How I Invest with David Weisburd - E383:Why the Next Fortune 500 Companies Will Be Built on AI

Episode Date: June 4, 2026

What if the biggest investment opportunity of the next decade isn’t AI itself—but the companies building the infrastructure and workflows that allow AI agents to actually do work? In this episode..., I sit down with David Blumberg, Founder and Managing Partner of Blumberg Capital, to discuss why he believes agentic AI is still in the first inning of a multi-decade transformation. David explains how AI agents will reshape productivity across industries, why vertical software companies with proprietary data have a major advantage, and how network effects are evolving through AI-powered data flywheels. We also explore the future of work, the rise of AI-native businesses, and why human relationships remain one of the few enduring advantages in an increasingly automated world.

Transcript
Discussion (0)
Starting point is 00:00:00 David, you're a founder and managing partner of Blumberg Capital, and you're going all in on AI agents. Why is now the right time to do that? Agentic AI is liberating us from the drudgery of mundane work. I'll give you one example. Cut and paste. How many of us do that over and over and over? And it's so mind-numbing and it's not very productive. So the agent, the agentic worker for you, can do a lot of that kind of stuff.
Starting point is 00:00:26 The logging in, the security protocols, the mind-nostic. the money transfer, it goes on and on. And we're just at the first inning of this game. And in the next 10, 20 years, I predict that the work world will be entirely changed. There's essentially two narratives in the market about AI. One is it's going to take everyone's job and everybody will be jobless. And the other one is that there's going to be 10 times more jobs. Where's the ground truth?
Starting point is 00:00:54 You talked about ground truth. That's why I started with agriculture. Most people don't know this. I think it's a fun fact. Remember, 250 years ago, 95% of Americans worked in agriculture or the rural economy. Today, do you know what that percentage is? Less than 1%. It's about that.
Starting point is 00:01:10 I think it's between 1% and 2% and falling. So all those people, quote-unquote, lost their jobs. And yet, we produce far more food, much more nutritious, much safer, with far fewer accidents in the farm world. and that cost of food as a percentage of our worker daily wages is much lower. And we export to the many countries in the world. So we do a lot more with less. Productivity is the name of the game. Some people will lose jobs, but most likely, to say a cliche,
Starting point is 00:01:43 you're more likely to lose a job not to an AI, but to someone else who is using an AI when you're not. Dr. Alex Wisner Gross, previous guest said, if you're not at the table, you're on the menu when it comes to AI. So if you're not integrating AI, you're going to be disrupted by AI. I think about it in two different frameworks. There's David Deutsch's whole concept, the beginning of infinity. In this book, he argues that innovation is infinite. Why? Because every time you innovate and every time you create something new, it can now combine with everything else. Yes. So as you're creating more new paradigms, more new structures,
Starting point is 00:02:20 more companies, they now have to interact in other ways and combine in new novel ways. So the theoretical limit to innovation is infinite. The second one is actually instead of going way into the future, going way into the past from an evolutionary psychology basis. Human beings for millions of years have been wired to be status seeking and to be zero-sum when it comes to status. Therefore, if everybody can now afford a roles, Royce, there will be now something that's 10 times more prestigious than that Rolls-Royce.
Starting point is 00:02:54 People will argue that resources themselves will become infinite. We'll see maybe in 10, 20, 30, 40 years. But in the next five to 10 years, human beings are not so easily satiated in that if they check the box and they get this livable wage, they're suddenly happy. We may see what Elon Musk calls extreme abundance and revolution at the same exact time. I agree, at least in concept that the innovation cycle is potentially infinite. The other one about human beings, I agree that human nature doesn't change very fast. Technology changes fast, human nature doesn't. But I'm not worried about status-seeking people competing for too many rolls orices. I'm worried about the fact that there are, for example, 700 million people on Earth that have zero electricity. There are
Starting point is 00:03:41 four billion people on Earth that have less than four hours a day of electricity at their disposal because it's so unreliable or so costly. We have a lot of room to help the rest of the world move up. I'm very excited and I'm very optimistic about the potential because who wants waste? No one. What the Agentic A.I. Revolution offers us ahead of us in this bright future, this golden dawn to my mind, is less waste, more productivity.
