AI, Venture Capital & The Power Law Explained | Amar Varma

The plot point on the chart of everybody in this category, the 10 companies getting 41% of the dollars, right? They're just going and land grabbing this whole thing. The cost to start companies that went from tens of millions to millions to hundreds of thousands to ostensibly whatever time you can dedicate to this stuff, marginal cost is phenomenal. I've never seen it in history. Today is the best day in history to start something.

Welcome to the Startup CEO Show. I'm your host, Mark MacLeod. In this episode, I sit down with my good friend Amar Bahrma. If you're a fan of this podcast, you'll know that I have Amar on periodically. For these Tim Ferriss-inspired random episodes. Ammar and I always have these like really interesting conversations, typically on a tennis court, and every once in a while we're like, man, we just gotta bring this shit to the podcast. So we cover lots of ground today talking about, you know, the power law of venture capital. That's always been a thing, but it's more so than ever. 41% of venture dollars so far this year went into just 10 companies. So we talk about implications of that. He had some pretty fun observations about how all these James Bond villains in different industries are becoming true in real life now. We talk about VC pattern recognition and whether that's still a thing. Lots of chat about AI and, you know, you may be running a company that has an incumbent, like in a category with an incumbent. Amar's doing that. And so last thing we did was talk about the implications of that. So lots of really good stuff here. I really hope you enjoy the episode as much as I did. Amar. Welcome to the Startup CEO Show. It's a true pleasure to have you here. How you doing today? I'm doing great.

Always a pleasure to be here, Mark. Thank you for having me.

So for folks following the podcast, you'll know that Amar is by far our most frequent guest. He's a good friend and a country neighbor for a good chunk of the year. And we end up having these very interesting conversations often on the tennis court. And then we were just periodically like, hey man, this shit should be on the podcast. And so welcome back. Um, and maybe to kick things off, you and I were just kind of talking about, um, a recent observation that Jason Lemkin from Saastr made, which is like, so far this year, 41% of all VC dollars have gone to just 10 companies. And so venture has always been this, like the power law of returns, right? So for folks who don't know, like, most of the returns in a venture fund are concentrated in like a very small number of their investments, and those pay for all the other investments. So returns have always been unevenly distributed and capital has always flowed to the winners. But now Jason's saying it's more polarized than ever. And so just to put some numbers on this, so like, and then wanna turn it over to you for your thoughts. So like so far this year through I think this was July, $197 billion in venture funding and 81 of that went to like 10 names, the names we know, like Anthropic, OpenAI, et cetera. So yeah, what are your thoughts on that?

It's a new game. It has changed and to its purest form has become the search for power law. And as time is tracked, every 5, 7-year period, every vintage year kind of thing, the, the track's gotten tighter and tighter and tighter and tighter. And there's the search for runaway names that hap— that occurs. And we're seeing it at its most extreme form, uh, you know, history to date and just our kind of collective histories to date. Um, and it's happening for a few reasons. One, ultimately the expectation And valuation of these power law assets are bigger than we've ever seen them. They're like we expect, they're lagging the public market valuations. So, you know, now you have multiple trillion-dollar-plus valuation public entities that are driving demand for their stock price to— and their stock that's ultimately driving the stock prices up. And then ultimately in their— I call it the magnetic pull, or, you know, uh, planetary gravity pull that they, they have in their ecosystems where they can pull along, uh, infrastructure spend, application spend, the traditional cycles we see. It's just larger than we've ever seen. You know, it's to the point where old nuclear factories are being turned on to power some of these, uh, capital expenditures. So it's, it's you know, back to, back to Sethia saying I'm good for my $80 billion in 2025. Like, this is kind of the, the comments we're seeing.

So the power of Microsoft that, uh, got a nuclear plant to be powered back up.

Yep. The, you know, the one in, in New York State. There's another one, I believe, in, in Ohio that's being fired up, and, and Iowa. And there's just everybody's looking at everyone now, right? What's, what's there? What infrastructure is there? Is it What kind of, what kind of reactors were in there? What's safe? What's unsafe? There's all this analysis and it's partly also—

My sister's a nuclear engineer, so maybe she's in the safest job category around right now.

Possibly. And, and this is one of those arenas where, you know, there's unlimited demand driving unlimited exploration of this stuff. So it's, it's kind of, you know, uh, The Simpsons are relevant again in terms of Homer's job. So that's kind of one of the things I was looking at.

Uh, you know, that power law thing always been the case, right? And I wrote about this a few weeks ago with Lovable going from like zero to $100 million revenue in 8 months. And it used to be like the best in class for SaaS. And this is again, another Lemkinism was like, you would triple in one year, you would triple again, then you would double, double. So like, I don't know, you have $1 million, then you go to $3, then you go to 9, then you go to 18, then you go to 36. So like 4 years in, you're at $36 million, whereas Lovable just tripled that in 8 months. Yeah. Now, and that's just an illustration of like the, the nonlinear, completely explosive growth that's possible with these new, completely disruptive companies. And anyway, my observation about all of this was just like, now, like as a VC, you can't unsee this. Now, you know, that's possible. Now all you want to do is back the next lovable before it takes off. Right. And so like, I feel like the bar for these merely mortal companies, like, oh, oh, you're just going from 3 to 6 million. Like, oh, I don't care. Like, I don't know. What do you think?

