.

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So it's interesting because you do both software. You do hardware. I wanna talk about the revenue between the two, the different types, and then also the business model. So how how come you mentioned a little bit now, like, now the window for hardware investing is a little bit more attractive. But on the business model side, can you break that down?

Like how like, it's never been an attractive VC investment. So why is it attractive now?

Yeah, all those people invest in the early stages of space and and roll really regretting it. Right? They did a horrible job. Horrible job. I think you're pointing towards something which is genuinely true, which is that hardware is definitely harder than software.

It is harder because you actually have to build more product. It is harder because that product is more expensive to build. Know, it's not like writing bits, which are more or less free. It is atoms, which, you know, costs money to put together. It is hard because there's often an operational aspect to hardware investing where I don't just have to build a product and press a ship the binary button on a computer.

I actually have to have a manufacturing line and a deployment line that gets us out into the real world. And that said, I think hardware businesses can be enormously durable and attractive once you actually get them off the ground. You know, it's really hard to imagine who is possibly going to disrupt SpaceX at this point, knock on wood. Or, you know, water is going to be someone who could really go out and disrupt Androle. And that's because I think when you get over the hump of these really, really hard industries and problems, you actually have built something at scale that is very hard to quickly replicate.

Whereas in software, not true for all businesses, but the barriers to building software are probably lower than ever before too. And so I think there is a dynamic here of, yes, there are bigger fixed costs to getting hardware off the ground, but these businesses can be really unique and powerful once they do. And they often actually have a very geometric growth rate to them. I was looking at the revenue curves actually of Anerole and SpaceX and Tesla the other day, and they are some of the only companies that have actually accelerated growth at scale, which is to say they are growing at a faster rate at multibillion dollar scale than they were when they were small. Normally in a technology company, you have a deterioration of growth over time.

I think the difference with hardware is actually the bigger you get, the bigger markets you can access, and the more people trust you to take on big problems. Like take Androle, for instance. When they were an early stage company, you know, they were really great about getting on the field. They, I think, won a program of record, which are the very big budget line item contracts in the National Defense Authorization Act within two years, fastest timeline since the Korean War. But those deals were good and they were on the order of tens or hundreds of millions of dollars.

Now Andrew is being tapped for many of the great technology programs that the US military is thinking about across all domains from air to space to Navy, etcetera, which means that the number of contracts they're eligible for and the number of the amount of revenue they can go after is quite a bit larger. And so again, I think actually expanding the aperture of what they could do or think SpaceX. You know, for the first fifteen years of the business, SpaceX was a launch business. Great business. Lots of free cash flow, only provider in The US, maybe the world that could bring mass into orbit at a competitive price point.

I don't know if you know this, but actually before SpaceX, we had to rely on the Russians to bring people to the International Space Station. So good we can have an American company doing it now. But it created the opportunity for them to build Starlink, which is now one of the most powerful Internet constellations in the world, and it's actually driving a very, very large majority of overall free cash flow and revenue for the business. And so again, I think these later age second stage acts of hardware companies end up looking a lot bigger than the early stages. There's a very distinct characteristic.

That said, great businesses are great businesses, and you do need to make sure that these things are still high margin, great products, great founders, etcetera.

There certainly has been a surge of funding that's gone this direction.

Yeah.

And there's also bottlenecks that come with it, whether it's policy, government, etcetera, and different kinds of regulations. So how do you see this current stage of hardware in a cycle? Do you think that we were in a bubble? Are we in a bubble? Like, what's the, like, I guess, temperature on the ground?

Yeah. I think temperature on the ground is the returns always accrue to a small number of companies. Venture is the asset class with the worst beta and the best alpha of any financial asset class, which is to say, you know, the best companies are gonna give you the best possible return of any possible equity instrument you can invest in, and the index is probably gonna give you pretty mediocre returns. I think hardware is gonna look no different than that, which is to say, I am fairly confident that we are going to produce some of the world's most valuable companies in hardware over the next decade. Even right now, five of the 10 most valuable companies in the world are hardware companies, Apple, Nvidia, Broadcom, Tesla, TSMC.