Starting point is 00:04:10 Any good economists will also tell you that the only way wages can rise is if the worker, the employees are more productive. Now, if we give them tools that make them more productive, guess what? That's a wage unlock. People will become much more valuable to their employees if they're doing more work. Give them better tools, give them better machines. They can be paid more. The sewing machine example, when a person sewed everything by hand, X-level productivity, give them a sewing machine, which costs cap-ax capital investment, they're much more productive. They can pay more because they generate more. So there's a lot of post-modernist neo-Marxist ideology that is getting infected in all of this stuff.
Starting point is 00:04:54 I'm much more of an optimist because I think that most people want to do better for themselves and their families, not in an ego-driven way, but just because they want to achieve, they want to do something meaningful, and something that's meaningful and productive serves other people. So let's go from philosophy to day-to-day execution. You're specifically focused on B2B agents, which are agents. that transact within businesses and between businesses. Why are you focused there? This is where huge volumes of waste occur.
Starting point is 00:05:24 Let me give you one example. We just were showing this company at our LP meeting yesterday in New York. This is a company called Overview. They're based in the Bay Area. They're former engineers from Tesla. They were fascinated as manufacturing engineers by the factory floor and the defects, and how to reduce the defects and how to increase the output of the factory line. And they realize that there were cameras on all the factories watching the production and trying to glean knowledge.
Starting point is 00:05:53 But they improve the kind of camera, hardware improvement, semiconductor. We talked about that. And they improved the AI. And they put the AI with the computer vision. And they took the production of this, I won't name the company, but it's a big medical device manufacturer, a hundred billion dollar value company. They make little tiny surgical rings among many other devices, the diameter of which is as thin as the this card, less than a millimeter. Now, when they're producing them, they have to look for the
Starting point is 00:06:21 defects because you can't have a defective surgical ring if someone might die. So they used to be able to produce 10,000 a day because the inspection, the quality control was very demanding and slow and painstaking, and often manual. Move forward with smart, intelligent cameras, they're able to increase the production to something like 166,000 a day, 16 and a half fold increase, and they improve the quality so that the defect detection rate, which was 94%, is now 100%. So 16.5 times better volume and at least 6% fewer defects to a point of perfection. So that's one example and give you so many, so many more in every field we can see. So far, you said, why is B2B so interesting for a gentic?
Starting point is 00:07:11 AI, we cannot yet find an area where agentic AI will not improve the state of play. It's interesting because one of the first real use cases of AI was radiology. Yes. So radiology, AI quickly became better than leading radiologists to tell whether there's cancer within a patient. And paradoxically, the need for radiologists, I think went up something like 10 times because so many people were coming in and using in, the cost was being driven down. It's one of these unexpected second order effects of AI disruption and the bringing down the cost.
Starting point is 00:07:51 There's a law in economics, and it's about energy. The less expensive energy gets, the more the demand is for it. People would think, oh, if you're more productive, then you might need less. But no, if you make it more efficient, people will use more and more of it. I hear a lot about agentic AI. I hear a lot about B2B agentic AI. I hear about OpenClaw and consumer agentic AI. And when I ask people personally one-on-one, what agents they're running,
Starting point is 00:08:21 almost nobody but developers are running agents. How do you reconcile? Expert calls have always been one of the most powerful ways to build conviction. But today, investors are asked to cover more companies, move faster and do it with leaner teams. With AlphaSense AI-led expert calls, their TGIS call service team sources experts, based on your research criteria and lets the AI interviewer get to work. The magic is in the AI interviewer, purpose-built and knowledgeable-based information to conduct high-quality context-stretched conversations on your behalf,
Starting point is 00:08:51 acting as a trusted extension of your team. Then they take it one step further. Your call transcripts flow natively into your Alpha-Sense experience and become querable, searchable, and comparable, so your primary insights plug directly into earnings prep, digital work streams, and pitchbooks with zero tool switching. And with Alpha Sense expert call services, the AI-led expert calls are just one option because we know the importance of a hybrid expert research approach. AI for coverage and efficiency. Humans for complexity and conviction.