Yeah, this is, this is great. So, so let's take it, let's take a step back into the power law. So the, the greatest, the GOATs, you know, that we've seen, and there's, there's a handful of GOATs that have been around for multi-decades. Traditionally came from sizes of funds that were in the few hundred million dollars. Now you're seeing across the board people sitting on billions of dollars in funds, and then they have these growth vehicles that are multi-billion dollars and all of this capital has to go to work. And unless you're in one of the 10 names of this vintage, you won't have the ultimate returns, DPI, whatever metric that gets used to raise the next fund next time. And that's kind of where seeing this massive chase in this ecosystem and the barrier to compete with these folks is getting harder and harder and harder. So I think that's just kind of the power law that you're seeing in terms of size. In terms of the opportunities, lovable, I loved your article on that. No pun intended. I think it was just highlighting how quickly this thing can happen. You see it. And if I take a step back, what's happened is the substrate and the barriers to entry to get into the substrate of, of using AI is the equivalent of using search on, on a browser, right? It's a box. Mm-hmm. So that has opened up a huge swath of, of the internet population to start, try, and use. And you start to, you start to compound your learning and you start to, to figure stuff out. And then what it's unlocked is there was always this cast of people who wrote code, didn't write code, and there was two sides of a line and that line's been blurred now. And everybody feels like, everybody should feel like they can write productive code that goes into production. And that's kind of opened this floodgate to allow people to do it. And you see how much people are willing to pay to get that stamp to do it, right? They're willing to pay Lovable that kind of money in that short period of time. And incredibly, they're not the only company, right? Like you see—

No, that's right. You got Replit, there's probably others. Yeah.

And you see these companies come up and up and then the question ends up being, what's the network effect? What's the moat that you create with these tools? Am I just going to use the next version of Lovable for the next versions of apps? Or am I going to use this? Like, you know, there's just a series of these tools and if you've used them over multiple projects over a longer timeline, you start to see, okay, like clearly Copilot in Get Something you're going to use, or in the Microsoft suite you're going to end up using, right? So that's kind of one of the ones where there's just a built-in network effect and moat., do these other folks have it? Can they be longstanding? Because there's one thing to chase the growth from zero to, you know, 9 figures, which is amazing. Can you get from 9 figures to 10 figures in that period of time? Is there, is there a, is there a growth or is there a petering off and you've bought at the top, right? These are some of the questions that are there in terms of some of these applications. If I switch back to the infrastructure investment, that's just steamrolling. That's still just compounding, you know, um, that I don't see slowing down. I feel like the cost per token is going to get to a place where that infrastructure spend is just going to make even more sense. You'll see them just continue to— some Moore's Law equivalent for making the cost of tokens cheaper.

You don't think the big providers, once we're hooked on tokens, are going to jack the price? Like they're just crack dealers here, your first hit's free, and then afterwards we're going to— hit you up, you know?

It's a great, it's always a worry with different types of players in the system, right? But if you look over time, you know, cloud providers were there and they were forced to bring down the cost of their services. And like smart people, they added new services that you paid more money for, right? So getting into the cloud was easy, firing up a new service cost you money, and leaving their instance for another instance was incredibly expensive, right? So those are the types of things where they know this stuff, they know this game and they'll use Porter's Five Forces to navigate you down the gauntlet.

So I'm curious through your vantage point, not just as a pundit, you're now a part-time pundit, but as an operator, as a CEO, because like on the one hand you see these companies raising just ridiculous amounts of capital. And then on the other hand, what they're building is actually enabling most CEOs to be more capital efficient than ever. Like there's so many headcount functions that you no longer have to scale linearly as revenue grows. I'm thinking about developers, support staff, et cetera. There's a trend with many companies now seedstrapping. I don't know if you've heard this term, which is sort of like skipping the seed round and just bootstrapping your way past that, uh, which AI enables, right? Like it enables efficiency like that we've never had before. So there's sort of like these two opposing things happening. There's a cohort that's being super capital efficient to the point of bootstrapping. And then a cohort, a very small cohort that's like sucking up all the capital in the ecosystem. Do you feel pressure to go one way or the other? Like what do you, how do you react to that?

Yeah, it's a great observation. The ability for all of this capital investment to enable Seed strapping, I think, is the term that you're pulling up. And that's, it's, I understand it. It makes intuitive sense now that you bring it up. It's amazing. If I look back in the history on two vectors, one is think of maybe some of the home automations we've had over time, dishwasher, laundry, those types of things. You didn't go back, you didn't go back to washing your clothes by hand unless you had something very delicate. Maybe you're washing fine china that doesn't fit in a dishwasher, like things like that. And that's maybe the crude analogy that's happened here. If you switch into maybe more of a tech lens, you know, the huge cost of infrastructure projects, of big physical, you know, chips, systems over time led way to creating lighter weight tools., you know, open source tools, software, databases, you know, Ruby on Rails was one that was influential for, for us maybe 17, 18 years ago. And when it kind of just made web development way, way more, um, approachable and you start seeing that play itself out at the scale it's playing itself out now and the cost to start companies that went from, you know, tens of millions to millions to hundreds of thousands to ostensibly whatever time you can dedicate to this stuff, you know, marginal cost is phenomenal. I, I've never seen it in history. I speak at tons of classes, entrepreneurship classes, and I go, today is the best day in history to start something. There's never been a lower barrier to, to get here.

So I remember my first startup I was finance leader for, they had to raise $3 million mostly to buy like Oracle databases and shit just to get started.

Yeah, look at Oracle today.

Yeah, pretty wild for such a big company, right? And they had like crazy guidance. They're like, we're going to grow. I think they said they're going to grow their cloud business like 70% next year or something. Mental.

When you see these data points in public companies and you put together that whole ecosystem of the various vendors that fit into a deployment, the infrastructure, the software, they're just, they're creating the groundwork for, for this next revolution of companies that are coming through. You're seeing it in the Lubbables and the Replit and the Cursors and all this, uh, you know, that category of companies. There's a bunch of others, so I'm not trying to single them out.

Do you feel tempted to raise more capital than you need in this environment?

