Investing Billions - E305: Why 95% of AI Startups Will Never Build a Moat

Episode Date: February 16, 2026

Why are vertical AI applications emerging as some of the most defensible opportunities in technology today? David Weisburd speaks with Nick Beim about why context—not raw intelligence—is becoming the key driver of AI performance, and how vertical software is reshaping wealth management, legal services, and defense. Nick shares how legacy infrastructure, industry economics, and human-centered workflows create enduring opportunities for AI-driven transformation.

So, Nick, you've been investing across your career in AI, FinTech, Defense, Wealth Management. Tell me about what you're most excited about today. I'm most excited about vertical AI applications. I think the first inning of AI innovation, we've seen broad horizontal platforms, the big LLM labs, achieve extraordinary things. And they're starting to shift their focus from just providing an LLM to getting into horizontal applications. I think some of the most interesting investments are going to be in verticals.

AI applications. And the reason I think vertical is so interesting is twofold. One is more defensible. It's very difficult for those horizontal platforms to get access to all the workflow and data in a vertical application. And many of the vertical application incumbents and major customers are very reluctant to give their data to these AI labs. But the second of maybe the more interesting reason is when you look what drives AI performance, it's kind of context. So general intelligence is interestingly getting commoditized. But when you apply that intelligence to a particular vertical where you've got really rich idiosyncratic context, the performance can go through the roof.

I sometimes get upset with my LMs because I ask the LLM a question gives me an answer two months later. I realized that it was the wrong context or I didn't ask the right question. There's a counter thesis to what you're saying, which is that the horizontal LLN, you LMs will disrupt the vertical application of AI. Does it really come down to the proprietary information? Is there more to it? Why won't the large LM players disrupt the vertical AI players? It's a few things.

I think first, they've got a lot to do. They got a lot of their plate already in this sort of commoditization struggle. They're all investing a lot to try to get incremental improvements in their core models better. And they can't devote all their attention to trying to win every application category. they can. They'll go after a few of them. They'll go after the biggest ones. I think it's very similar to what happened with Google and Microsoft as they extended their search and operating system franchises into horizontal productivity apps. Very profitable for both companies. They're both very good at it. And we use those applications today. They didn't do everything. And they tried to do some things and

weren't successful at them. I think it'll be similar for LLMs. They'll nail some horizontal applications. you can see OpenAI experimenting with planning travel for you or helping you with e-commerce. You can see Anthropic experimenting with business agents. And coding, of course, has been a very attractive area for both companies, but they can't do everything. And you've invested in terms of the largest players more in the wealth management tech than really any VC that I know. What makes you so bullish on that sector of the market?

When I look at wealth management more broadly, I think there are two kind of structural problems that lead to a lot of opportunities. One structural problem is the current technology in the industry is terrible. If you were to ask any financial advisor, hey, how much do you like your custodian or these different point solutions? They'd tell you they were very unhappy. So what's happened is financial advisors have to work on legacy custody platforms, primarily Schwab, Fidelity, and Pershing that, you know, were developed 20 years ago.

They use batch processing, very limited APIs, just a, technology you would have expected in the 1990s. On top of that, they have to cobble together all these expensive point solutions, and it means that they spend so much of their time in operations getting their tech working rather than with customers or growing their businesses. So terrible tech in the industry. The second and interestingly related structural problem is how profitable wealth management is. So I think, as you know, small RIAs have profit margins in the sort of 30 to 35 percent range. large RAs have profit margins as high as 45 to 50, maybe even a little bit above 50%. It's an incredibly profitable industry given the nature of pricing.

Someone somewhere historically said 1%. That's what's going to be the cost for me to manage your money, and it's stuck. It's sort of like 2 and 20 in the fund industry. So it's an immensely profitable industry. Because it's so profitable, there's not an incentive to innovate or adopt new technologies to survive. If you compare it with e-commerce, which is a Darwinian fight to the death every quarter, the companies have to adopt new technologies to succeed and survive.

