Investing Billions - E39: Guy Perelmuter on Generating Alpha in Deeptech

Episode Date: February 6, 2024

Guy Perelmuter of GRIDS Capital sits down with David Weisburd to discuss his investment strategy, the unique portfolio construction of deep tech companies, and the potential of DeepTech. They delve into the paradox of AI, its impacts on the labor force, and discuss the ideal GP relationship and transparency. They also touch on LP value-add and the importance of overcommunication. The 10X Capital Podcast is part of the Turpentine podcast network. Learn more: turpentine.co -- X / Twitter: @guyperelmuter (Guy) @dweisburd (David) -- LinkedIn: Guy: https://www.linkedin.com/in/guyperelmuter/  David: https://www.linkedin.com/in/dweisburd/  -- LINKS: Present Future - Business, Science, and the Deep Tech Revolution: https://www.amazon.com/Present-Future-Business-Science-Revolution/dp/173542451X  -- NEWSLETTER: By popular demand, we’ve launched the 10X Capital Podcast newsletter, which offer’s this week’s venture capital and limited partner news in digestible news bites delivered straight to your email. To subscribe please visit: http://10xcapital.beehiiv.com/  The 10X Capital Podcast Newsletter is powered by Ikaria Labs, a full-service content marketing firm that partners with the top funds, fintechs, and financial services firms to grow their investor communities. To learn more, visit: https://www.ikarialabs.xyz/  -- Questions or topics you want us to discuss on The 10X Capital Podcast? Email us at [e-mail] -- TIMESTAMPS (0:00) Introduction and Guy Perelmuter's investment strategy (4:06) Introduction of Grids and what sets it apart (6:33) Discussion on DeepTech and its potential (13:20) Paradox of AI and its impacts on labor force and job market (20:00) Unique portfolio construction of deep tech companies (23:13) Strategy for consistent returns and downside protection in investing (27:03) Ideal GP relationship and transparency (33:55) LP value-add and overcommunication (39:18) Wrap up and Guy Perelmuter's multi-talented, likable GP image (40:43) 10X Capital Podcast Newsletter

The typical number of GPs that we have per fund is something like 11 or 12. You know, give maybe a little less in fund one, maybe a little more in fund three, but around 11 or 12. Ultimately, these managers, they have different styles as we would like them to have. But I think it's reasonable to assume that each one of them is going to invest in anywhere between 15 to 25 companies. So let's call it 20 companies. So that part of the portfolio gives us investments that works almost as another VC fund in our mix. So we typically will do 15 to 25 investments, direct investments as well. And normally those investments come and to a later stage in the life of the companies, we will typically do a series A,

maybe an early B, but ultimately we try to be very flexible and we try to make sure that the odds of us getting the companies right are higher because we have this kind of front row seat to watch what the company has been building since day zero. Well, Guy, I'm very excited to chat today. You have such a prolific background in terms of being an LP, being the author of a great book, Present Future. Thank you so much for having me, David. It's my pleasure. So I've been involved with investments for pretty much all my career, even though I'm a computer engineer by training and I have a master's in electrical engineering. I've been into risk management and portfolio management for 20 plus years.

And a big part of this experience has been with investing in multiple asset classes, multiple entities. So it became a very natural strategy for me to at least partially do my allocation through funds. And you have a very natural strategy for me to at least partially do my allocation through funds. And you have a very unique background. I think you have one of the most unique backgrounds of any LP that I've ever interviewed. Tell me about how your background plays into your strategy at Grids. Sure. So when I kind of wrapped up my formal education, my master's in electrical engineering, and before that, my undergrad in computer engineering, my plan was to work with AI, of all things,

because that was what my master's was back in the mid-1990s. So once this was clearly not going to happen because the state of the world back then, I mean, AI was basically a research area, I ultimately started looking for a job. And it became very clear for me that the experience within the risk management world and the banking world would become quite useful at some point, at some juncture in my career. So after about 20 years doing that, investing and managing risk, I felt that the combination