Or, well, this is, this is very interesting. So I was been looking at our team here at Mantle. We're around 20 people and for the amount of throughput and things that we're doing versus maybe a company, like when we did Autonomic, maybe, you know, 7, 8 years ago, it was probably a third of the staff, what we have versus the output that we're getting versus back then, maybe even less, you know, I'm just trying to think out loud, it might even be less than that. And that's just a tribute to the tools, tribute to our team's ability to execute all those things, but we're not unique in that kind of equation. The numbers might be different, but everybody has that opportunity. So the question is, what are you raising for, right? And if you're raising for, ability to, you know, land grab market share, like the traditional venture types of things, you know, that's really where you're having to look at the money. And that's why you're seeing the barbell distribution or basically the plot point on the chart of everybody in this category, the 10 companies getting 41% of the dollars, right? They think they're just going and land grabbing this whole thing and then following onto it., you know, I'm, I'm, I'm in a, an application layer, uh, you know, what parts of the applications get subsumed by the models and how do you interact with, uh, the data? And, and fundamentally the question I ask myself, I ask all the entrepreneurs is what is your moat today? Because it, it's certainly not the ability to write software or, or create great systems and code.

It's not features.

It's not features. It's the human decisions that impact the success of your product. When I break it down for us, you know, it's our customer choosing to use us to do something. And I go—

So it's a human connection to you is maybe implied, like there's a brand element there.

Yeah. Without that human checkboxing, signing, or agreeing to do something with our company, if that didn't exist, the moat would be But, you know, and, and I, I have a blank, it's a, it's probably a longer, deeper philosophical discussion, but it's like, what is that moat? Because if you don't have the moat, you might get really great liftoff, but if you can't sustain the liftoff, you don't end up being a longstanding business. You might end up being an ephemeral thing that goes and comes. And I'll just give you a quick app, uh, example. I use this one and maybe even used it before here, but you know, we went to brunch, me and some of the, some of the kids, and they really like playing trivia at one of the places we go to, the Soho House, just down the street here. And we went once and somebody was using the board game and I was like, they're like, ah. And I was like, no problem. I went in, I created a trivia app in, I don't know, all of 20 seconds. And we played trivia for at least an hour and a half, having the time of our life for brunch. And at the end of that session, And never looked at that, that thread again. And, you know, it was gone. It's ephemeral. It's missing. It didn't need to be a standalone app in the App Store with distribution and ads, right? It was gone. I was like, oh, the game, the game, like apply that across consumer applications, enterprise applications. And then, you know, just SaaS is really one that I'm really taking a keen look at and being like, what is it that people need to do in the interaction? What's the human in the loop? And then after that, when the human in the loop's no longer used or required, what is that user interface? Is it voice? Is it a text box? Uh, and then when these decisions are being made, not so much by just, you know, AI as we think about it on a machine, but in physical AI, now, now we're, we're in this other one. So if anybody's, you know, if you use Waymo, uh, if you use, you know, self-driving in any of your, your, your vehicles, like you, you, you are using physical AI today., and it's making decisions on your behalf that are, you know, pretty important.

So it's kind of life or death decisions.

Your life's in their hands. So these are the types of things where it's like, okay, like, where's the end of these things? And it's not so much the end, but what can you do as an entrepreneur to grab onto one of these waves, ride it through a crest and see where you can come out on the other end.

Is the role of design changing for you in light of all this?

Incredibly. I love this. So we have, um, the cast of designers that we've worked with over the last couple of decades through Extreme Labs and Pivotal and VMware and Autonomic and all the companies that people have gone on to, I think, you know, like, uh, Echo B, if you went there, and then Ritual, and they're just spread all over. Uh, some work here, uh, with us again, and their ability to articulate what what the product or outcome should be is usually very, very, very good, like a cut above. And they're able to leverage the models better than the average, just because they're, by design, roles, they're very articulate and very opinionated, and they can use the models to output things at a pretty high level. They're now also contributing code, for quite some period of time now, and it's getting better and better and better. It's really impressive. So the design has gone from just a visual aesthetic and a user experience aesthetic to a, let's build that. Let's not just have it in a, you know, prototype. Let's build it. Let's have it on localhost. Let's put a PR through there and let's actually get it into production. It's really impressive. It's taken on a whole expansion of the role. And the interaction has never been more important because if you don't get that first experience tangibly correct, like I use the, you know, when you walk outta the Apple Store with a box handle and you know there's a machine, you have a really nice feeling carrying that box. Like you have to have that kind of experience when you enter someone's product or else it just falls, it falls a bit flat. So it's never been more important.

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So going back to this, the 41%, and of course it's going to the big horizontal players, OpenAI, et cetera. And you made an observation and that was one of the catalysts for like, oh fuck, we need to do another episode, which is like there's a new kind of ecosystem that's being run off OpenAI alumni. So I would love for you to just expand on what you're seeing there.

Yeah, look, I, I think as you know, we both previous lives been, been active investors and still do some personally, but it's like there are ecosystems over time that created a lot of next generation opportunities. If you go back in time and look at all the folks who came out of, you know, that created a lot of the chip companies in the, in the late '80s, '90s, know, they all came out of, you know, AMD and some of the other ones that were longstanding chip companies. You know, then all the telco folks came out of Lucent. Like you could just kind of go through it over time and, you know, then PayPal for software. Yeah. Everybody started coming out of PayPal, has it like probably the best advertised, you know, alumni network on this stuff. You can look at, you know, I'm doing beat a dead horse here, but there's just a few that have been great. Like obviously a lot of Google alumni, et cetera. But I'm looking at what's happening now in folks who have come out of model-based AI companies and they move— the speed at which this is moving is unprecedented. The who you know and the tag you can give somebody in 30 seconds, it's like, oh hey, this person worked at, on this model doing this piece or owned this part of the, you know, of the thing. So like example, this person worked at, OpenAI was part of the training and did it, you know, mixture of experts. Like all of a sudden, like if you could follow that nomenclature and that tagging, you're like, okay, I can visualize where that person's going to go next and what they can accomplish 'cause they have a fluency, they have an adaptability and understanding. And you're like, okay, that's a person who can move this forward. And if you can bet on people who are gonna move this state of the art forward, you're gonna find winners in that. And that ecosystem's happening in a super tight, super fast network. And if you're not in it, you're on the other side. And it's kind of analogous to maybe, it's maybe more so, I think even this week was the YC Demo Days. It's like every company's funded before the demo day, right? So if you didn't approach them, you didn't have the list, or they didn't find you, like, you know, good luck with that, right? So that's kind of how this is, the game is evolving. And this is why you're seeing a lot of fast capital early. You're seeing a lot of bigger funds put money to work early because they just, it's become a bit of a numbers game early in that capacity.