At the same time, these businesses are hard. There aren't that many people who are really great at being combined hardware software thinkers. And so there's probably going to be a lot of companies that don't work. That's just the nature of company building. But I think the really exciting thing, the types of companies we invest in are N of one founders, like the Camerons or the Travis's or the Palmers or, you know, also investors in Nudge, like you mentioned, Jeremy, who used to help run engineering at Neuralink, Fred Ursson, who was one of the cofounders of Coinbase, who are working on these very unique missions.

I can't think of anyone else who is using noninvasive ultrasound to stimulate brain activity like Nudge and try to cure neurological illnesses like depression, pain management, addiction, etc, and who are doing them in ways that are gonna be very, very hard to replicate in the future. And I think those companies that can actually solve the problems we're looking at are gonna be valuable no matter what.

Okay, let's talk about nudge. Because you brought it up, and it's really fascinating. Tell me everything.

Well, I'll tell you all the public things. I think the nature of real estate technology companies is you want to make sure that the the correct secrets are kept secret. But and the way I would think about Nudge is the human brain is basically one of the last frontiers of engineering. For a long time, it's been considered a science problem. You know, something where we'll study it in the clinic, we'll study in the lab, but we don't really build products for the brain the same way we might build products for other parts of the economy or even for human health.

Nudge is taking the approach of what if we could engineer the human brain or bring engineering solutions to the brain's problems? And I think for a problem like that, you want people who I describe as life's work founders, people who, no matter how much money they have, no matter what island you put them on, only have one missionary purpose in life in mind. And I think Jeremy and Fred are both that. Jeremy, like I mentioned, you know, one of the early employees and key leaders at Neuralink, another really amazing neurotech company. Fred was actually one of early investors in Neuralink and obviously built an incredibly successful company with Coinbase.

And I think they're both convinced that the most important thing they can do with their lives is go and actually build a solution to neurological illnesses. So how does Nudge work for those who haven't heard of it, which I imagine is most people right now, but hopefully not very many people in the future. So much like we use ultrasound to image pregnant women, you can use ultrasound waves to actually simulate brain activity. They're very safe. You know, for we're comfortable taking images of babies, we should be pretty comfortable using them on ourselves.

And so what Nudge does is it will take ultrasound waves, it will direct them at very, very specific points in the brain that they've identified as being associated with some type of neurological problem and use those waves to stimulate the brain and actually change the neurological activity that's going on there. And ultimately, goal is how do you have a treatment for neurological illnesses that is easier than taking a pill? Imagine if we could treat, you know, really, really tough illnesses like depression and addiction by you wearing, you know, a set of headsets on your temples and that actually doing meaningful amounts to cure versus struggling with an illness over a prolonged period of time. So really inspiring mission. The company is early, but moving really, really fast.

And so if there are any engineers out there that are excited to work on engineering the brain, I think one of the best places in the world to work.

So what's the for most people, what's the difference between Neuralink and then also just traditional, like, clinical brain stimulation?

Yeah. So Neuralink, really amazing company as well. You know, I I think incredibly highly of DJ and Elon and the entire team there that have done huge feats of engineering. I would think about them as starting with the read side of the brain, understanding the brain. They use a invasive neurological implant.

So if you are a paraplegic or someone with ALS, they will implant a device into your brain with a very relatively easy surgery. They've automated to a high degree. And as of today, this gives you what is called, telepathy in classic cool Elon terms, which is to say, I can now control any digital device with my brain. And for people who have paralysis of that degree, this is a life changing experience. So you can imagine you have ALS, you actually no longer able to speak, you can communicate with your loved ones for the first time.