of my technical background and my financial background could make me a pretty interesting VC. So this is the path that I chose and I never looked back to. So what do you mean by that, their combination of technical background and your financial background? How does that actually help you as an LP? So if you think about the way people approach investments in general, unless you have a formal education or practical education, it is a very complex subject for you to understand. There are many nuances. How do you go about the due diligence? How do you evaluate providers? How do you look into the portfolio management style of each one of your potential GPs? So once I was

kind of formally trained doing that for two decades,, I added that with my experience in technology, my knowledge of electronics and programming, and after a while, some biology and some chemistry. Then all of a sudden, those two areas, they became almost like one integrated monolithic base of knowledge. And through that base of knowledge, I think I was able and I am able to make better investment decisions. I think one of the paradoxes of being a great LP is being able and being a great VC is being able to marry two contrarian parts or two paradoxical parts. One is the ability to take intense power law type binary risks on deep tech investments. And the other one is creating a portfolio that allows you to consistently perform and to smooth out the returns from that portfolio of deep tech investments.

So it's a perfect segue. What is grids? Do we really need another fund to fund? What is grids and why does grids exist? Right. So we like to think of ourselves not as another fund of funds. We ultimately, we employ a blended strategy. We are about two-thirds on the funds and a third traditional direct investors.

And we only do deep tech. So I think two things that really set us apart are, one, the fact that we have this very focused strategy. And two, the fact that we will use our ability to navigate and invest in some of the best GPs, early stage GPs in deep tech, to get a very good and accurate full review of what's going on in the market and access to some of the best founders out there and ultimately leverage that in a subsequent round. So I think the final touches that you need to make sure that you have a strategy that works have to do with fees. And we're very aggressive when it comes to our fee structure in the sense that we charge your typical management fee. However,

our carry only kicks in after we distribute 2x of the commitments of our LPs, which means that we are very much aligned with them. And I think one of the key arguments against funds are the overlays of fees. And we try to handle that through that very aggressive and aligned strategy with our own LPs. You eat what you kill. But essentially, I want to push really on this deep tech angle. Is deep tech like the new crypto AI rebranding? What alpha do you generate by being purely focused on deep tech? And what does that even mean? That's a great question. So let's start by trying to create some sort of definition of what does deep tech mean. And in our world, the way we see it is any kind of company or any kind of project where there is a clear technical moat around it, a clear barrier of entry where you need to have, you know, a number of years of formal education in you to be able to handle it. So PhDs, post-PhDs, researchers are your typical founders for deep tech companies.

And that's something that is very hard to copy. They normally come with some patent protection, some intellectual property. So that's a part of the world that we look at. The other part that we feel that's very important is that when it comes to deep tech, there is a very interesting asymmetry. And as a former risk manager, we love asymmetries because they do mean that you have some sort of advantage when you come into it. You don't come into it at the level playing field. There are some advantages.

And if you think about how the world has been working so far, specifically in the U.S., there has been for the last 50 years a statistic that has been kept at the very same levels for 50 years, which is science and engineering PhDs compose one in every 10,000 people in the US. That's the number for the last 50 years. So that's scarce, right? There are not many of those out there. Second thing, and so that's one specificity. The second thing is that we are now living in a world where pretty much every single incumbent, I don't care which area they work at, but every single incumbent is already very much aware that they will need to be on top of whatever technological innovations are happening in their respective fields so that don't become obsolete, so that they don't become the next Kodak or Nokia or Blockbuster. And statistically speaking, if you are a list of companies in the 1930s, on average, you will remain listed for almost a hundred years, right?

But if you are a listed company in, let's say 2025, on average, you're going to be listed for 14 years and that's it. So another asymmetry is that there will be more buyers of high technology than sellers, because again, there will not be that many people able to build and to develop advanced technology. So we feel that the deep tech angle is not the fads. We feel that this is something that will ultimately continue to drive progress in multiple areas, not only AI, but biotechnology and robotics and advanced materials and energy and so on and so forth. I didn't tell you this before the interview, but I did read your book,