I was reading today about a new AI company from some prominent OpenAI alumni. I think it's called Reflective, like raising, seeking to raise $5 billion. And they're ostensibly a seed stage company. So I don't know, I'm old and crusty, but I don't figure, I don't quite understand how that works, but.

Well, like, look, here's kind of maybe some framing for some of the folks listening. You know, there's always this term acquihire, right? And there's been, you know, you can acquihire a company, you can buy a product that fits in a business line, or you can buy a product line, right? Like those are usually the depths of them where you could just merge equals, which is rare. The acquihire used to be a, and still sometimes is, hey, come work here. You know, we'll give your investors some stock in our promising place and you'll join here as a pretty prominent person. Then that ranges to sometimes like Google was doing acquihires in very nice sums and figures over time. And then like the acquihire now is just at a level that I've not seen. It's like, you know, the ones that NVIDIA is picking up or these people are like OpenAI is picking up. Many things. These are not like, these are not trivial numbers. You know, they are, they are large numbers because the value that they add as a puzzle piece to the ecosystem is so big. And that's why you were seeing some of those offers that, that Zuckerberg, that Facebook Meta was throwing around earlier this summer. It was like, well, it looked like an NBA contract, you know, with less years, or a baseball contract. Like, it was like Oh my goodness, right? Like, there's just that much of a run. There's always going to be value on scarcity of talent, and we're seeing it at the next level.

Do you think all of this is a bubble or evidence of a bubble?

Underlying this is a fundamental shift. This is an equivalent of an industrial revolution. Now, some people want to coin it the fourth industrial revolution. My history's not perfect, so, you know, I'll follow somebody else's tag on this. But this is fundamentally where, you know, I had the Ford Motor Company having bought one of my companies, working there. That was the, one of the quintessential industrial revolution companies. And you're seeing this AI as a next jump in revolution. So that's going to happen. You will always see bubbles in these things because things will get overfunded. You know, how many car companies were there and how many are there today?

Probably hundreds, right?

Hundreds, hundreds to tens, you know, like the, that's happening. Um, so you'll, you'll see it, but I don't know how as an entrepreneur you're, you're, you're not excited by this opportunity. Greed will always have some level of, of, of impact and it might be one of the stronger impacts in a lot of these bubble deals, but as an entrepreneur and investor, like you have to go in with conviction and you have to be there and, and, and kind of to some degree be greedy about it and be greedy about the outcome for, for everything. And if you're, if you're not, you, you risk not being in the, in the, the wave moving you forward. You risk being on the undertip part of it.

Yeah. I mean, Sam Altman himself thinks there may be, we may be in bubble territory, but at the same time, he's enabling pretty big secondary as far as employees, I would say, cashing in.

You know, we've been around the block a few times, right? People always want to focus on one line that someone says instead of an arc and their actions, right? So I think you've got to follow the actions and, you know, really do a fundamental thing on that. And if he said it, he said it, great. But, you know, having the secondaries at those valuations is enabling it.

Which goes back into this notion of OpenAI alumni, right? Like part of what made the PayPal mafia work was they all had this experience, but then they had capital to invest in the next generation. And now you're gonna get a whole bunch of OpenAI employees or alumni with capital to start or invest or both.

You know, there's two things in the journey, um, in a life that I, that I'd look back on. One is, when I was young and maybe not even so young, I had a naivety of opportunity and outcomes. I was like, there's no ceiling in this world. Like I can just go do this thing. That signal is usually stronger generally the younger you are, which is good, but you kind of have to maintain that through life to be in this, in this, uh, in this world, in this business. Right. Um, so you have to have that, that ability to think I can go do it. And that fuels a lot of leaps of faith on what you're doing. I'm just reading like an old friend's book. Barry Diller put out his book recently, so it's really exciting. He, he, oh cool. For all those who know Barry Diller, who's like a Hollywood, uh, exec, and he kind of stumbled into doing, uh, movies on TV and he just never feared failure, right? He didn't, he didn't feel fear of the failure. And, and part of it coupled in there is the naivety of, of like knowing something can work. And the other is not fearing the outcome. Like you, you, you sell your, your stock at whatever valuation and you're, you're financially independent. Your ability to fear a negative outcome is either reduced, limited, or eliminated, right? Like, like you're just like, I don't fear the outcome of this, which is the most awesome place to be. 'Cause that's, those folks do the most ambitious, generally kind of swings at things.

100%. All of my CEOs who've taken secondaries along the way or had a prior exit and now they're back in the ring, all of them are just like de-risked. And to your point, yeah, just have either no or little fear because their downside is taken care of already. Like they don't need this to work. They want it to work, but they're willing to go swing for the fences.

The first win, right, is always what people are chasing. Some people are like, oh, I was a founder and then they become like an associate at a venture firm and it's like they haven't had the win, right? And, and, and maybe they've thought they can go get the win as a venture investor, then come back to doing something later. You know, everybody's got their own path, but it's like once you have that first win where people go, oh, you're on the scoreboard.

It is.

And you never want to play somebody else's marker game, but in your mind you're like, I have the win. I, I have, I don't need, I don't need this output of the scoreboard to be relevant to me. I'm going to drive my own rules, my own engagement. And that's when you just see people move with a different speed and purpose.