You were paralyzed in a ski accident, you can now actually go back to work and do meaningful economic work for the first time by interacting on a computer. So they're on the read side. Over time, I think they'll actually do a number of things that are really helpful on the right side too. You know, things from their road map like blindsight, which they're going to try to restore sight to the blind. If you imagine things that are actually going to try to restore limbic motion, it's basically biblical miracles.

Pretty amazing we live in an era where this is possible. Mostly on the stimulation side, so they are not so much reading what is going on in the brain and interpreting it, but actually targeting specifically affected areas of the drain and trying to stimulate it. And so the closest comparison that we have to this today in modern medicine is something called TMS, which is transcranial magnetic stimulation, where this is really a version of what you might have seen in movies called electroshock therapy, where people will more or less use, electrodes to zap the brain. It's actually pretty effective. It is very unpleasant, and I I have not personally tried it.

But What

kind of diligence is that? I know.

I know. Totally slacking here. Did you try it before the podcast?

Yeah.

Yeah. Must be a big believer in nudge then.

I love nudge. Excellent.

But in case, oftentimes people have to do this treatment over many weeks. You have to go to clinics very far away from where you work. And so the what's called the second line adoption of this treatment, the number of people who will try this after, you know, first line treatments in depression, fail is very, very low because no one wants to do this. And so not only do we think that ultrasound can be more effective than TMS, but, you know, wearing a pair of headphones in your head way easier than going to a clinic to get zapped. So I think hopefully evidence that this is not only possible, but there's just a much, much better way of doing things.

Will you try it?

Nudge? I'd love to. I mean, I think it's one of the exciting things about Nudge is that you'd imagine a world where everyone should use Nudge. Because today, they're treating neurological illnesses. But if we can stimulate the brain to get desired outputs, why shouldn't I be be able to stimulate my mood or my energy levels or maybe my focus levels.

And so I think there is a world where, actually, when we do this podcast again in ten years, we're both wearing headphones on our temples. They're getting us really dialed in to ask great questions to each other.

Everything is computer.

Exactly.

That's really funny. I wanna take a step back a little bit and talk more on the funds thesis and the thesis on concentration. Yeah. So Peter Walker just recently he's a researcher at Carta. He recently shared this chart that showed spray and pray versus highly concentrated funds.

Turns out highly concentrated funds, typically, like, 20 companies per portfolio outperforms spray and pray. But spray and pray looks pretty good because you have lots of potential bets. So I'm curious with rumored and reported maybe it's not reported. Maybe it's rumored 25,000,000,000 in AUM. How do you guys think about where to concentrate your bets?

Yeah. I think there are two aspects that really matter to hit us, which is one, you have to pick a strategy that is authentic to how you want to operate as an investor. My partner Karim often has the line that mathematically, there apply a lot of ways we can make money as a venture firm. The question is, what feels really aligned to the founders we partner with? And I think above all else, I can talk about why concentration we think is a really great financial strategy, and I will, but the most important thing is it allows us to be really deeply aligned with the founders we work with.

If you are working with a life's work founder, this is a portfolio of one for them. And we may have a portfolio of a few, but we really shouldn't have a portfolio of that many, because all the wins should really feel great and all the losses should really hurt. And we should have real skin in the game. And so I think the way we'd like to set ourselves up with is that if we're gonna invest in someone, they should really believe that the success and failure of the company really matters to us as investors. And so I think there's actually an emotional and ideological aspect to this.

Now there's also just a reality of the power law, which is that, I don't need to document this for you. It is very clear that a small number of companies drives a disproportionate amount of the economic and social value in the world. I think right now I'd have to check the latest stats, but the MAG seven and the NASDAQ, the top seven stocks represent 50% plus of the NASDAQ's market cap. And so that that gives to show you that few companies really, really important. And so our concentration strategy just sort of reflects that reality.