Present Future. And there you talk about nano, AI, information technology, biotech. Which one of these fields are you most excited about? You have to pick one. Which one would you pick for the next 10 years? I'll not dodge your question because that would be unfair to you and to our viewers and listeners. So I would go with biotech. I think biotech is now living a phenomenal moment where the convergence

of the underlying technological infrastructure, robotics, computer vision, plus data processing, AI techniques, pattern matching techniques, and the advances, of course, in the biology and chemistry fields alone, I think they are kind of pointing to a convergence that will ultimately

drive phenomenal companies into the forefront of our technical capabilities. So I think if I had to choose one, I would say life sciences and in particular, biotechnology. What does a world in 10 years look like if the biotech revolution formally operationalizes? So ultimately, if you think about how the world has been, how the history of disease have been playing out throughout the last hundreds of years, we now live in a world where the infectious diseases, they are not the ones that are going to kill you, right? We have the capability to develop vaccines. Most of the diseases that are going to kill you, right? We have the capability to develop vaccines. Most of the diseases that killed hundreds of millions of people over the past few centuries have been either completely eliminated or now we have cures for them.

So we're now left with the big killers of our time, which are neurodegenerative diseases, heart diseases in general, and cancers, right? And these are, most of those are diseases that are associated with old age. So we are already witnessing right now the world becoming older, right? The percentage of the world that is 65 and up has never been so high, and it's becoming higher and will continue to creep up. You now have a number of countries out there where the average lifespan is already above 80 years old, which was something that just half a century ago was kind of unheard of. And we're going to see a world where the impact of living better and longer will ultimately be the most important advance for our own society that we have experienced for a number of years. And I think that diagnostics,

therapeutics, drug development, all of those areas within the umbrella of life sciences are poised to make this a very interesting run for investors that are willing to kind of correctly allocate their money into this particular field. Guy, you've been in AI since the 90s, which is something that only a handful of investors on the planet could say. What is the future of AI, artificial intelligence, and who will be the winner of the AI space in the next 10 years, in your opinion?

So I think that ultimately the trend that I think is kind of playing out in front of us is the myth of the centaurs, right? The half man, half machine being able to be the winners of this particular revolution. I think AI has been up to a number of whole starts since the mid 1950s when they start the summer of AI happened back in Dartmouth up until the winter of AI

in the 20th century. And now we're looking at a process that has no turning back. We're now living in a world of AI. And I think the developments that are going to be facing us, the decisions that are going to be facing us are going to be quite critical. But I'm ultimately very optimistic because there is a paradox that people have been studying for 150 years. It's called the Jevons paradox.

And Jevons was a British economist. And he wrote a book at the very tail end of the first industrial revolution back in 1865, where he was discussing the effects that the increased efficiency of steam engines and the use of coal would have. He was arguing that although coal was now a commodity that was much more efficient, the world seemed to need more of that and not less, because now you could do so many more things with coal than you could do just 20 or 30 years before. And this paradox has been playing out for highways. Every time you add another extra lane or two

on a highway, you continue to have traffic jams because you have more efficiency, more cars, and hence you get your gridlocks all the same. This has been playing out with solar panels. This has been playing out with agriculture, precision agriculture. You don't need so much land, but now it's cheaper, so demand increases. And I do believe that this will play out with the labor force. There is this whole panic around, oh my God, AI is going to come and eliminate jobs and make people, you know, that are not so skilled out of jobs, or maybe that are too skilled out of jobs. And I do believe that we will witness the same paradox going out with human labor. We, as, you know, workers that are able to enhance our abilities with AI, we're going to see more demand, more work.

And I think we're going to continue to see a prosperous environment for the development of multiple new skills, multiple new jobs. So I am ultimately optimistic about the trend that AI is going to start. And as it comes to winners, AI is a very different animal when it comes to innovation, because for the first time, the big guys, they have the upper hand, right? The big tech companies like Meta, Amazon, Google, and Microsoft, they do have the upper hand because the massive data that is required, the massive processing power powered either by NVIDIA or by other silicon companies, this is not going to remain the same. So I believe winners are not going to be the players that are on the surface of this revolution, on the application layer, if you will. I think the winners are going to be the ones that are going to be able to build tools that will be under the hood, that will be connected to the puzzle of infrastructure pieces that will need to be added on as we advance new software architectures and new hardware architectures. And I think this is going to be a very exciting time over the next few years.