I love it.

I'm curious, you're an operator, but you're also a very active investor. Does this environment make you want to invest faster or slower, or there's no change?

This is a long, a great question with a lot of depth. But I, I will try and synthesize some of the thoughts. I've actually spent a good chunk of time looking at power law. Over my career and then some of the venture investments. And then on a risk-adjusted basis, I've started looking over the last decade or dozen years, what were the returns in private markets, risk-adjusted versus owning the S&P, owning names you used in your life every day, including tech, right? Like if you had a, you know, ask, I've been asking folks, who've started setting aside these education savings plans for their children whose kids have just started to go to school. So they're, call it 17, 18 years old. I was like, how big did that get? And the answer varies based on what they invested in. Some people were in index, some people were like, I just, I YOLO'd it. Or like, I did Tesla. I met a friend last week for dinner at old Facebook, forever, like a friend now living in Costa Rica was in town and it was like, he YOLO'd it and like now his child's got high-class tax problems for a few years post-school. Right. It's like, you know, these are high-class problems, right?

Yeah.

So I really started looking at risk-adjusted basis and the answer is, is like if everybody's chasing the 10 companies with 41% of the dollars, either need to have been in those and you need to keep doubling down in those, or you need to be in your mind smart enough that you've caught an early wave where you can still make, you know, the, the, the real power law returns starting early in something that's not necessarily a, you know, a known category yet. And that's, that's where infrastructure we know drives, um, all sorts of applications and, and, and other investments over time. So there's a kind of a historical flywheel there, but you know, will it happen again? Will we be right? Will it happen in a shorter time period with a compressed cycle? Will it take longer? Will subsuming of apps change what this looks like? Like there's just all these things that start to come about it.

Let's talk about that subsuming of apps. That's another observation you had recently. Tell us about that.

Yeah, look, for anybody who's doing productivity work, whether it's for personal or professional use, it's like, like I'll give you an example. I had to pay some city taxes. I was like, it'd be great if that could just get done for me, right? And it's like, well, you could automate it. You could, you know, put a calendar notice for yourself every 6 months or however you want to do it, right? Like the tasks like that can just get taken off your plate. Organizing a vacation and a trip, right? Like, is that a, do I need to go into any of the travel apps now or do I ask the model to curate an agenda for me, you know, click here to buy ticket, you know, like there's just a bunch of these things that are becoming copilots, concierge services, however you wanna think about it. And it's just, it's fascinating for me. So do I go to, you know, vacations.com anymore or am I looking somewhere else? Am I starting somewhere else?, you know, okay, Gemini or ChatGPT, like, or Claude, like, hey, create the agenda for me. Like, like there's this conference coming up, you know, later this year and it's like, hey, what days can I go? What flights can I go? You know, what do I need to bring? Like, these are all, these are all exciting things that I, I'm like, huh, okay, who do I, when I'm gone, what kids' activities do I need to have covered? Like, just, just all of these types of things as a, as a, as an individual and family. And then when you get to work, it gets amplified, right? Like all of the email marketing automation, all of the contract negotiation, a lot of the development, like anything that was kind of friction, a lot of the friction's starting to come out using, using these tools and sometimes the apps get eliminated. Um, yeah, that, that's just part of the subsuming. I'm trying to think of the big, a big one that's just getting eliminated. Like if you go through the stack, you know, Gmail's not going anywhere, Copilot, GitHub's not going anywhere, some messaging apps not going anywhere yet, email's not going anywhere, but you know, do I need, do I need slides?

Blogging's probably gone.

Yeah, yeah, blogging, slides, do I need to, do I need to have a disparate app for slides or can I use a canvas that says, hey, create some slides for me and it has subsumed the slide creating capability and it does it. OpenAI Canvas does a good job of this to allow you to kind of, edit and view, you know, on both sides of the screen. So it's, this concept is coming, it's there, it's not coming, it's there, we're using it. But when I'm in this like everyday, you know, like a frog we're getting boiled, so I'm sometimes losing track of what's hap— what's like the jump functions and the jump steps.

I just got Perplexity's Comet browser yesterday.

Nice.

So it's just another example, right? Like just behavior patterns moving, right? What do you, how much time of your time, like your work time, do you think is spent engaging with an LLM versus inside an application standalone?

Taking a moment to answer this, 'cause it's, it's a bit of an involved answer for me. For quick task-oriented things, it's probably a quick ask into the model. I spend a lot of time in our applications and it's a bit of a morphed one because we use a lot of automation in the applications. That's probably not the right benchmark, but you know, more than 0 times a day I've asked models for things in work context. It's kind of always.

Like I run a 1-person business and I have 3 employees, which is ChatGPT, Claude, and Perplexity. Yeah. And I, I use Claude for creative work. I use Perplexity for research 'cause its origins are search, and I use ChatGPT for everything else.

And what, what's actually super interesting is, is a lot of people will do the, the first layer of the work in, in terms of using these models. What's super interesting now is as the context windows are getting bigger, you can throw more at it, but as the memory capability is starting to come up, You can have the starting point, uh, for analysis have a bunch of context and a bunch of memory on, on situations. And it's super interesting. We use this, um, for initial views of any kind of, uh, contract negotiation. We've fed all of the historical negotiations in the, all of that context, and we now can take any contract we get and get like a green, yellow, and red on any term, right? And it's, it's, it's, we get that as a starting point for which we then go to, you know, Chad and team to get, to get things finalized and stuff at NoSlurp. But it's like, it's like, you know, or is it's just, it happens super fast.

All right, let's switch gears. This one, I'm hoping this will be a fun one. You were talking about James Bond villains and how they're kind of across all these different industry categories and taking over in real life. Do you want to expand on that?

Oh, wow.

Okay.