So with all that as background, when you provide a really high value solution in wealth management, your competition, the legacy players are generally, the competition is really poor, and the economics tend to be really good. So those are the things that got me very excited about wealth management. But one last point I would highlight, because I do think this is the thing that Silicon Valley missed. The advisors are absolutely central to wealth management. Silicon Valley keeps waiting. If you were to poll people in Silicon Valley today, 98% would say, well, of course the humans are going to be automated out. And the humans are the product. People, for the most part, there's a

robo segment. There'll be a digital advisor segment with AI, and those will grow more over time. But consumers really want a person who understands them, who they trust, who empathizes with them and they develop a real relationship with that person that they value. They rarely switch advisors. And that is the centerpiece of the advisory industry. And that was very hard for Silicon Valley to rock. And that actually interestingly dovetails with our previous discussion on vertical versus horizontal AI. The advisor actually has the context on the person. So a lot of financial decisions are not only right or wrong. They're contextual to the person. On top of that, it requires a high degree of context and understanding, and they're very high stakes.

If you sell your home and you get a tax bill in the wrong year, that could mean hundreds of thousands, if not millions of dollars of a mistake versus a chat TPD might give you the right answer, quote unquote, but it's the wrong answer for your specific context. One of the hardest things of investing is seeing what's shifting before everyone else does. For decades, only the largest hedge funds could afford extensive channel research programs to spot inflection points before earnings and to stay ahead of consensus. Meanwhile, smaller funds have been forced to cobble together ad hoc channel intelligence or rely on stale reports from sell-side shops. But channel checks are no longer a luxury. They're becoming table stakes for the industry. The challenges has always been

scale, speed, and consistency. That's where AlphaSense comes in. AlphaSense is redefining channel research instead of static point-and-time reports. Alpha-sense channel checks delivers a continuously refreshed view of demand, pricing, and competitive dynamics powered by interviews with real operators, suppliers, distributors, and channel partners across the value chain. Thousands of consistent channel conversations every month deliver clean, comparable signals, helping investors spot inflection points weeks before they show up in earnings or consensus estimates. The best part, these proprietary channel checks integrate directly into AlphaSense's research platform trusted by 75% of the world's top hedge funds with access to over 500 million premium sources.

from company filings and brokerage research to news, trade journals, and more than 240,000 expert call transcripts. That context turns raw signal into conviction. The first to see wins, the rest follow. Check it out for yourself at alpha-sense.com slash how I invest. Absolutely. The context is critical, and so often it comes out of the dialogues and relationship that people have with an advisor.

One of the biggest trends in alternatives, if not the biggest trend, is the rise of retail expected almost as large as an entire institutional market. I've had the CEO of Icapa, Lawrence Calcana. I've had the CEO of Hamilton Lane talk about these. Is there a world where these wealth tech platforms allow the RIAs to access smaller funds, not just the Blackstone Apollo TPGs, but really the smaller funds in the market? And if so, how do you marry wealth tech with the rise of alternatives in retail? It's coming very fast. That possibility will absolutely come to pass. And it's interesting. I know the people driving sort of the Alts Revolution well. I used to work with Lawrence Calcano at Goldman Sachs a long time ago.

This is something that customers want and customers demand and that increasingly funds are able to provide. So I think we'll see a lot more of that. I do think, though, that just because I come from this world, as we're saying, the most attractive funds don't want to have retail, like small, I'm thinking of venture funds in particular, really don't want to have retail investors. It just adds a lot of regulatory oversight and hassle. We've got a great business working with a limited number of really sophisticated institutional clients. We're not playing an asset accumulation game. We're playing a performance game. So I don't think it applies across the board, but to clients that are looking for more assets that are willing to take on those responsibilities,

a lot more is coming. Is there more tooling coming down the path? In addition to platforms like I Capital, what would be your advice for GP that is looking to raise from retail? There are more tools coming. I think it's interesting. I don't think tools alone will be able to solve the problem for funds. I think intermediaries like I Capital are going to be very important to help them, to help consumers invest in these areas and help funds get on these platforms.