So it seems like from the outside, OpenAI is realizing the commoditization of the LLMs, and that's why they're building essentially the App Store for artificial intelligence. There'll be some winners there, similar to the Apple App Store. When you say infrastructure and winners in that case, what do you mean exactly? What are some spaces that you're really excited about? So let's go back to biotechnology, for instance, right? It is probably not very wise if you want to train or use or leverage an existing LLM that is not specialized into your realm to develop a new drug, a new diagnostic tool, a new therapeutics tool. So I think the winners are going to be the ones that are going to be able to hear.

You are a microbiologist or you're a chemist or you are an expert in protein interactions. I'm an expert in data analysis and computing. I am able to look at the world of biology or chemistry or whatever. And I'm able to kind of create an LLM that is an expert with no noise, with no hallucinatory biases that will power your application or will power your research. So I do believe that those architectures where you need curated data, where you need experts kind of chiming in on how we're going to go about the modeling of that library or that particular application, that's where there is a ton of value.

And I think this is not restricted to biotechnology. I think this is true for manufacturing, for logistics, for retail, for any food, beverage, any kind of big business area you can think of. I think these guys will be able to benefit from this architecture that is being built before our eyes. We saw a month ago the attempt to take over of open AI by a movement called Effective Altruists or EAs. Their argument would be that they are trying to keep Pandora's box from opening and AI from coming in and potentially, even if there is a 1% chance that this would happen, could potentially take over and destroy the human civilization. What are your views on the EA movement and effective altruism?

So ultimately, I've learned over, you know, 20 plus years working in risk management that it's very, very rare for whatever scenario you're preparing to, the worst case scenario you can imagine that this will be playing out. It's usually much worse and usually caused by something you never saw coming, so I do believe that people are probably focusing on the wrong side of the problem. I think that ultimately all those initiatives, right, that you can compare a little bit with what the Luddites did during the first industrial revolution, throwing sabots inside the weaving machines, rebelling against the

machines. I think you can ultimately make a parallel because, again, history doesn't repeat itself, but it rhymes. And now people are pushing back a little bit on that front. But I think what people don't really realize is that, of course, we're creating an entity, if you will, an artificial entity that has computing powers, processing powers, data analysis powers that far suppresses our force. But we still are able in, you know, for the foreseeable future to keep that particular power very much under strict supervision. And I think that to try to stem this development, to try to kind of get in the way of that and say, okay, this has to be built in another manner, or this has to be built slower or whatever, I think that goes against the nature of innovation. Innovation is a chaotic process. Sometimes we will reach that end. Sometimes we'll feel that, okay, this is probably something that we should not be playing with. But again, we've been here before, right? When we were able to break the atom

and literally build a planet wiping weapons, we kind of dealt with it. Okay, now we have this power. We have to be responsible and put guardrails around that. So I think that we will ultimately be able to control and we will succeed at making sure that AIs work for us and not the other way around.

All the conversations surrounding the companies that are now well positioned in this space are, as in any other business venture, conversations that have to do with power and earnings and money and status. And I think that this is just human nature. We'll continue to see that, I would say, for centuries to come. This is not going to go anywhere. I think I'm sympathetic to the EI, at least the intent of the EI movement or many of those in the movement. Many include luminaries such as Elon Musk. I think there's two main things that they fail to realize. One is there's a high risk to not moving forward, primarily driven by two different forces. One is we've seen with these

two wars going on in Israel and now also in Ukraine, we've seen how fragile our world is and how staying single on a single planet is highly problematic and in an infinite amount of time will lead to extinction. The question is just when, not if. So the risk of not moving forward is also very great. And I would actually argue So the risk of not moving forward is also very great. And I would actually argue that the risk of not moving forward is finite. The risk of moving forward is unknown. The second aspect, and perhaps a much more practical aspect, is we've also seen, we sometimes project our democratic ideals on other countries.

And we see countries like China, like North Korea, like Iran, that have completely different ways of operating and different sets of morals and ethics. And I would argue that the AI Pandora is already out of the box. And it's in the United States and the Western world's imperative and moral imperative to make sure that we are first to that goal. So moving on to a lighter topic, let's talk about, I know you have a very unique portfolio construction specifically because you take such deep tech and such power law, true bets. A lot of people talk about power laws, but end up investing all in SaaS, but you have entire portfolio of deep tech companies. How do you put together a portfolio like that?