We want to invest in a small number of companies that are on the right tail of the distribution, the power law, that are going to be the most important to how the world works over times. And that's not to say there aren't other great companies that might make us money we can invest in with a more index like approach. But in the way in which we think we can deliver differentiated, correlated returns for our partners is through investing in the very best companies. And once we think a company is of that stature, concentrating as much capital into that company as possible.

Perfect tee up. Okay. We're gonna talk about OpenAI. Great. I pulled from Patrick O'Shaughnessy's original interview with Josh way back when, and Josh said concentrate on the most exceptional businesses and hold on to them over time.

Case in point. Yeah. Concentration strategy. But I also was able to find some data that OpenAI rounds reportedly led by Thrive Capital date back to 2023. And this was like right around inflection point and like the chatty bitty moment.

So that started in January 2023 at a $29,000,000,000 valuation. Next step up was February 2024 at an $86,000,000,000 valuation. After that, October 2024, a $157,000,000,000 valuation. And then most recently, October 2025, hitting a $500,000,000,000 valuation. So how did you get involved in OpenAI?

Yeah, I think people probably overestimate how popular the company was in its early days, if we want to be perfectly honest. Think Sam and Ilya and Greg and everyone else at the company worked on this project for seven, eight years before others realized how valuable it was. And so actually, if you want to go back to 2022, ClearOpenAI was a really exciting company. We had been spending time with them many, many months. Josh had known Sam for a long time.

And we actually got a demo of gbt4 in November 2022 before it was publicly released in March. And it was one of the most astounding pieces of technology we'd ever seen. I think these days, there's a lot of talk of what is AGI? What is an AGI? You know, we could debate that here if you want.

Debate it right now. Right now. What does it mean?

What does it mean? You and me both have it stumped.

Okay. Okay.

But the marketing is definitely true. That that model passed the Turing test. You know, there there was all this talk for many years of the Turing test was this really important moment. You wouldn't be able to recognize it, or a computer that was capable of acting like a human or having the intelligence of a human. GBD4 was that and we don't talk about it anymore.

But that was a really important moment in technological history. And that felt really exciting. At the same time, I think a $29,000,000,000 valuation or thereabouts is undoubtedly a high price for a company that Chatchip Key hadn't even launched for. And so when we invested in OpenAI in that round, I think we were one of two firms that gave the company a term sheet. And this was actually more an artifact of investment that required belief than sort of competitive edge, so to speak.

Now, if we fast forward course of three ish years from now and from there, so much about the company has changed. We looked at our original investment model. There was no mention of Chatuchui tea in there. Now it has, you know, more than a billion users and is on its way to becoming one of the most dominant and important ways in which people access technology, the Internet, AI. I think it's the front door to AI in many ways, and the company has totally changed in that sense.

And as a result, I think when you see these new levels of value get unlocked, you're able to have real confidence in the dominance of the business and its centrality in the arc of technological history. Yeah, your confidence in the company should increase, and yeah, you should invest a lot more in the company. And so I think the past few years have basically been a story of us having a front row seat to that and getting to see this arc unfold up close.

I think one of the probably most impressive things to come out of it is the team. Yeah. Because everything that they've pushed out would seemingly be a tremendous force. Like and they continually do it over and over and over again. This is something I talked about with Apoorv from Altimeter.

They're also investors in OpenAI. And it was almost not so much as momentum as a moat, but speed as a moat and continually pushing things out and trying things. And it went back from voice to text, text to voice, all this kind of stuff. And it seems like every month, every week, every day, there's something new coming out of that company. And so how do you think about how they have recruited, they've assembled team and the talent around it?

Yeah. I think one of the great privileges of my career has been able to spend time with the OpenAI team. Not just because they're great people and brilliant thinkers, but the talent density, as you're pointing out, is really unprecedented. And I think there are good reasons for this. If you are building what I think is one of the most important technological innovations since the atomic era, forget the Internet, yes, a lot of the really brilliant people in the world are going to go work on it.