This has always been fun for me. I've used this for those who've known me a while, and this is kind of an overused analogy, but if you, if you're listening for the first time, this is fun. So I always felt like Hollywood's always had a bit of a movie industry generally across the globe, had a bit of a leading, leading indicator of imagination of how the world could, could unfold. And, um, in this race for AI. You know, if you look at a movie like Ready Player One where it depicts the world as this, you know, place of you only want to be in the virtual space of it, you know, who are the people out there and what are the personas, right? And I think Elon's one to pick out. He's got energy, he's got media, he's got space, he's got transportation, right? He's got AI now. He's got a lot. That's not necessarily the Bond villain per se, but you know, Everyone will have a different opinion, but I look back and I go—

sometimes he seems like a villain. I don't know.

Yeah. Well, everybody, everybody's entitled their opinion on that.

Right.

Uh, and it's like, if I look at media, right? Media, we went through this era of misinformation. Uh, what's the source of truth? You know, I think it was Tomorrow Never Dies, uh, Elliot Carver. Right. Um, this, the chip revolution, this was one of my favorite. I remember going to the theater to watch this one. Semiconductors. If you remember Max Zorin versus Singin' Smythe in A View to a Kill, this is to destroy Silicon Valley and hoard the entire semiconductor chip inventory. We see that happening today. Who's hoarding these things? Who's got contracts and access to these chips? Water sources are becoming incredibly valuable, are always valuable, they're becoming incredibly more valuable as the AI industrial revolution is starting to come through. And like, Who remembers Quantum of Solace? We had Dominic Greene, right? Uh, that character. Energy Alternatives. You know, this one's a bit older. The Man with the Golden Gun. This one's harder. I had to look this one up. Francisco Scaramanga.

I love these names.

And these books aren't new. These movies aren't new. And then, you know, The Spy Who Loved Me, Transportation. We had Carl Stromberg. Like the list goes on and on and on. It's really fun to, fun to do this. Um, all this to bring back the whole context of, you know, though we see things as new and maybe for the first time, somebody's imagined it already. Somebody's already looked up. That's kind of, kind of, you know, James Bond is a lens. I'm sure there's the George Orwell lens. There's a bunch of other lenses you could use on this.

Well, some people bring up Terminator.

Terminator. It's a great one. Yeah. Terminator, the headset, you know, Total Recall now with these Waymo robotaxis. Like, this is fun stuff, right? I remember for Bumptop, uh, Anand did this, uh, 3D user interface. Anand Agarwal, if anybody knows him, he did a 3D interface for, uh, touchscreens. And in his, like, talking about it, he used that movie with, uh, Tom Cruise. What was it where they were using the hand interface?

Minority Report.

Minority Report. And he goes, it's that, but for computers. And I was like, oh, that's a great analogy. You know, it's just, it's just always fun to kind of do that just as a, as a, as a good gut check.

Yeah, that's fascinating. So not to put you on the spot, but where do you, if you have a position, are you in the Terminator's gonna come true camp or it's not gonna come true camp?

So this physical AI element, and there's a lot of talk about it. So let me frame it for how I think about it. You know, AI in the virtual world, like using ChatGPT or any of these, like the number of times we've mentioned that in this podcast is unbelievable. Like the number, anytime you're using like an interface for a compute where this is happening, that's very fun. When you start using it, interacting and interfacing with it in a real world, it's interesting. So like think of the iRobot or again, another movie, but it was just kind of one of these things where it's like the models now at scale have open weights, right? And if, and I can use them, on Sonny's hosting at Groq, Siddhi Madra, I can do that. I can maybe use Aliasaria stuff, put it on my laptop. There's just a bunch of ways to put these models together. And exoskeletons are now at a point where they are incredible. I'm sure you've gone on YouTube at some point or somebody sent you some kind of clip where you're like, robots can do that, right? And it's like navigating this incredible terrain, you know, holding, holding a, you know, tray of glasses or something, right? You're like, wow. And like you start putting those two things together and start, you know, saying, hey, learn to do this, learn to do that. Um, unload it, like something simple, like unload a truck, do something more complicated, drive the truck, right? Like this is, this is, uh, an area where, where people are doing incredibly fun things, um, and impactful things. It's not just fun, it's super impactful. So I think we will, you know, North America, we're probably behind. Waymo is our depiction of seeing a robot in, in the wild. In other societies, you see them kind of outside, right? In China, there, there, you see clips of it. And if you've been, you've seen it. And it's like, okay, so it's a bit of a human change management that we got to figure out here. It's coming. It's coming. I don't know if they're gonna, you know, get programmed in the wrong way and learn things and be nefarious. Like, we all hope that that's not the case. And we gotta put in some safeguards and understanding of how and why as a community we can advance together.

I tell you, I got mixed feelings about robots. I think I would only have a robot in the house if I could turn it off.

Okay, so let's use one. You and I out there slinging on the tennis court, and I have that ball machine that could learn how to make you a better player, would you trust it?

Absolutely.

Okay.

Yeah. Yeah. I'm all over that.

Yeah.

But it's more like a robot around the house. Like, I don't know, making me a drink, opening the door, doing stuff, maybe cooking me dinner. Like I, I want to be able to turn it off at night and not feel like it's going to come in and strangle me while I'm asleep.

Yeah. So like Jetsons styles, right? Like, uh, you know, some, you know, there's an old cartoon, I'm dating myself, but The Jetsons was a cartoon where they lived in the future, right? Robots were taking care of all of this.

For what it's worth, my wife brings up The Jetsons pretty regularly because they would apparently, I don't remember this detail, but the food was just a capsule and it had all the, like, she hates eating. She's like, if I could just take a capsule and have like all of my nutrients, I'd be great.

Yeah. Yeah. People are trying that. Um, yeah, this is super interesting for me. I'm just like, you know, the, the, if, if the robots could take off a bunch of the workload for people, um, that'd be nice.