So ultimately we will look from a top down perspective. We'll try to make sure that we are covering the right sectors, right? We don't want to be a sector fund. We don't want to be too concentrated in one specific sector. These are funds that will go on for a decade, maybe a little more. So we first start with making sure that we have coverage on the sectors that we like and that we feel are going to be particularly profitable for the next decade or so. Secondly, we will try to make sure that we completely dodge the adverse selection effect by making sure that we are investing in funds and in GPs that are attracting the best possible

entrepreneurs. So this right there is a huge, huge advantage because instead of us looking at the very top of the funnel, we are already looking at the world once it has been filtered by some of the best GPs out there. Third, we will typically concentrate our investments in early stage GPs so that these GPs are coming to write probably the first, maybe the second checks for those companies, meaning that there's still a ton of upside. And finally, we try to make sure that we will use our experience, leverage our experience by doing the right due diligence

in those managers and then subsequently in some of the entrepreneurs to make sure that we really have a very accurate way of kind of placing our bets once we allocate the product. What are the number of funds that you invest in per fund? And what is the underlying allocation of companies? The typical number of GPs that you have per fund is something like 11 or 12. Maybe a little less in fund one, maybe a little more in fund three, but around 11 or 12. Ultimately, these managers, they have different styles as we would like them to have. But I think it's reasonable to assume that each one of them is going to invest in anywhere between 15 to 25 companies. So let's call it 20 companies.

So that part of a portfolio of direct investments that works almost as another VC fund in our mix. So we typically will do 15 to 25 investments, direct investments as well. And normally those investments come and to a later stage in the life of the companies, we will typically do a series A, maybe an early B, but ultimately we try to be very flexible and we try to make sure that the odds of the companies, we will typically do a series A, maybe an early B, but ultimately we try to be very flexible and we try to make sure that the odds of us getting the companies right are higher because we have this kind of front row seat to watch what the company has been building since day zero.

And Guy, you have 250 companies, you essentially have another 15 to 20, I call it the 12th or the 13th manager. So you have 265 to 270 companies. Why is it that LPs still want over diversification within each single portfolio? Why aren't you just saying play offense, offense, offense? So, so that's a great question. So our view and all the simulations or the tests, all the analysis that you did before we started with this model pointed to a world where if you tried to play offense, you would

get it right every now and then, but you would also be really aferred every now and then. And ultimately you'd have maybe mediocre returns with a ton of volatility. So one year you'll be feeling like, you know, the king of the world, the other year you're going to say, okay, I don't know anything about investment. Ultimately, what we have built is a machine that hopefully will produce consistent returns, high quality risk return relationships every single vintage. So if you look at the portfolio, because we have 200 plus companies, chances are we're never, ever going to be a 10x fund. And that's okay because by design, we don't want to be a 10x fund. What we don't want to be is a zero or 0.5X fund. We want to be every single vintage between a 2.5 and a 5X net fund.

Parable vintages maybe will just double or a little more than double our client RLP's investments. In great vintages, we're probably quadruple, quintuple their investments, net of all fees. And that's exactly where we want to be. We want to make sure that when investors come to our strategy and invest in our model, they understand they're not swimming for the fences. They're not going to get the 10X or the 20X returns that a lot of GPs out there try to deliver. But at the same time, they have a very, very clear downside protection because of the way we build our diversification and because the way we think that we have

access to some of the best deal flow in deep tech out there. Speaking of the best deal flow in deep tech, you have 35 to 40% concentration in co-invest. That's a incredibly high co-invest concentration. How do you avoid adverse selection in your co-invest? So ultimately we don't lead. Ultimately, I don't think that I can see something in a company that no one else can see.