Starting point is 00:09:20 It's the institutional edge that scales research without scaling headcount. For hedge funds, that means validating thesis assumptions across dozens of experts before earnings instead of a handful. For private equity, it means faster pre-IOI scans and deeper commercial diligence. For investment banks and asset managers, it means pulling real. operator perspective straight into models and sector positioning without disconnected tools or manual handoffs. All of it lives inside the Alpha Sense platform, trusted by 75% of the world's top hedge funds alongside filings, broker research, news, and more than 240,000 expert call transcripts, turning raw conversations into comparable, auditable insight. Take advantage of AlphaSense AI-led expert
Starting point is 00:10:03 calls now. The first to see wins. The rest follow. Learn more at Alisprud. Alpha-sense.com slash how I invest. First inning. First half of the first inning. Like, they just sang the national anthem. Really early in the whole process. We just saw some statistics that I believe, where it was experimental last year, it's being scaled into production this year.
Starting point is 00:10:27 One of our advisors, Marshall Lux, is on the board of a number of Fortune 500 type companies. And he said, David, the board members are leaning forward. They're demanding it. And it's happening two ways. It's happening from the board down with a mandate. Do this. Bring AI into our operations. We know that our competitors are doing it or they're going to do it.
Starting point is 00:10:45 We have to be competitive. And it's happening from the bottom up. Often it's a precocious engineer or a particularly young person who's just been exposed to it at school. That's happening. We saw a little bit of that in the mobile phone revolution. That was more bottoms up where the top was resisting mobile phones in the office. The corporations were giving them. and blackberries and employees were asking for it.
Starting point is 00:11:09 You know the story. So let me just do a data set for you that I think will help explain how big this market is. It turns out that the average white collar worker, knowledge worker, somebody works in a bank, an insurance company, a lawyer, a consultant, marketing pro, a corporate executive, all that crowd, most of us, people in podcasting world, those folks cost the employer about $170,000 a year. Now, 160,000 of that is wages and benefits. 10,000 is spent on software tools that we use every day, whether it's Microsoft, plus Google, plus Oracle, plus Amazon Web Services.
Starting point is 00:11:46 All of that together is that software industry sells about $1.5, I think, trillion dollars a year, or 1.7, and their market cap is something like $17 trillion. That's just for the software tools. Everyone's been fighting over that for 30 years, the big companies, right? Now, McKinsey says that agentic AI, within a very short period, I think it's within a decade, is likely to disrupt, transform, maybe lose, 57% of those work hours. It'll be transformed from humans doing it, cut and paste, boring stuff, to an agent doing it seamlessly, silently, frictionlessly, 24-7, and very low cost.
Starting point is 00:12:31 So that 57% of that 160,000, that's about 100,000 of spending that's going on wages now that can be transformed into agentic agents. So that will probably compress, just like we saw print media. They used to say a print dollar turned into a digital dime. So there'll be some compression. I don't know the ratio, but I think it's safe to say that the agentic agent software market, when deployed, within, say, 10, 20 years, will be two or three times larger than the existing software industry today. You're saying 20 or 30,000 of that will be charged to the customers, and 70,000 will be productivity gains. Yes, sir. Yes, sir. And there will be whole new categories of jobs created. Prompt engineers. That's a new kind of job.
Starting point is 00:13:23 Every large corporation that I know worth its salt has a chief data officer and a whole team. and they're grabbing data. I remember the chief data officer of Walmart telling me, we will buy every kind of data that you can offer us. They want everything. It's still unclear to me how we go from today where almost no one's using agentic AI on a TAM basis and a future where everything's around an agent.
Starting point is 00:13:49 No one's really giving me the game plan on how that breaks down over the next couple of years. I know you can't see the future, but what are some low-hanging fruits on where companies are going to start incorporating? agentic AI and how is that going to happen? I'm just one little story and I already have six companies that are in this, I'll call it the loop of agentic commerce and the requisite financial infrastructure that goes along with
Starting point is 00:14:12 that. That's a whole new layer that needs to be built. Let me start with truly you. I sit on the board of this company since I've known you pretty much. They're based in, too, came a little bit later, but they're based in Vancouver, Canada, but they're world, they sell worldwide. They sell in around 100 countries. on earth and they can go to many more. They are identity management experts, leaders in the world. Identity management is known by its colloquial name K-Y-C, know your customer. This is important for onboarding, for compliance, banks, Airbnb, Stripe, Square, gambling companies, Coinbase, all these kinds of companies need to have this kind of onboarding. Are you who you say you are?