One of the other large trends in asset management, specifically on the taxable side is tax-aware strategies. And you see a lot of wealth tech going after that space in many different ways. What's the future of tax-aware investing look like for the retail channel and for the non-institutional investor? I think tax-aware strategies are going to have a huge renaissance and go way beyond what we see today by harnessing AI. So I think we're going to see a world where RAs get much more sophisticated on tax planning

and just financial advisors everywhere get much more sophisticated on tax planning. AI will provide very powerful new tools. But I think also you're going to see different kinds of financial products that are built around the concept of personalization to maximize after tax returns. And the building blocks will not be traditional funds. The building blocks will be individual securities that AI uses to perhaps create synthetic funds or other tools that help individuals get the best asset location, the best sort of after-tax optimization. So I think we're early days in a really interesting AI revolution to come.

And these are not your grandfather's tax tax loss harvesting. This is not the 1% per year that Goldman JPMorgan would promise you to bring in your business. Some of these strategies are cultivating 100% capital loss on year one. So you sell your company for $20 million. You invest it. You hold it for one year, you wipe out the capital gains. And the problem with those is that some of those minimums are $5 million. So they're very restrictive for most people, but for people that might be startup employees, GPs, maybe not the founding GP, but somebody that has Kerry, you know, do you see that as the next, as the next generation, like lower minimums and AI-assisted ways for other people to reap the benefits of tax-aware investing? Yeah, no question. It's coming. And

I think AI is going to enable the discovery and execution of new tax-aware strategies that go beyond the capabilities of current technology. David Cabellers, a family office, the team that did that, they're doing this around real estate. I've had crypto, actually, crypto tax-aware strategies pitched to me, which makes so much more sense because there's more of all. You don't even need to leverage, you don't need to put crypto investing in there's enough fall there to harvest quite a bit. So it's a fascinating part of the market.

I think this is one of the hottest things that, again, the individuals with 50 million plus net worth are all talking about it, but a lot of a lot of the smaller wealth and smaller RAs are not able to access it because purely just because of minimums. The sophistication is not that hard, actually. Some of these tax-aware strategies, they are even easier than investing into alternatives. They give you a 1099. It's not even a K-1. Yeah. You're also very bullish on legal tech. Obviously, there's been some first generation wins with startups like Harvey.

Why is there still much more to do in legal tech and the integration of AI and legal? I'm very bullish on legal tech. The primary reason is that of all business verticals law is the one that's driven most by language and knowledge. And those are exactly the areas that generative AI is best at. So I think if you were to ask a lawyer how impressed they are with what AI can do, they're incredibly impressed. They're probably scared that it may, you know, affect their future employment prospects.

What Harvey's done is interesting. It starts with a very simple product that's useful that, you know, is productivity, basic research, automating some basic workflows. But an interesting thing about law is that it's so multifaceted. There's so many different areas of law. And some of them like litigation, for example, are very complex. So in addition to companies like Harvey that have a relatively simple product,

you've got far more complex products like Sillow, which is really, to AI litigation leader that help you automate a lot of parts of the traditional legal workflow like document review, do traditional e-discovery, but do it better with agentic AI, and then help you think through the major litigation tasks that need to be done with far more efficiency than could otherwise be done. And so I think in legal tech, there'll be a litigation winner, there'll be a general purpose tool winner, there'll be specific winners in other areas where expertise is required, international

tax law is a vastly profitable part of the legal world. And I don't think the existing players are focused on that today. But that requires a lot of financial knowledge as well. So many parts of legal yet to be enhanced with AI and lots of opportunity. I think it's good to have some skepticism as a lawyer looking at legal tech. But the reality is that the majority of legal opportunity is not pursued because the cost of discovery and the cost of even figuring out whether you should do something is relatively high. It might cost $25,000 to figure out whether you have a $200,000 suit. And although it sounds rational to do that, 90% of the people won't do that. They have that downside risk aversion that keeps them from pursuing. So actually, legal tech, in my opinion,