Now I think the really cool thing about OpenAI is they've attracted a lot of the star power researchers. You know, Ilya literally invented Alexten back in the day, which kicked off the deep learning revolution. But a lot of the really great researchers at OpenAI have come up through OpenAI and were not famous entities or well known people before. But Alec Radford, who was at the company for a very long time, famously did not even really study AI when he was a student, and was one of the most prolific impactful researchers at the company. And I think one of the other things OpenAI has done really well is they've actually looked for young talent in the AI era.

I think this is a really important thing, one of the things that Cursor has actually been really attuned to as well is the people who almost hold the model weights in their brains because they've been brought up thinking about AI natively are really, really good at the creative thinking and experiments and hypothesis testing that is necessary to push the performance of these models. There's Sora, a recent OpenAI product launch. I think if you looked at the average or median age of that team, I think it's in the low twenties. It's pretty amazing. So long way of saying, you know, OpenAI one has the benefit of, yeah, if you're a great, you know, computer scientist, probably should be working on, you know, building some type of super intelligence.

And two, they've been really risk forward about trying to find people who could be great versus who are already great. And I think that has actually allowed them to bring up and train several generations of great researchers in the company itself versus just needing to hire the people who've already been proven entities.

How do you think about the evolution of OpenAI and where it goes to? One of one of the sponsors that proudly sponsor Sorcery is Turing. And so I've gotten I've gotten exposure to the AI research side of things or an AI research accelerator. So they help out with the models.

Yeah.

And right now, they're noticing the severe shift in the last, like, quarter or two on imitation data, synthetic data to reinforce learning. And so I'm curious how you're seeing it on like the technical side and then also like on the application side.

I think AI is a little bit like semiconductors in a sense. If I'm allowed to go back to semiconductors, a great touchstone. And that's in the sense that there are many, many waves as we're trying to get better and better performance. You know, with semiconductors, we used to have, you know, single core semiconductors, then we couldn't basically squeeze anything more out of the single core. So we went to multicore, then and we went to GPUs.

I think we're seeing something very similar with AI, which is that, you know, we started with pre training back in GPT one, GPT two era, GPT three, that took us to GPT four. Then, you know, we started using a lot of post training techniques for chat GPT, supervised fine tuning, reinforcement learning with human feedback, and this is what allowed the models to be less alien intelligences and more helpful assistance. You know, and now as a lot of the low hanging fruit for those gains have been squeezed out, even though there's probably a lot more to do, reinforcement learning has been sort of the next big paradigm shift in AI and where a lot of the resources are going. My guess is there's going to be a couple more of these. This is not the end of the story.

You know, we are basically figuring out in real time how to do the alchemy of turning pieces of metals into, you know, thinking machines, so to speak. And that is a really tough and challenging thing. And I think the really exciting thing about OpenAI is that, yes, it's one of the great product companies of today, but it's also a research effort. These are not things that we have fully discovered and figured out yet. So I think a long way of saying the ultimate competitive advantage for the labs and for OpenAI in particular is actually being able to constantly figure out what the next paradigm is, even as you're productizing and implementing them.

The last paradigm, and I think one of the highest testaments I can give to OpenAI is that every single major paradigm in large models at this macro level that has been very successful to my knowledge has come from OpenAI or at least been originated at OpenAI. And I think that speaks really strongly to their ability to continue to push the frontier of research going forward.

One of the lines that comes out of cursor is what comes after code?

Yeah.

What comes after OpenAI? That's the question for you.

I think the beauty is one hopefully OpenAI is going to be an enduring technology. And so I'd be very surprised if in the near term, were talking about an after OpenAI. Is there an after Meta or an after Google? I think the the better framing of the question, if I could tweak it would be something like, are the companies that can now be built as a result of OpenAI? I think there is a what comes after SaaS, that is a more interesting way of about this.