Mm-hmm.

That'd be nice.

Yeah.

I'm thinking something super basic, like, you know, I was, I was on the freeway and I saw people cutting grass on the freeway and I was like, okay, like, Or if that was just a machine that did its, uh, did its thing and we knew it wouldn't turn around and try and slice someone. Right.

It's like, yeah, I hear you.

I hear you.

There's, there's, and even on the cars, like I was driving to my parents last night and it was mostly straight on a highway. I would have loved it if, if we could truly have autonomous driving here, I would have taken a nap. I was pretty tired, but got to keep your hands on the steering wheel and you got to You don't be looking out. You clearly don't have a car.

That's the problem for you.

I thought it was neutered. The capability was neutered because of Ontario's regulations. I assume the car itself has the capability.

I don't know. The car would do all those things. Yeah, there's a, there's a whole human element of, of design and, and rules and stuff. Like I think you could, you could cheat the, uh, the camera looking at your eyes. Before. It's gotten better now, even if you're wearing sunglasses and, you know, they, they, they're learning, they're learning. Got it. You know, people used to put weighted, weighted bags onto the steering wheel.

Yeah. Yeah, we tried that. All right, I got two more topics for you. One quick one, and then we're gonna bring it back to your company. So, you know, you're an active investor in, in companies and in funds. And a thing I was bringing up with you is like, hey, is, VC pattern recognition out the window. Like all, like again, like, so one pattern is Jason Lemkin's triple, triple, double, double, like best in class. That's a pattern of best in class expectations for SaaS companies. And other patterns might be when you look at the top tier companies, the time between rounds compresses, maybe it was 18 months from the seed to the A, and then it's like 12 to the B and 9 to the C because you just get this momentum, right? So there's like certain patterns. And then of course, VCs looking at all these companies to identify the few to invest in, use pattern recognition as their primary filter. And I wonder with all of these changes, does that filter become less effective?

In the history of mankind, pattern recognition has proven to be valuable. Pattern we're recognizing is being rewritten in some capacity. But I'm sure when we look back in a couple years on the other side of this chasm, it'll be like, oh, that was obvious. It was the same thing we did last cycle.

Right.

It happens every time. But the observation of, you know, uh, triple, triple, double, double, um, that's just a filter now. That's not really an, uh, it's not really an observation of like, uh, to me anymore where it's like, well, I could see that. I could see that happen in that company that's sitting at, you know, 1 million today and it'll triple, triple, double, double, and you're sitting at $35 million in 4 years, right? Like, maybe, right? But what's the pattern? It's like, okay, I've seen super cycles of investment. I know roadmaps of the incumbents are moving like at light speed, but there's a warp light speed of like the next, next roadmap items they need. They think the roadmap's gonna go there in 2 cycles. So you're building for this next cycle of, of, of, uh, roadmap and you either connect with their roadmap and vision or you miss. Like that's, that's an obvious pattern to me. And if you can hit that next, next roadmap item, um, you have a chance to catch the wave, right? Um, that's a, that's a pattern recognition thing I've just seen over time. Always, always be successful. Um, easy to say, hard to do, but it's just changing. I feel like that network effect of being inside one of these closed networks that has the ability to influence and move markets, like there are companies out there that can adopt a solution and anoint a company overnight, right? Like that's just, it's always been the case, but it's more prevalent now just given the scale. Data center ops, you know, GPU management, like there's just a, there's a whole ton of these things that were, were kind of quirky things that have just like grown at scale. You know, how do you quickly create physical space for a data center in, in, in the desert? Is it a tent? Is it concrete wall? Is it like all of these things are getting rethought, rewired, and that's a supercycle spending on a pattern, but it's not a, it's to your point, maybe the SaaS revenue one is, is, is an observation and not so much a pattern to, to watch right now.

Well, I'll tell you, I'm not gonna go raise a venture fund anytime soon.

Well, let's spend a minute on this, right? Like you, you've been asked to join a number of firms since you've chosen to do other things and, and, you know, likewise. And it's like, if you were to do it today, let's just frame it here. What would you do? What would you raise? What would your thesis be? And I'm just like, you could either be so small, so nimble, 'cause you know the 10 people that matter, which is rare. Or you have to be so large that people are, have a gravitational pull to you because of your scale. Um, and your referral and networking engine need to be on point, right? Like that's really hard to do 2 vintages back to back. I, I've seen very few people be able to be at the top for multiple vintages. So I, you can always come back to it during different timelines and stuff. Cause you'd be like, hey, I was successful in this, this part of a, of a supercycle. Or, or, you know, yeah, it's, it's a tough one. Would you raise 10 million, 100 million, a billion, 10 billion? Would it be a buyout funded at 100 billion? Like, like it's just, I, yeah, I'll tell you.

So last time I was a VC, it was seed stage. And I stopped doing that for a number of reasons. One, I didn't believe in the industry at the time. Location mattered far more than it did today, and I didn't feel that I could out Sequoia Sequoia from Montreal with a tiny fund. But also at that stage, product mattered a lot, and I'm not a product person. I now spend all of my time helping CEOs grow faster than their business and have observed many who've achieved real scale. So if I were to pick a focus for me, it would be that, like getting a fund that is focused on the growth stage. You're, you've hit escape velocity. Now you're scrambling to keep up. And my entire focus is actually on the CEO and like, how do I help them grow? You know?