is going to significantly increase the number of legal opportunity because there's much more things that are not being pursued. I think you're right. And I think EI is going to help in other areas like arbitration, where you can get very quick responses, quick settlements, and just make the overall legal system much more efficient. When I found out you were on the Council of Foreign Relations on the board of directors, I was very excited. One of the most famous think tanks in Washington, specifically dealing with foreign policy, which is chaired by David Rubinstein, co-founder of Carlisle.

You have a very unique vantage point on that. board, what do you see as the future of defense and the future of national security for the United States? These are areas I've spent a lot of time thinking about, and it's interesting. These areas have brought together both my work with the council and other think tanks on defense, intelligence, and foreign policy generally, but also my work in the venture capital world where I've invested in a variety of companies that serve those customers and struggle through all of the ridiculous hoops that, you know, are put in their way. It's very difficult to work with the government, but that the government really wants because the character of warfare, the character

of intelligence competition, and the character of geopolitical competition generally is being radically changed by technology. And the council has been a great place to really get to talk to a lot of the leading actors and thinkers in those worlds in an off-the-record context where they can just be very honest about, hey, these are the challenges we're having. These are areas where we'd love to see the private sector help us. And when I look at what we are witnessing now, I think we're witnessing a very rapid shift in the character of warfare. And I think interestingly, Ukraine has become the Silicon Valley of the future of warfare. They've gotten so good at innovating and constantly iterating on what works on the battlefield. And I think, however the Ukraine war ends, is like

it will end with the Ukrainian army still probably the most significant land army in Europe, the most experienced in how war is changing. So what's changing is a couple of things. One is hardware is becoming commoditized and attritable for the most part. There will remain some exquisite, very powerful hardware systems, weapons systems, aircraft, and so on. But there's going to be a huge amount of mass production of land, sea, and air drones that are able to do a lot of the work that humans used to do, so you can deploy them without the human risk, and there are going to be specific defenses that are arrayed against them. And when you think about where the intelligence for those is, it's really in software and AI. So that's one change, sort of autonomous systems,

attritable systems at the edge. Another change is the ability of AI to ingest all of the sensor data from the battlefield, from, you know, potential battlefields, and understand what the most intelligent operational decisions are. So it's been very difficult to get all that information historically in the first place. To get it all together into AI and be able to sort of query it and have it be a sort of partner in decision making for operational decisions is incredibly powerful. In the Cold War, when the Cold War started to get, it started to really heat up. So with the Korean War in particular, and with Sputnik, we put a huge national effort into innovations. We created DARPA. We created STEM education in the United States. We made all sorts of changes to try to avoid

that sort of technological surprise in the future. But as the Cold War, you know, war on and when the Cold War ended, we sort of sat on our haunches a little bit and we weren't as aggressive in adopting new technologies as we should have. And the result is now China is trying to develop a more capable military primarily by trying to leapfrog us in the area of applying advanced technologies to their military and to their intelligence. And I think we now have a lot of urgency in this area, but we've got a lot of work to do. Ukraine is really the testbed for this asymmetric warfare,

which means you have these $500 drones that are destroying $5, $10 million tanks. So you have almost this last generation of technology battling out, the next generation of technology. What is the United States doing in order to evolve their defense, stack for next generation warfare? It's interesting. So on counter drones specifically, there are a lot of approaches that are being experimented

with, both sort of in the lab, so to speak, and on the ground in Ukraine, like working with Ukraine. But I think generally, there is a part of the military revolution that we are not currently well suited to execute on. And that's low-cost hardware. You know, if you look at the margin structure and the business model of traditional defense primes, it's cost plus. They charge a very large amount for their hardware systems and they bundle services with

these systems, whether it's an aircraft, a radar system, whatever it is, a ship. But the action going forward is going to be in a lot of these low-cost systems, and they don't see enough margin for that to fit their current business models. One might say their business models have to change. I think more likely you're going to get new players like Androll, and there are going to be others that are able to make great businesses around doing that really, really well. And it's interesting, if you look at how much we spend on defense,