And we had an old way of building software. There are these cloud primitives, we build these great digital apps on top of them, a lot of really amazing companies that we had the privilege to invest in. Now there's a new substrate for technology, which is what if you could productize intelligence and call it via API or fine tune a model with it? And I think that it engenders an entirely new breed of software companies. So I don't think it's an after OpenAI, I think it's an after SaaS that we're going to see.

And so, you know, we're seeing the early signs of this and then like Cursor where we're actually thinking about products that can work with you as a as a sort of collaborator in order creating work. We're seeing this with products like Harvey on the legal side where they are doing work, as well as just acting as an assistant. We're seeing this with products that are even incumbent products. You know, Wizz for instance, now has a security assistant to help you find and triage vulnerabilities. But I think there basically is a new set of building blocks that we've gotten.

And I think the right way to think about it is software is going to look very different going forward. But, yeah, the big fundamental companies, I think they're going be around for a while.

The other standard second order question of this is impact on jobs.

Yeah.

Calculation recently had a chart out that was up to 86% thought we would have more layoffs this year in tech than in 2024. How do you and there's also I don't think it's yeah. I definitely take the under. But public companies have been reporting more layoffs. It's part of, like, a natural cycle and etcetera, etcetera.

Do you think that AI and these tools will create more efficiencies, create new jobs? Where are you in this whole discussion and debate?

Yeah, I'll give you my bottoms up and top down answer. My bottoms up answer is, I'm an investor in a lot of companies that use AI tools. I cannot think, especially on sort of the coding side and engineering side of a single one that has laid off engineers because of these tools. I think maybe it allows them to grow without adding quite as much headcount. But really what it has done is allowed them to go after a much wider range of problems.

You can actually make everyone the 10x or proverbial 100x engineer in a really exciting way. And so thus far, I think just empirically, there be some turnover in economic centers? Of course, there always is, but it's actually been much more of an augmenting substituting technology. And then I think as we look into the future and look beyond just, you know, cursors of the world, but to this notion of what does it look like to have very powerful intelligent AI more generally, there's just a lot of problems that as a species we aren't working on right now that we should be working on. You know, way more people should be working on cures to oncology.

Way more people should be thinking about what does it look like to actually sustainably mine the world's natural resources? What does it look like to actually make us, you know, a space faring species? And I think the beauty of AI is that we're gonna be able to reallocate a bunch of human brainpower, firepower, creativity to these most important problems and away from the things that, you know, have been great jobs to date, but are not the highest marginal use of humanity's creative and intelligence potential. And so I think there's just a lot of problems left to go solve, and AI is gonna help us solve the most important of these versus less important problems.

Where do you stand in the AI bubble debate?

I think this is one where being concentrated allows us to feel a little bit better about no matter how the world works out, you're going to be in the right circumstances. And it turned out that if you invested in Google in 1999, in 2001, in 2004, in 2005, and you were a long term investor, Google might have had some variability in returns, it was a pretty great investment. Likewise with Amazon, likewise with Netflix, likewise Microsoft. And so I think we really just think about what are going to be the enduring companies versus trying to time the market cycles. And so that's my honest thought.

You know, think there's a lot of value will be created out of AI. I actually think in a lot of the rounds we participated in, they felt eminently rational to us. But I think the most important thing is be in the right companies and trust that if you've picked the right companies and want to be the multi decade holders of those companies, the rest will wash out.

And where do you stand on the exit environment for this? OpenAI is one of, if not the highest valued private company.

So yeah,

do you go public? Can you? Where like, what do you think about this in front of private companies?

When we invest in companies, it is almost always with the intention that if they want to, they can at some point be a standalone public company. I don't know OpenAI's particular plans for this, but I think, you know, we should expect that most great technology companies will be public companies over time. Probably takes some, in some cases, a little bit longer than in the past, in some cases, maybe shorter. But I think beauty of American capitalism is that everyone gets to participate in the growth story of these really important economic engines, and I think we think that's morally the right thing to do. And, also, we think this is how most companies will choose to represent themselves over time.

