Big Technology Podcast - Where Are The AI Startups? — With Rick Heitzmann

Episode Date: October 15, 2025

Rick Heitzmann is the founder and managing director of FirstMark Capital. Heitzmann joins Big Technology Podcast to discuss whether AI startups can compete against the ChatGPTs of the world, or whether the big AI bots have ingested all the opportunity. Tune in to hear Heitzmann break down the economics of AI investing today and whether the application layer is investable. We'll also break down the big funding deals in AI today, looking at the potential for the frenzy to pay off. Tune in for a sensible discussion of the potential future of AI innovation. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. Want a discount for Big Technology on Substack + Discord? Here’s 25% off for the first year: https://www.bigtechnology.com/subscribe?coupon=0843016b Questions? Feedback? Write to: [e-mail]

Where are the AI startups? Are they actually coming or will chat GPT gobble at all? We'll talk about it with Rick Heitzman, a first Mark Capital right after this. Capital One's tech team isn't just talking about multi-agentic AI. They already deployed one. It's called chat concierge and it's simplifying car shopping. Using self-reflection and layered reasoning with live API checks, it doesn't just help buyers find a car they love. It helps schedule a test drive,

get pre-approved for financing, and estimate trade and value. Advanced, intuitive, and deployed. That's how they stack. That's technology at Capital One. Welcome to Big Technology Podcast, a show for cool-headed and nuanced conversation of the tech world and beyond. Well, something we've been wondering on the show is, where are all the individual AI startups? We know, of course, about ChatGPT and Claude and the big chatbots, but why hasn't there been a wave of individual? startups building on top of generative AI that has emerged alongside this wave. And we have the

perfect person to speak with us about this today because Rick Heitzman is here. He is the managing partner and founder of First Mark Capital and he is here with us in studio today to talk all about it. Rick, welcome to the show. Thank you. Thank you for having me, a longtime listener, first time guest. So it's always exciting. It's great to have you here. I love running into you before we're about to go on. CBC. Usually one of us is right before, right after. So today we actually have some time to speak with each other one-on-one. I'm usually your opening act. Or the other way around.

So let's go to the big question, right, which we started with here. If you believe that generative AI is a transformative technology or at least has the ability to make some waves in the tech world, which I think is basically consensus in this world, where are all the AI startups? Of course, you have some point solutions like Harvey, which is really good for lawyers. But if you took the functionality that's baked within generative AI and you sort of unleashed it to all these startup developers without chat GPT, my guess is we would see a swarm of AI startups, something that you could use for fitness, something that you could use to find

the best surf break, which I know is a application that you've played with. But we haven't seen that wave. So what's happening? So we're starting to see some things. You know, it generally has to do with how specific and how big your data is. And I think there's a couple things which create this dynamic that we're seeing in the market. First of all, I think open AI and chat GPT have done a great job of making a very good product that has both breath and depth. So, you know, the leader not being complacent is something, you know, we hope as venture capitalists that there's leaders and then they get lazy, they get complacent, they get slow, and they get easy to disrupt. I think in this case, Open AI has done an excellent job of not being any of those things, hiring great people,

continue to develop product very quickly. The other thing is a lot of the data, so your AI is only good as your underlying data and your training data. So a lot of the training data in general consumer is general broad-based web. And, you know, obviously you're seeing litigation around who's training on what data, and is it all the books in the world, is it all the crawlers on Google or all the crawlers on the open web. And there's not been a differentiation based on data, which is slightly different than, you know, you alluded to Harvey and some of the enterprise AI companies.

We had a company, Evolution IQ and insurance. There's Harvey in legal. There's Henry in commercial real estate. And they all have a very discreet and sometimes private data set that enables them to build a better model, enables them to deliver a better end user application. But for, You know, you and I, who are trying to find surf breaks or where to go on vacation or the best place to have a French dip in New York, answers for Charles. But if you're trying to find those things and I'm not available on a podcast, you know, those things have generally been broad-based chat GPT or perplexity. And we, frankly, have been a bit frustrated by the lack of startups we've seen in their ability to invest along those lines. Right. By the way, Harvey Henry, I'm sensing a trend here.

There's a trainer, yeah. Is it the new dot L.Y? You just take a random guy's first name? I think so. It's easy to say, easy to pronounce. We'll see. And there was Blue Nile and there was Amazon and there was a bunch of things in the 90s. Maybe this is the thing.