I think we could spend, you know, half of that and have it be more effective because so much the money is wasted in these huge, exquisite contracts that have lots and lots of maintenance costs. And, you know, it's interesting. If you look as a subset of that at how software is developed

in the Department of Defense and intelligence agencies, it's often by companies that aren't really software companies. And they throw lots of bodies at the problem. And you get this custom code by people who aren't, you know, the kind of software talent that Silicon Valley runs on. And I don't think our country is best served by that. You mentioned cost plus. Not only is there no incentive to lower the cost,

there's a disincentive because oftentimes this cost is a percentage, not a dollar sum. So it's not like if they lowered the cost by 10 times, they would make the same amount of money, which doesn't really matter. They actually make less money. Absolutely. And if you look at the major systems that have been driven by cost plus,

their cost keeps going up and up and up and up. You know, there's a joke in the military that eventually all military spending, we'll go into one airplane. I don't know if it's the F-94, but, you know, just the cost of aircraft, the F-35, was so incredibly over-budget. And we can't afford to have that type of development drive our spending going forward. We need to be smarter about where we spend money and make sure it has the biggest impact.

If you've been considering futures trading, now might be the time to take a closer look. The futures markets has seen increased activity recently and plus 500 futures offers a straightforward entry point. The platform provides access to major instruments, including the S&P 500, NASDAQ, Bitcoin, natural gas, and other key markets across equity indices, energy, metals, Forex, and crypto. Their interface is designed for accessibility. You can monitor and execute trades from your phone with $100 minimum deposit. Once your account is open, potential trades can be executed in two clicks. For those who prefer to practice first, Plus 500 offers an unlimited demo account with full charting and analytical tools. no risk involved while you familiarize yourself with the platform.

The company has been operating in a trading space for over 20 years. Download the Plus 500 app. Trading and futures involves the risk of loss is not suitable for everyone. Not all applicants will qualify. How are the new defense tech companies like Anderl able to compete with these entrenched defense companies? They've done something very intelligent, which is not try to compete with existing primes on their core territory, but carve out some new territory, in particular autonomous systems, and get really, really good at that. And autonomous systems are such an important area for all parts of the military,

is really one big dimension of where warfare is going, that they've been able to grow rapidly. And I don't think the prime, the traditional primes are going to be very effective in competing with them because it's a low-cost game, and that's not what they do. And I think that's not what they can really afford. And I think the technology, you know, AI development is not currently really what they're good at, whereas Andrewl, I think, has a lot of, you know, highly trained AI engineers that really are good at it. Stepping back, AI is changing on just such a fast pace. We normalized the last week's changes as if it was 10 years ago, but it's just changing

almost on a weekly and monthly basis. Given all this change, how do you come up with principles and methodologies to diligence invest in companies, either both in AI within the AI space, but also those heavily reliant on AI. It's something I think about a lot. And for the kind of investing that I do, early stage venture capital investing, it's very intuitive, it's very people-driven. And the most valuable tools that I have found are really two.

One is finding the smartest people in the world in certain problem areas, technology areas, the application of certain technologies to different business sectors. They're out there. I spend a lot of my time just trying to find who the brightest people are to help figure out what are the big new opportunities in a space. Often they're entrepreneurs who are active in that space and who have a lot of calibrated imagination about what's possible in it. The other thing that's very valuable in venture capital,

You don't always have the chance to experience this. But if you invest in a company that's a real pioneer in an area, it's doing something very disruptive. Usually they're the kind of companies. Data Miner was an example of this. Ultris was an example of this where people sort of scratch their heads and say, really? You think you can do that?