Starting point is 00:14:53 Then we go to the new era, K-Y-A, know your agent. Remember I gave you a moment ago, where I'm going to interact with you through a third-party bank. We each can have agents one or more operating for us. How do I know that your agent is who it says it is? So this is a whole new level of identity management that needs to be addressed. Truly is in the lead among companies helping build that whole extra layer. Then there have to be a whole other set of data. And I'll give you another example. There's an amazing company called Telen. AI. They are with the hairy audacious goal, the B-Hag, a big hair-adish goal, of one-click audit. Support for today's episode comes from Square, the all-in-one way for business owners to take payments,
Starting point is 00:15:43 book appointments, manage staff, and keep everything running in one place. Whether you're selling lattes, cutting hair, running boutique, or managing a service business, Square helps you run your business without running yourself into the ground. It's actually thinking about this the other day when I stopped by a local cafe here. They use Square and everything just works. Check out is fast, receipts are instant, sometimes I even get loyalty rewards automatically. There's something about businesses that use Square. They just feel more put together.
Starting point is 00:16:10 The experience is smoother for them and it's smoother for me as a customer. Square makes it easy to sell wherever your customers are, in store, online, on your phone, or even at pop-ups, and everything stays synced in real-time. You could track sales, manage inventory, book appointments, and see reports instantly, whether you're in the shop or on the go. And when you make a sale, you don't have to wait days to get paid. Square gives you fast access to your earnings through Square checking. They also have built-in tools like loyalty and marketing.
Starting point is 00:16:37 To your best customers, keep coming back. And right now, you can get up to $200 off Square hardware when you sign up at Square.com slash go slash how I invest. That's SQ-U-A-R-E.com slash go-slash how I invest. With Square, you get all the tools to run your business with none of the contracts, or complexity. Run your business smarter to Square. Get started today. Support for today's episode comes from Square. The all in one way for business owners to take payments, book appointments, manage staff, and keep everything running in one place. Whether you're selling lattes,
Starting point is 00:17:11 cutting hair, running a boutique, or managing a service business, Square helps you run your business without running yourself into the ground. It's actually thinking about this the other day when I stopped by a local cafe here. They use Square and everything just works. Check out is fast, receipts are instant, and sometimes I even get loyalty rewards automatically. There's something about businesses that use Square. They just feel more put together. The experience is smoother for them, and it's smoother for me as a customer. Square makes it easy to sell wherever your customers are,
Starting point is 00:17:38 in store, online, on your phone, or even at pop-ups, and everything stays synced in real time. You could track sales, manage inventory, book appointments, and see reports instantly whether you're in the shop or on the go. And when you make a sale, you don't have to wait days to get paid. Square gives you fast access to your earnings, through Square checking. They also have built-in tools like loyalty and marketing.
Starting point is 00:17:59 To your best customers, keep coming back. And right now, you can get up to $200 off Square hardware when you sign up at Square.com slash go slash how I invest. That's SQU-A-R-E.com slash go slash how I invest. With Square, you get all the tools to run your business with none of the contracts or complexity. Run your business smarter to Square. Get started today.
Starting point is 00:18:23 Support for today's episode comes from Square. the all in one way for business owners to take payments, book appointments, manage staff, and keep everything running in one place. Whether you're selling lattes, cutting hair, running boutique, or managing a service business, Square helps you run your business without running yourself into the ground. It's actually thinking about this the other day when I stopped by a local cafe here. They use Square and everything just works. Check out is fast, receipts are instant, sometimes I even get loyalty rewards automatically. There's something about businesses that use Square. They just feel more put together. The experience is smoother for them and it's smoother for me as a
Starting point is 00:18:58 customer. Square makes it easy to sell wherever your customers are, in store, online, on your phone, or even at pop-ups, and everything stays synced in real time. You could track sales, manage inventory, book appointments, and see reports instantly whether you're in the shop or on the go. And when you make a sale, you don't have to wait days to get paid. Square gives you fast access to your earnings through Square checking. They also have built-in tools like loyalty and marketing to your best customer. customers keep coming back. And right now, you can get up to $200 off Square hardware when you sign up at Square.com slash go slash how I invest. That's SQUA-R-E.com slash go slash how I invest. With Square, you get all the tools to run your business with none of the contracts or complexity. Run your