And if you look at our portfolio, our direct portfolio, which is, you know, posted in our website, all of these companies, they have a fantastic syndicate around them. So we have the benefit of getting to know these companies, either through existing GPs in our portfolio or by friendly GPs that we have good relationships with. And we also try, once we build that portfolio, not to overweight any specific company. If you look at the range of checks we're writing to these companies, we'll write checks anywhere from $350,000 up to $3 million when we have really

high conviction and we double down on a specific company. But this strategy has a ton of guardrails around it, right? We have limits when it comes to the funds we're investing in, the companies we're investing in, the sectors we're investing in. So even when things don't go really, really well, we do have, again, limited downside. And of course, I can argue, but people in venture shouldn't be concerned with the left side of the distribution of returns, right? People in venture are looking at the upside, are looking at the right side of the distribution of returns, right? People at venture are looking at the upside. They're looking at the right side of the distribution of returns. And in my experience in managing other people's money, which is an incredible responsibility, is that that is really not the case. That people are,

actually, they are okay with losing money, but they're really, really frustrated with surprises. And venture is such a hard asset class to predict. So surprises are almost inevitable. So what we have built is a strategy where negative surprises, they're probably very well controlled and restricted up to a certain point. And your upside with the addition of one third or maybe a little more of one third of the portfolio into direct investments. It's almost like I'm giving you some optionality. But guess what? The optionality I'm bringing to you is curated and is leveraged by our network and our partnership with many of the best GPs in the world. So we feel it's a great way to leverage those connections and at the same time to produce a great risk-adjusted return for investor base. You mentioned GP relationships

and how important that is as part of your strategy. What is the gold standard? What is your ideal GP, both from what you look for, but also from the relationship? If you could tackle, it's a two-sided question. First, so I think ideal GPs, they are incredibly transparent, not only in quarterly reports and annual meetings,

but also when between quarters stuff happens, right? When a company is in trouble or when a company is doing particularly great. So they're also, at least the GPs we look for, they're always very happy and very eager to share deal flow once the time is right, okay? Because we are not interested in hindering our GPs' ability to build their own successful portfolios. What we want to make sure is that they understand that they can count on us for subsequent rounds as a good parker, as someone who does not particularly is interested in board seats, not interested in veto powers, not interested in kind of overseeing the company. We just want to

make sure that our money is tagging along high quality money from high quality investors who have been at this for a number of years. So ultimately, if you combine those two features, full transparency and the ability to share deal flow, the ability to ultimately enable us to participate in some of the subsequent rounds, we will probably have a great interest in talking to and getting to know these GPs. What has happened over the years, because we've been doing this for a number of years now, is that this has become such a virtuous cycle because we have, of course, established great relationships with a number of GPs out there.

We have fantastic relationships with Lux Capital, with Section 32, with E14, with Ubiquity Ventures. These are just some of the names that we have been working with for a number of years now. And this partnership has been very, I think, fortuitous for both sides because I have in them early stage investors that are able to really attract fantastic entrepreneurs. And I think they have it as not only someone who is able to try to cross-pollinate some of the companies into other GPs out there, helping to spread the good word that there is a particular company that will be of interest to specific GPs, but also someone who is always interested in looking at specific companies and participating in subsequent rounds. How would you like GPs to interact with you?

Do you want them to be calling you every day? Do you want them to send you an email once a quarter? What is your ideal cadence? So I am absolutely fine if the, even though this never happens, because I will initiate contact every so often. I have a little control mechanism where if I go more than a month without hearing from a specific GP, I'll gently nudge him or her. And more often than not, yeah, I haven't talked to you in a month

because there's nothing relevant to talk to about in a month. And we'll switch off those controls during holidays and summertime. So that's okay. We don't call people in the middle of July asking, hey, I haven't heard from you since mid-June. What's going on? But I think that the ideal communication cadence is between those two extremes, right? I don't want to talk to them every single day, even though they're lovely people. All of you, love you guys. But I don't need to talk to you every single day.

And I'm sure you don't need to talk to me every single day. And I don't want to hear from you only once there's a quarter letter that pretty much every other investor is receiving. We don't want special treatment. But we belong to that 10% to 15% sliver of LPs who are interested in also co-investing. And this number, I'm not sure anyone has made any sort of formal research about that. According to statistics, 100% of LPs love co-invest.