That seems impossible. Like, you know, talk to me in two years and let's see where you are. And if those companies succeed, which both have, both are, you know, multi-billion dollar companies now, they often bring a huge wake of innovation behind them. And they often have, if you are an investor in those companies and working with those management teams, you have really interesting insights into what else is possible in innovation in related areas. And so I think in part because of my investment in Altruist seven years ago, I had a chance to work with Jason Wank, the founder. And he created such a terrific company

that opened up so many other opportunities that it led to a much deeper focus on my part in wealth management because I suddenly saw all these big opportunities. And Jason and myself, Bill McNaft, the former CEO of Vanguard and others, collaborated on finding and making the best investments, also in creating some brand new companies. So all of which is to say, if you are fortunate enough to be in one of those pioneering companies, that gives you disproportionately valuable and often proprietary insight into where other opportunities lie. Has that been one of your keys to success is essentially to focus on a niche, kind of like a business? It might not be the biggest.

Well, tech, let's be honest, it's not as big as AI LMs, but it is a niche. It has specific players, has specific ways of winning. Was that a purposeful strategy or is it just something that you'd made a couple of investments and you're like, okay, I now have two more investments than 99% of the world? I'd like to see it was all prescience that I had this all figured out 15 years ago. but it was very opportunistic based initially on the success of altruists and then the success of other companies like vanilla and moment that I've invested in in wealth management. And I found that in virtue of those investments, I just not only could I see where the opportunities

were and did I have a group of people that were so well attuned to where innovation was possible in the industry, but I also knew all the major customers. I got to know, you know, so many of the leaders of large RIAs of the wirehouses and and custodians, that it became very straightforward to help create new companies to go after new opportunities. Do you have to avoid the temptation to enter these new hot sectors when you have a niche that's great, great opportunity? But sometimes you have these temptations that come about that seem very interesting.

I find it's often very helpful to yield to that sort of temptation because the world is changing so fast, I think if you've really built a franchise, an investment franchise in an area, it will always yield fruit, but maybe you've gotten the most attractive fruit early on. And AI has increased the pace of change so much that vast new things may be possible in areas that you previously had written off as not being sufficiently exciting to invest in, or maybe you missed some of the early investments, but you'll see very big new ideas. It's in venture capital, the moment you stop, exploring fascinating new ideas that could be highly disruptive and are content with what you're doing,

you're done. The world just moves too fast. You've had a story career, McKinsey, Goldman Sachs, Matrix Partners, you've been a VC for almost 26 years coming up. I don't want to age you. But what is one piece of advice you would have given a younger Nick when you just started at McKinsey that would have either helped accelerate the rest of your career or helped you avoid costly mistakes? The biggest piece of advice would to be, would be to be more cautious about pattern recognition. Pattern recognition is incredibly valuable to venture investors and sort of sorting all the opportunities that you see and to very quickly make a judgment on whether something might be a good investment.

But it fails in one critical case, the most important case of all, which is very big new disruptive investments. They don't fit a pattern. And when you see them, they look different. They sparkle with greatness, but they look kind of weird. And there are 50 reasons to turn them down according to traditional pattern matching. And this is true for if you think back at Apple, if you look at Open AI, if you look, you know, it was a nonprofit. You know, why would you invest in that? A lot of the most disruptive companies, you have to throw out pattern recognition, shift from fast thinking to slow thinking, and go to ground fundamentals and really use your match.

based on those fundamentals to think what's possible. And right now, I spend all of my time looking for really big opportunities. I'm not satisfied with things that could be a double or a triple. I'm satisfied to take my time, take really a significant risk, but really calibrated, thoughtful risk in areas where I think I have an advantage to go after something huge. Because in our business, all that matters is the big wins. everything else is really a rounding error to those. Do you feel that more 25 and a half years into your,