Starting point is 00:19:44 business smarter to Square. Get started today. So imagine that. Financial audit. Financial data is very well structured, and it's labeled well. So it's very suitable for AI interpretation and manipulation, manipulation in a good sense. And the future is being written right now. For example, they just had an announcement that Citrin Cooperman, a top 20 auditing firm, just purchased, I think, by Blackstone for about $3 billion, which has hundreds or maybe thousands of private company accounts that they work on and they do audits every year. They are auditing processes one by one by one. There are probably a hundred different processes in a typical audit, something like that. And just one of them, quality control, already has an agent that talent is developed and is being
Starting point is 00:20:34 put into production. It's already saving Citrin Cooperman, one firm out of hundreds or thousands around the world, 10% of the spending. So 1.2 million out of the 12 that they spend on quality control is already being saved. Next month in June, they're going to add a second notch to it. That will save 25% of spending. So three out of the 12 is being, that's just in a couple months. This is happening very fast. So you say that many companies are not using it. I beg to differ. They're not using it a lot that you hear about on posters or billboards or maybe other podcasts, but I'm letting you in on the secret. It's happening extremely fast. And just, I'll give you the B to C example. the adoption of ChacheePT, fastest product adoption ever, I think, in human history, right? It went to like
Starting point is 00:21:23 100 million users. Yeah, it was literally on the graph. It's up and up, up and up. It's amazing. So we're living in revolutionary times in a very good sense. You talked about revolution in the bad sense. I'm talking about making humans more productive. And I'll go back to, again, historical analogy, because it's hard to always understand what's happening in the present tense. But our mothers, our grandmothers, our great grandmothers, you know, used to have white. wash, you know, by hand before the washing machine came around. Think how much time that liberated for people, mostly women, to do better, more creative, higher productive things.
Starting point is 00:21:57 So Tellen is automating the auditing process. Auditing is limited, but the data that it will be surfaced from this is unlimited. It's kind of that back to the infinite innovation loop. If you're an M&A banker and you have a client that wants to do an M&A deal in the middle of the year, Say, what are we in? May? So May 21st, you want to do the deal. Well, usually audits are done at the end of the year. So you'd have to do a whole special audit for May. With the audit ability that Talon is doing, it enables daily reconciliation of all the numbers. They flow in from the various systems of record. They are tallied. It's all labeled. It's all structured.
Starting point is 00:22:35 We can have you have a daily audit. Now, with that daily audit, the management, the corporate overseers are seeing data they would never see, except maybe quarterly or annually. So they can get information earlier and they can make decisions faster. It's also going to do something very interesting for the world of credit. And this is where Truly You and Tellen, two companies in the portfolio, will be able to cooperate. Tellen is developing this set of data from all the accounting firms' clients. Most of them are private companies. They don't expose their data. This is not going to be in the open source world of LLMs. This is Mr. Smith's construction company, private financial information. He doesn't share that with the big LLMs.
Starting point is 00:23:21 So Tellen will create this organized, daily reconciled audit ability and information database, data lake, if you will. On an opt-in basis, this construction company can share with peers and on a blinded basis put their information out in return for seeing what the benchmarks are. from competitors. So I will see if I'm spending too much on marketing, if I'm paying too much for plywood in that example. This has never been possible before. How well truly you use it, truly use the identity management company up in Canada.
Starting point is 00:23:57 They are going to use that to create the world's first global credit bureau for small businesses. Public companies have to disclose their financials. So that's knowable for banks and everybody else. Private companies don't. And counterparty risk is a big issue, especially in international trade. So Tellin and Trulley together are going to create this unique, irreplaceable set of data, private company financials, and they're going to make it available for counterparty risk analysis and management, lending. It'll help increase volume of trade in the world thing because you'll be able to say, I want to do business with this guy because he's legit, he's, you know, solid, et cetera, et cetera. And so it should unlock some credit around the world, make
Starting point is 00:24:41 more business available. So I'm super excited. There's so many new paradigms going on with AI. I had the CFO of Lagora on and that to create all new metrics. They created new terminology, new lingo. One thing that's not changing is what makes businesses valuable and that is network effects. And one of the things I see the top AI companies doing is not only gathering the data, doing the processing and efficiency gains, it's building on these, these building on these network effects and building motes.com pound. We talk about the data flywheel that's enabled by a Gentic AI. Here's how it works.
Starting point is 00:25:21 Say your startup company and you have some data that's proprietary. You mentioned radiology. Maybe it's that. Maybe it's construction data. Maybe it's mining data. The data flywheel. And the data flywheel starts with a company that has perhaps no data or it's got some proprietary data set.