That's right. And 10 to 15% of that do that. Do Co-Invest, yeah. That's at least been my experience, you know, consistent experience through multiple asset classes, geographies, and so on and so forth. So if you get to a point in the relationship, like, you know, we have been lucky enough to achieve

where you have, you know, your GPs in your messaging app, your favorite messaging app. If you have your GPs ultimately communicating with you, not only in the companies that you're sharing a direct investment in, but also in the overall portfolio, that's pretty much one of those intangible things

that you want to kind of add to your due diligence analysis to make sure that you've got the right partnership, you've got the right people working with you. Let's talk about the two-way relationships. Part of what makes a two-way relationship is that you're there for good times and for bad times. Let's say a company, let's say in theory, you had this whole open AI debacle and it was changing every hour and a GP came to you for guidance on the situation. How do you build trust with the GPs so that they could communicate not only the good news, but the bad news to you as well? I think that ultimately educated investors are the best types of investors,

right? And when you come into an assets class like venture, where there's such a bias towards assuming that only good news will happen, right? That your little startup will become the next Amazon or the next Alphabet or the next Microsoft. I think that as early as possible in the relationship, you want to make sure that they understand that you are actually looking for that type of fun because they don't exist. What you want to build is a relationship where they understand that you're coming from a place of trust, where you want to make sure that you are getting their best skillset on display, and that sometimes things don't go as planned. And it feels like over the last 18 to 24 months that nothing is going as planned because of venture. So once you get that ball going, then it becomes, again, a virtuous cycle because we as investors,

we work very much by example and by experience. And once you experience a particular company that didn't go well, and you share the news, and instead of you getting an LP that is demonizing you and asking you, what the hell? With this, because we really monitor every single company that is coming into our GPU's portfolio, we understand where they were coming from, why they made investment, why they wrote the check. Even though sometimes we don't agree with coming from, why they made investment, why they wrote the check. Even though sometimes we don't agree with the reasoning, and that's fine. We want multiple brains thinking about our portfolio.

We understand where they're coming from. And again, to just reiterate the point that I mentioned before, investors are okay with losing money. They don't love it, but they understand it's part of the game. However, investors really freak out when there's a but they understand it's part of the game. However, investors really freak out when there's a surprise, when there's something from the left field, something they really didn't see coming, something that is out of style and out of whack. This is what really breaks relationships. And this is something that we will take every single step possible,

leveraging a 20 plus year experience in risk management to avoid, to make sure that the relationships that we build are everlasting. And again, many of the funds that we've been working with have been present in every single one of our vintages. I think that's one of the elusive LP value adds. When you talk to first or second time GPs, they're always talking about economics, co-invest. That's what they think is LP value add. When you look at the third, fourth, fifth time GPs, they're looking for people that are dedicated to the asset class. And that means many different things. That means supporting GPs through difficult times because sometimes the best returns come in difficult times. But it also means being there for multiple vintages and being an absorber. There's this concept in psychology that you

want to be around people that absorb chaos instead of repel it and being an absorber. There's this concept in psychology that you want to be around people that absorb chaos instead of repel it and amplify it back to you. Sometimes you have an issue and you go to somebody and then you end up being the one that's actually trying to calm them down, trying to lead them up through your own issue. So you want LPs that are really absorbing that and being good thought partners. I think if somebody was to ask me, what is LP value add, that would be my number one definition of that. I think you're spot on. I think that at the end of the day, it's us looking for a specific service and skill set that they will provide us. But at the same time, if you want to build a robust firm, a robust partnership, you want to make sure that your LPs

who are limited partners are actually partners, are people that ultimately are supporting you, that understand what you're doing, and that ultimately are supporting you, that understand what you're doing, and that are there for you in good times and bad times. And again, the fact of the matter is, ultimately, when you build this type of relationship, it can withstand a lot. And we do the exact same thing with our own LP base. We have LPs, and we want to make sure that those LPs, most of the LPs we have by a very, very far margin, have been with us since our first fund. They understand what we deliver.

We're very deliberate about reporting. We are very transparent. Every single LP knows what's happening in their portfolio. We don't sugarcoat, you know, what's happening with the environment. We ultimately want to make sure that these people understand that we're not going to be able to flip the portfolio in a week or two. This is a decade-long venture. Every single fund has a story that lasts more than an average marriage in the U.S. So you want to make sure that the relationship and the communication is there. The key to good communication is over-communication.