25 years into your venture career? Do you feel that more like you've internalized this power law? I think I have, and I think one of the reasons is that I got lucky, particularly for all of us in the last five, six years, we lived in the age of this AI explosion. So there are more of these huge companies that are being built in their home runs, Power law is one of those things that it's this unlearnable lesson that until you experience it

it yourself, it's like, yeah, yeah, power law, great, great. I'm going to focus on two, three, X and yeah, I'm going to get my power law. But it's so powerful that it's hard to actually internalize until you've experienced it. And here's the challenge in venture. When you see something like that, something that sparkles with promise, has all sorts of challenges with it, lots of reasons to turn it down, but there's been nothing like it before. And you introduce it to your partners. Some of them are going to say, wow, this looks interesting. But often for the most disruptive ones, the bulk of the partners might say, hey, it looks cool. I don't see this, though.

Or, you know, gosh, you're, we think you're probably too excited about this one. And in those moments, and Venrock is terrific because we have a decision-making structure that allows partners to go forward with those investments, even if all the other partners disagree with them. For us, it's not about banging the table. It's about being incredibly thoughtful about what, you know, you have to have a really thoughtful reason, set of reasons for wanting to make an investment. But the biggest wins of all tend to have the signature of zero or one other, you know, one other person in the partnership

thinks this could change the world. And everybody else thinks, yeah, this is kind of nuts to us, but, you know. How would you explain that? Because they're so different. They don't fit traditional pattern recognition. And to appreciate them, you have to really spend a lot of time understanding how they grow, where their competitive advantages, what's distinctive about them, how they, you know, where their defensibility is. It's idiosyncratic. You don't actually know until you're deep, deepen them. And it's so driven by the people, like the person typically or the people that are founders have to understand what they're doing in such depth, understand the problem, better than anybody else has thought about it. And if you see all that, those are often the best

kind of investments to make. But when you make them, it takes a lot of courage of your convictions to say, I very much appreciate that people disagree with me. I think this could be huge. I'm obviously going to be judged on my performance. I love venture firms that allow people to do that. Venrock has that kind of structure. And those have been some of our biggest wins. To play devil's advocate, obviously these startups, you know, Facebook, Google, SpaceX,

these are just completely idiosyncratic, completely non-linear companies. But there must be pattern matching whenever. comes to the founders. Is that also completely different for each generation? Or is the founder archetype and something in the founders subject to pattern matching over your career? It's very much subject to pattern matching. And on top of the founder archetypes, there are deep relationship networks that we find lots of insight in that might tell us this founder is extraordinary. I love calls where someone says, Nick, this is one of the most extraordinary people I've ever met, you're going to think he's kind of weird. You're going to think he might not

understand all these things. Hear him out. He is, I will invest in whatever he does. And he's going to change the world. I don't know quite know how. And he's going to make a bunch of mistakes along the way. But he needs a great partner. And please take the time to talk to. I will drop everything I have going on if a really calibrated person introduces me in that way. And yeah, founders come in a lot the shapes and sizes, but the good ones tend to cluster around, you know, five or six different artists. A lot of the top investors I know have told me, both private and publicly, that they will invest in a top founder with what they consider to be the wrong business and the wrong business model. Do you subscribe to that? I completely agree with that. Why does that work? Play that out.

Well, the best founders change their business model, change their business focus, but companies that are committed to a specific business model or business focus don't suddenly, you know, increase the caliber of the people at the team. For us, we do a lot of what are called incubations where we really help start a company in our offices. And it's interesting, a lot of those exercises begin with, this is an incredible person that we would love to build a company with. Let's go find, you know, there are three or four areas that we've talked to this person

about and they'd like to work in. We'd like to really go deep with them and come up with a really great idea. Some of our biggest wins. In fact, many of our biggest wins have that structure. And it all starts with a person. There's a wealth tech company, two wealth tech companies that I have that will be coming out of stealth mode in the next several months that both have that background, where we started with the person.

And then it was a great idea, but the idea changed a lot. But the person is what makes it magic. There's still what makes somebody so special that Venrock wants to put resources behind him or her, maybe not even with an idea. Several things. One is just incredible intellectual horsepower and incredible drive. And the drive is interesting because you and I know a lot of incredibly driven people who have always stayed on the straight and arrow and don't take a lot of risks.