Interesting. Well, if you didn't know this, Sorcery sponsored by Brex. Awesome. Amazing.

I'll throw out my ramp card in my pocket right now.

Do it. Thank you. That's so generous. So Brex is all about spending smarter, moving faster performance. I'm really, really curious about this question.

Because Thrive is like such a stealth fund, a huge fund, and you do a lot of different things from incubations to funding very large rounds of companies. How do you think about performance as a team? And like, how do you think about performance as an investor on a very small team?

We think about decision processes a lot more than near term outcomes. I think when I worked at Bridgewater early in my career, Ray Dalio had this very famous line of focus on the swing, not where the ball goes. And I actually think that's very much how we operate, which is that we want to have the shot on goal with the most exciting companies. We want to have the right conversations around those companies. We want to be, as my partner Miles likes to say, paranoid but patient, always thinking about what could be, but not necessarily rushing into things.

But I think that structure is really what we anchor to. We have seen plenty of companies that didn't like look like they went anywhere for the first few years. You know, if you were an investor in OpenAI, you know, it a nonprofit in 2017 and 2018, and even sort of a capped nonprofit with profit like shares in 2019 and 2020, you might have thought, oh my gosh, what what is this thing gonna do? Is it gonna go anywhere? And of course, now one of most valuable companies in the world.

By contrast, I'm sure we can think of plenty of companies that looked hot coming out of the gates at first and at some point, looked less good thereafter, which is all to say when we make decisions as a team is that, you know, no matter what performance looks like for this company in the next one to two years, we're going to be confident that we made the right decision because we looked at the right inputs for this. And so I think the worst types of investments to make are investments where if the numbers change one quarter or one year, you would all of a sudden start to feel bad about the company. Because that suggests to me that you're not investing against the fundamentals of the company, you're investing against the momentum of the company. And I think that is rarely the right way to capture really long term value.

We were kind of joking about this in the beginning, but I don't know what date is. You don't know what date is. I thought it was February. It's apparently almost November.

Yeah.

But what are you looking forward to in the next twelve months?

Great question. First off, I think we're in this moment where reinforcement learning, as you mentioned, is this new lever. We've seen it make its way into very few new software products. I think few products in labs, rumor has it some of the coding companies like Cursor have done some really cool things that they've mentioned on their blog. But relatively speaking, not that many RL problems and projects out there in the world right now in production.

I'm really excited to see that change. I think it's one of these really powerful things where we now have a lot of the inputs required to go automate large amounts of really high treacherous work. And I think we're gonna see software companies start to productize that over the coming months and years. So that's one thing I'm really excited about. I think the other is the point of, you know, intelligent hardware.

I think we're gonna see a real renaissance of problems that don't just have to be solved with bits. They can also be solved with atoms as well. You know, sometimes to make a real impact on the world, you actually need to move something in reality. And so we're investors in physical intelligence. You're doing this on the robotics side.

We've talked about Nudge, talked about MASH, talked about Androle, but I think we're gonna see a new wave of companies that can actually address, you know, the large swath of global GDP, you know, well north of 50% were actually affecting the physical world really matters. And then finally, I think there are going be some really exciting developments in applying AI to science. There's isomorphic labs, Thrive is a very proud investor in, which is Alphabet's drug discovery and life sciences AI portfolio. You know, there's a new company called Periodic, which is working on material science, which we are not an investor in, but is doing really awesome work on new materials discovery. And I think there's this cool question of at what point, you know, similar to our discussion on Nudge, do science problems become engineering problems thanks to the power of AI.

And I'm really excited to see how that transitions and evolves over the next few months.

It's a lot to look forward to.

I know. We're a really exciting time.

It's really exciting. Philip, thank you so much.

Thanks for having me.

Hey. It's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email, and also go deeper on our podcast interviews. Subscribe to Sorcery today, and don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.