And it is better to err on being overly communicative and overly redundant, as well as employees. So I left the best for last for those that are still on the podcast. We can't go an entire episode without talking about alpha in emerging managers and alpha in managers. What are the one or two characteristics

of top GPs that you look for? So the world of venture, that's a fantastic question. I love this question so much. The world of venture is probably the one that has the most impactful halo effect. So the halo effect is the effect that investors have that a specific manager or specific group has a halo around them that will enable them to consistently deliver great returns. And the reason why venture has such a persistent halo effect is because founders will look for successful GPs in their respective fields

in order to start shopping their particular startup. And I think that the secret around becoming a strong GP or something that we'll look for in an emerging GP or in a well-established GP is the following. Why would a phenomenal entrepreneur pitch to you? There's no shortage of GPs out there. There are many well-capitalized groups with money to invest, interested in investing in innovation. So what does make you of all those GPs, of all those groups special? So if you as a GP are able to get, to provide a good, sensible

answer to your LPs as to this is why fantastic entrepreneurs will want to talk to us, will want to pitch us, then you have something. And I've seen it before. And I believe that every single one of the GPs, we've come into the portfolio, they have to have a very, very good answer to this specific question. Because guess what? Venture is not a game where GPs are cherry picking entrepreneurs. The best entrepreneurs are cherry picking the best GPs. And if you're able to understand that and to dedicate part of your time to really harnessing the power that those specific GPs have to attract the best entrepreneurs, then I think you have a great shot at choosing the right GPs, the right partners for you and your business.

I want to highlight something that you said that's very important. The top GPs are not the ones that most entrepreneurs want to back their companies. It's the ones that the top 1% of entrepreneurs want to back their companies. It's the ones that the top 1% of entrepreneurs want to back their companies. My favorite tweet is VC is 99% saying no and 1% begging. And that really summarizes, somebody could post who that tweet is. I don't remember who tweeted that, but that summarizes the industry. And a lot of times it's counterintuitive in terms of who the top entrepreneurs want. Jason Lemkin had a tweet about this and he said that very few entrepreneurs actually want constructive feedback. And I said, what percent? And he said, he commented back something to the kin of less than 20%, but

almost all the unicorn founders. I think that really summarizes is you want GPs. Typically, the top entrepreneurs do not necessarily want the most likable GPs. They don't want the most agreeable GPs. They want the smartest GPs. They'll tell them the hard truths and maybe they're also likable. And I think that's what differentiates what top entrepreneurs want from the top GPs.

So speaking of likability, you are a multi-talented, both deep hard tech and also highly likable. And I've really enjoyed the conversation. I highly recommend your book, Present Future. It really takes a deep look into deep tech. But you spent an hour in the hot seat. What would you like our listeners to know about UD and about grids and anything else

you'd like to share? First and foremost, thank you very much. Thanks for an invitation. Very happy to be here. Hot seat feels really good when you're in the driver's seat. So it's all good. I do believe that by watching many of the episodes of your podcast, I would say that ultimately this is a journey where there are no definite answers. Investing is both art and science. So we have to have some basic principles and you have to try to stay very, very loyal, very faithful to those

principles. And then you have to have that degree of flexibility and adaptability, specifically in the venture world and even more in the deep tech world. So if you are able to adapt to the times to make sure that those core principles are immutable, but that you have a layer of adaptability and flexibility, I think you should be fine. So thank you so much for an invitation. And I hope that we can do this again soon. Thank you, Guy. I look forward to meeting in person. Thank you for taking the time and thank you for jumping on the podcast. My pleasure. By popular demand, the 10X Capital Podcast has officially launched our newsletter powered by Carrier Labs, a full service content marketing firm that's partnering with us on the newsletter.

In our weekly newsletter, we will keep you updated on all things emerging managers and limited partners, including industry trends that are critical to know as an LP, VC, or founder. To subscribe to our totally free newsletter, please visit 10xCapitalPodcast.com. Again, that's 10xCapitalPodcast.com. We thank you for your support.