Love it. So betting on the jockey, so to speak, right? Like who's taming the horse, who's going to bring it around the track to use that sports analogy. Okay. In 2025, I would suggest you either need to have fast, nimble capital at any scale, plus at scale, you see these firms, they have all of these different product offerings that help to generate alpha now. Like it's gone past just recruiting and you know, it's like, I have an investor and they're great in Craft and they have like, how do you do product-led growth? How do you do like, it just, they have, you know, sales-led growth. They have all of these, not just playbooks or blogs, they have teams, they have people, they have programs. And they have unlimited cycles to spend with you. So to the extent that you can, like, and you should spend time with them, that's, that's part of delivering the alpha and attracting these deals now. Right. And it's like, it's, it's become a very functionally broad business versus what it was. You kind of need to have that. And I love that you're focusing on, you know, the, the CEOs of these ventures, 'cause that's generally where your alpha's gonna come, their ability to scale or not.

Get the CEO right, they'll get the rest right. I don't want to overly simplify, but look at all the biggest outcomes. They're founder-led.

Yes. Yeah. I think that's hard for people to digest. Maybe, maybe not in your audience, but just let's, let's go through it, right? Like, you know, Bill Gates, you know, uh, to the extent Larry and Sergey were there, uh, you know, Salesforce, NVIDIA, um, Zuckerberg, Benioff, Meta, you know, like, um, Toby's, Toby's the, like, amazing, like, these are amazing examples of founder-led, like, and I learned this in Silicon Valley when I moved there, uh, just after finishing school, like, all of the companies were founder-led and the companies were either, you know, public or startups and it was all founder-led and you saw, you saw a different attention to doing things. Um, from the, the founders that were running the place because there was always an attention on getting it right. No matter what the detail was, there was no, there was never this big company like, uh, the system will take care of it, we'll be fine. You know, like it was always like, we gotta get this detail right no matter how big or small the consequence was. And it was like this attention to detail that just got people grinding to get it right.

Yep. Yeah, totally. All right. Final topic, Ammar. And I threw this one last minute, like when we were just riffing before we went on air, but you know, there's probably many folks watching or listening, building in a category that has an incumbent and that's your reality kind of in your space, kind of in this whole kind of cap table management place. I'm pretty sure most, well, actually I'm not I'm not gonna make an assumption you're gonna say, but anyway, when folks think about that category, they probably think about Carta. And so I'm just curious, you know, as you were thinking about this, what did, did the presence of an incumbent motivate you, make you afraid? Like you were indifferent, you didn't care, you just saw the opportunity, you were scratching your own itch. I don't know, just turning the mic over to you, whatever, whatever thoughts come to mind.

So I think, you know, a lot of people building companies are, you know, there's the zero billion dollar analogy, right? You're either in a market where you're going to, if you're correct, you're going to go from a zero billion dollar market to a much bigger market. And then there's the, you know, shrinking a multi-billion dollar market from $4 billion to $2 billion or something like that, where you've driven a bunch of efficiencies. And then there's ones that can get both, right? They can they can nail both. Generally speaking, you're always up against an incumbent, which is the existing way that something is working. The current mode of operation from these textbooks, right? How are people doing it today? And I think if you fear the incumbent enough that you're like, I'm not going to do this, um, you know, that's a data point. If you, you know, if I told you 25 years ago, this company that left for like Nvidia would be, I think it's like maybe 10 times, maybe 20 times more valuable than Intel. You would, you would, you would, you would be like, bro, there's no way, right? Like you would just argue, you would be like, what? Like, no, come on, man, you lost all credibility. Like it would be like this crazy conversation. So if you're, if you're not willing to take on incumbents, if you're not willing to see where the market is going, um, you know, don't, don't play. Like, that's a simple thing. No, no crying in the, in the playing field. I love that we have in, in our business, obviously, uh, for, for cap table spreadsheets was the thing, and Carta created a tremendous business around it. I got a lot of time and respect for that, but I, I feel like for that business, we understand where that market's going, and we think there's room for not just one, there's room for more. And it's not just to be second. Like, we want to eventually, you know, win this marketplace, right?

I love it.

As we look across the entire spectrum of alternative assets and private assets, which is where Mantle plays, whether you're a company, a founder, an employee, a general partner in a fund, you're a limited partner in a fund. Like we've launched a second product in limited partners now. Like we, we think that The infrastructure here is at its infancy and with the power of automation, we've just been able to kind of create a lot of it very quickly. And if you look at some of the tailwinds we have, you know what happened, you know, in America there's an executive order to allow private assets into 401s and 401s is a, I don't know, $12 trillion. I don't know the exact number. It's probably, it's probably a very large number. And then BlackRock came out and said, well, instead of owning 60% stocks, 40% bonds, what about 55, 35, and 10? And it's like, and the 10 is now a private alternative asset bucket. Okay. That's a huge number of dollars that's going to, it's going to start going into that. And then now you have to look at all those dollars coming in. What are the products? What's the infrastructure? How does it get tracked? And then what's the tooling for that? You can't log into your bank account and see all your private assets. There's no way to transact it or no way to understand what you have. So this is not about, you know, anything other than just being able to get your handle around what's there as a starting point, creating infrastructure for transparency. And then ultimately what happens to it over time is the market will dictate, like, this is why Bloomberg works so well. There's that transparency underlying in the public market. Driven by, you know, a CUSIP code, which is a technical term, and it allows everybody to track each and every single asset and allows them to have communities and applications and all, all these fun things.

Fascinating. I love it. Well, I, I definitely think there's room for you to come in and win this market and yeah, excited to see you do it.

Well, thanks. I appreciate it. As always, I love watching your episodes. Uh, and I love, I love coming. So like, it's always a pleasure to be on here. So thank you and keep doing what you're doing. I love it.

Thanks, Amar. Always learn from you. So great that others can learn from you as well. We'll see it. We'll have you back on soon. Take care. Hey, thanks for listening to The Startup CEO Show. If you'd like to connect with me, be sure to visit my website at markmacleod.me or follow me on LinkedIn at The Mark MacLeod. Or Twitter @MarkMacLeod_. And if you want to tune in again next week, be sure to subscribe on YouTube, Spotify, Apple, or wherever you get your podcasts. We'll see you next time.