The drive that we're looking for has a huge quotient of raw willpower to it, someone who can create something out of nothing and just make it happen, a lot of grit and a lot of just sort of, you see a lot of trauma there. I know you're not a therapist or psychologist, but is trauma either a necessary component or an amplifier of founder's success? That's a really interesting question. I can imagine in some cases it is. And in some cases, there are psychological attributes

that aren't trauma per se. They may be related to trauma, but like having a big chip on one shoulder. That can be a huge motivator. So, you know, we tend to love that. That's not a necessary condition. Some people are just incredibly driven. It's who they are.

It's maybe how they were raised. So I think very high intellectual horsepower, our very high commercial instinct. What's going to work? What's going to make money? Not just in the abstract, what's an interesting business model or technology area. I think having leadership capabilities,

they don't have to be great managers per se. You can pair them up with all sorts of people. But people who are going to have an industry follow them, the customers in that industry follow them, the best talent who wants to be a part of something big in the industry, follow them and join their company. Investors follow them. So there's almost a Pied Piper element of someone who, and it's not based on anything false.

It's based on charisma and a very compelling vision. The last thing is someone who really, really understands the nature of the problem they're trying to solve. A lot of companies get started kind of on the fly. We're going to do something in this area. We'll figure it out. But we love people who are scientific about the problem they're trying to solve and have incredibly thoughtful approaches to solving it. And they know the customer.

They know the pain. Often they were the customer or they've previously felt the pain. And so those, I'd say those are four critical elements. And there are others as well, but I'd say those are the core ways. You mentioned this magnetism. I love the Ashton Kutcher role. Ashton Kutcher, a lot of people don't know, is a great early stage investor, Airbnb, and a lot of other great seed investments.

And he has this role that in order for him to invest into a founder, he needs to, for even one split second, think about quitting whatever he's working on and co-work for that person. Not think about them as somebody that could hire great people, but literally he himself has to be like, well, maybe this investing thing isn't for me, I'm going to be his CMO or his co-founder because he's that compelling.

I agree with that. There's one interesting criterion that goes along with that. That's really important to us, kind of a potential corrective to it or corrective to areas where that could go wrong, which is that we really seek to work with people who are truth seekers, who don't drink their own Kool-Aid,

who don't get caught up in their own career, but who always are interested in discovering the truth and are the first ones to bring up, hey, actually, I was wrong about this. And it looks like things are going to be different. And here's how I'm approaching it now. That commitment to truth and transparency is critical success because the rate of learning at a startup is one of the big drivers of success. And you don't learn quickly if you don't admit your mistakes and stop trick in the cool way. I think there's a tacit thing there. I like to say the best sales, like the best plastic surgery is unseen. So if somebody, if you look at someone you're like, whoa, you know, that a lot of plastic surgery, that's obviously really bad.

Or if you say that good plastic surgery, that's also bad. The best one is when you can't tell that that plastic surgery. Same with sales. The people that people think are the best salespeople are maybe a minus B plus salespeople. The best salespeople aren't seen as salespeople. I think charisma is the same thing. It's not these people that go into a conference and give the speech that they think everybody else is going to be hyped by. It's the people that drive other people to go and follow them. And to your point, they might be completely weird. They might be even anti-social. But they believe so much in their vision that, again, you want to follow them. It's almost an involuntary thing that you want to follow them. You're not even making a decision.

It's almost an unconscious decision. Absolutely. Well, Nick, this has been an absolute masterclass. Thanks very much for jumping on. Perfect to be with you. That's it for today's episode of How I Invest. If this conversation gave you new insights or ideas, do me a quick favor. Share with one person in your network who'd find a valuable or leave a short review wherever you listen. This helps more investors discover the show and keeps us bringing you these conversations week after week. Thank you for your continued support.