Starting point is 00:25:39 The first time a user interacts with that data, small as it is or if it's substantial, the data is increased because of the user interaction. That gets fed back in, that creates new data. That's fed back into the model. That's called reinforcement learning. The reinforcement learning improves the model. Then the model delivers better results. And then there's more users and more data created. And so it's a positive flywheel. So that gives a new, new meaning to the term first mover advantage. First mover advantage used to be talked about in network value or in brand recognition but here it's in the fact that if you start making a data flywheel your data flywheel is going to be earlier than the others and it's
Starting point is 00:26:22 harder for them to catch up because your data is constantly improving and everybody comes to the rational decision where who am I going to use I'm going to use the person with the best model that has the best data they feed their data and so it can compounds there you go so that's why we're extremely excited because it seems to apply to every domain we see. And that answers a question, how do these application companies compete or defend against these large ELMs?
Starting point is 00:26:48 Yes, that does. Most people think, oh, that large LLMs are going to take over everything. No, they're going to become, I think, a little bit more like AWS, Azure, and other cloud vendors. They're going to be a utility. The LLMs, they'll do a lot of things, and they're great. And I want to own a lot of the stocks and so on. But I believe that there's a lot of the stocks and so on.
Starting point is 00:27:07 but I believe that there's a lot of room for proprietary data set vertical experts because the future of agentic AI is about understanding process. And process can be very complicated and often process combined with a proprietary data set is a weird animal all of itself. And it's not as easily exploited by a generic LLM model. In full disclosure, I'm early investor in Anthropic. And I actually think that the most... most Pareto optimal strategy for them to do is to avoid going via verticals.
Starting point is 00:27:43 Obviously, I'm conflicting companies that are verticalized. But the reason for that is the number one risk for Anthropic and Open AI. The number one risk is the government and not the definite being defined in a monotry. And by the way, this is not a new phenomenon. Google's number one risk was that as well. There's a famous Peter Thielism, which is the reason Google has so many different product lines is to confuse the regulators that they don't just dominate the one market, which is Google search.
Starting point is 00:28:13 I think something like at one point more than 95%, I think it was even higher, of their revenue came from search, but they had all these businesses. Why? And Peter Thiel's theory was it was just to confuse people that they were all these different companies, so no one would go after them. But the number one risk. We're not the leader in all our segments, is what they say. Yeah.
Starting point is 00:28:30 Yeah. We have strong competition of all our segments. Exactly. Obviously, Dario and Sam Allman are have huge ambitions going after all sorts of different sectors. Maybe in the very short term, it's optimizing on revenue in the long term. It is not a wise strategy. Well, I won't try and get in their mind. They're doing great as they're doing.
Starting point is 00:28:50 I do think, and I think we agree, that there's a lot of room for substantial companies to be built. The next Fortune 500 companies are being created right now, and many of them will be in vertical domains, where they are masters of complicated processes that are idiosyncratic, their arcane knowledge sets, and they often come associated with specific proprietary data. One more thing. That is that there's a whole other realm. Most people don't talk about it very much, and that is large quantitative models. These are not LLMs.
Starting point is 00:29:22 These are not large language models. These are models about physics and models about mining and geology and protein folding and all kinds of other things. There are many different kinds of algorithms. Most people are just stuck on a certain kind. But there is room for folks with unique algorithms and as well as unique data sets to do very well in this bright future.
Starting point is 00:29:45 Demis Havas, who's the equivalent of the CEO of Google's AI, famously won the Nobel Prize for the Alpha Fold model, which basically figured out the folding is proteins. If you ask me what that means, That's beyond my pay grade, but what was revolutionary in the science space. I had this very same conversation, Dr. Alex Wiesner Gross. He believes that we're going to solve all of math and all of physics. He actually believes it will happen the next two, three years.
Starting point is 00:30:13 Wow. Most people think it's going to happen in the next five, ten years. Either way, it's a good deal from humanity. That's one of the reasons why when people try to predict even five years from now, it's kind of a silly exercise because you have to predict post the solving of physics, post the solving of math, and I'm not even sure Albert Einstein could do that today. Yeah, in many ways, we're already beyond individual productivity or capabilities. There's a study out there that something like 75% of all venture capital went to the top
Starting point is 00:30:46 five firms, these extreme power laws when it comes to actually on the fundraising side. What do you think happens in the long run? Is this a new normal, and is this even rational? It's true, and yet I see its vast flourishing of small firms. People under 50 million, under 100 million sized funds, and I hear a lot of LPs looking for that. And you know what they're saying? They're saying, we want to get close to the universities where this AI is being created. And the people that are closest to the universities are the people that just graduated and are starting these new funds, maybe with very little experience, but they have the relationships.
Starting point is 00:31:24 As much as technology is going to build our future, human relationships are crucial and should be maintained and cherished and cultivate it. So we have this combination of sociobiology, which you and I agree on, very important. Human nature doesn't change very much. Relationships are very important. Human species developed over hundreds of thousands of years in tiny little close-knit clans, right? Family-related, village-related. we're not used to this massive urban sprawl and dense societies that we have today. 20 years ago or something, the scales flipped from majority rural to majority urban.
Starting point is 00:32:04 It's never going back. Many of our LPs use Atapar as their system of record. And for those of you who don't know, Atapar is a system of record for complicated portfolios, both public portfolios, stocks, bonds, things like that, as well as alternatives, private things like venture capital, private equity, real estate and so on. So they just came out on, I think CNBC yesterday with a report that showed that 1.5 trillion AUM that Atapar was tracking. Only 2.8% of that was in venture capital. That surprised me. Double that was in private equity. I don't think that a lot of these small family offices are going to
Starting point is 00:32:40 get into these big giant venture capital funds except as through feeders and maybe through the big banks. And I think that a lot of these new small funds are going to do very well. And the savvy institutions and trying to try and get into their next funds. So I want to give in funds one. If I'm not in fund one, I want to be in fund two. If I can't be in fund two, then fund three. And that's the flip of what it was before. The old institutions used to say, we need to see that you have six funds under your belt before we're going to consider you. And now it seems to be flipping because the pace of change seems to be. Also, the large firms will be affected by the law of averages. Too much money generally gets more mediocre returns. There may be some returns to scale in that I can put a big chunk in Anthropic, as I hope you did. But on average, it seems to me that there's going to be innovation always around the edges.
Starting point is 00:33:36 Well, David, I think we met originally in 2009. So I'd put together... It was a very good year. It was a very good year. I'd put together two founders of a company called Isocket. Zach Husseneen and John Ramey. I did what would later be understood as an unscindicated pre-seed round before pre-seed was... You were a fundless sponsor.
Starting point is 00:33:57 It was my own money. I was a funded sponsor. That's good. That's good. And you helped with a company and you led the Series A. and we've kept up since then, so it's been great to stay in touch, and thanks so much for jumping on the podcast.
Starting point is 00:34:11 Much appreciated. You've done really well, and I'm honored that you had me on, and I'll say something also about this. You talked about the world of AI, and is it going to become making us more zero-sum and, you know, sort of data-driven and automaton's of a sort.
Starting point is 00:34:29 I think that you reached out to me partly because you knew me. Absolutely. decade and a half ago. And we built a nice friendship and mutual respect. And those relationships mean something. And you're a young guy, and I'm going to tell the audience, maybe who are many people who have been younger, most of you will live to a hundred years of age. Life is long. One of the most important things I ever learned was in ninth grade, two futurists came to my high school. John and Mary Nesbit. He used to write these books called Megatrends. They did Megatrends of
Starting point is 00:35:04 the 70s. of the 80s, megatrons of the 90s, I don't know what happened to them after that. The thing that they told me that lasted with me till now is they looked at us, the ninth graders in that back in the 70s, and they said, your parents, talking about my parents' generation, graduated at a time post-World War II when they generally would graduate from high school. Some of them went on to college, and they would go to one company and work for a career for 40 years. Same company, maybe increasing in responsibility, but more or less in the same line. and they would retire with a gold watch in a 40 years.
Starting point is 00:35:38 Your generation, they said, pointing to us, the kids, is going to have an entirely different career history. You're going to work in many different jobs, in many different industries. Many of those industries don't even exist yet. Because we're in a fast-changing world, and then he said, you're going to work in things called biotechnology, which we didn't even know what that meant. Some of you will work in the space economy.
Starting point is 00:36:02 Some of you will work off of planet Earth. Some of you will work in electronics and computers, which will do things that we can't even imagine now. We're at that same kind of inflection point. So thank you, David. I appreciate you jumping on and looking forward to doing this against you. Anytime. Thanks.

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.