These things go in waves. There are memes. All right. But let's drill down on this because I think this is a really important point, right? Just to give an example, there was about 10 years ago when I was at BuzzFeed writing about consumer tech, there was this nutrition app that I would use. And you would upload your meal. and your thoughts and stuff like that

and a real nutritionist would take a look and give you a rating and give you advice about how you were tracking on your goals. Now, people laughed at me. I was like, you can just program that app with natural language, but you really can. And it's something I know it's not just me. Many people have been using Chi-CTPT as a diet coach

where you give it a goal. By the way, you don't just say be my diet coach, you actually give it a goal. You say, I want to keep under 2,000 calories a day or I want to eat whole foods. And then you can upload photos. You can see the photos, upload with text, talk about morning weigh-ins, give it the data.

And it does a great job of keeping track of this stuff. Now, again, without Chatchip-T, if you have to it. It's a really good product. Absolutely. It's a really good product that has breath. And, you know, so it's solving your problem. But this is my question then from your perspective. Are we about to see a wave of consumer startup

that never happened because that was a real startup that got millions of dollars of funding got a nice exit I think to a health insurance company sure and today you can't it's hard for me to even conceptualize that that would get funding because a VC might just say why wouldn't I just do this in chat sheet we've seen a lot we've seen nutritionists we've seen a bunch of different things that have come out you know so I would say there's buckets of do you need a discreet application or you don't need a discrete application certain things for a bunch of different reasons including regulatory and compliance in areas like health tech, you need a discrete application.

But certain things, including general things like, you know, I'm eating this piece of salmon, how many calories does it have? Could you count it in your calories? Some chat GPT is great for. So we've found, sadly, that, you know, we haven't seen this wave of startups that we believe are sustainable. So there's actually been a handful of startups that are wrappers on chat GPT that are maybe a little bit better at travel.

They might be a little bit better at being your math tutor, but they're not that step function different. And even if you go back to the areas of search, if you remember, there was search, and then people said, oh, there could be vertical search where we get really good at something. So obviously, indeed is a very large company that was vertical search for jobs. Kayak was a very big, multi-billion dollar outcome. That was vertical search for travel. And, you know, you were able to break down that landscape and then think about where that goes. because with a more narrow focus, you should be better at it. And I just think that the broad landscape of chat GPT has made that more difficult than ever.

Yeah, and it's very interesting because OpenAI recently released data, and of course it's coming from OpenAI. Yes. But data about how people use chat GPT, we've talked about it here on the show. And the number one use that people go to it is for practical guidance. Yes. And let's just do a thought exercise. If there was no chat chip EPD and no broadly available generative AI technology, so think about it, you can't license an LLM. But a company came to you, let's say, five years ago, and they said, we have an app that with natural language will advise you on your relationship and tell you whether or not to break up with your boyfriend or girlfriend, for instance, or how to improve the relationship.

If they came to you and said, we have a natural language fitness coach, if they came to you and said we have you upload photos or video. of your of your soccer practice and we'll talk to you about positioning and and form each one of those ideas to me sounds like they would be like billion dollar ideas right yeah very financable very if maybe not billion dollar ideas we'll see where that goes but very financeable if you think about life coaches fitness coaches sports coaches anything where you have a tremendous amount of knowledge and you could take that knowledge and make it very specific to somebody which you know again going back to harvey is is not that different right law is a huge huge pool of knowledge that you put a certain rules around it you know

historically they just thought that was a thought exercise in rules today we could call it l-lm and then that produces better faster cheaper results of how to how to be more efficient in your life or job i mean even harvey uh you know we talk about harvey right which is again this is this is legal a i that you can that knows your knows the laws knows the rules has these big context windows so you can go to it for, like, legal advice or a lawyer would use it, you know, to help. But even Harvey, to me, doesn't even seem that defensible because what we're starting to see is bigger and bigger context windows from these models. So, like, what Harvey's great at is it has the, it's figured out a way to get the applicable law

and then find a way to measure that against the questions you might have as a lawyer. We are going to get to the point, I think, without a doubt, that a lawyer will be able to say, download the zip file of all the law and the state. Yes. uploaded into the context window, download the specifics of the case, uploaded into the context window, and maybe get close to as good as Harvey is. Yeah, I mean, and that's a very specific thing on the case where you might need a specific attorney. If you think about probably 80%, unfortunately not a lawyer, but 80% of all legal work is,

this is Rick, he needs a will. This is, you know, here is a first mark company that's going through a series A financing. Can you just reproduce documents given these are the founders, these are, these are the issues, and here's the term sheet. So there's a lot of rote work that's done by the bottom of the legal pyramid, which should be done better, faster, cheaper than overworked, overtired associate. Right. And so the question is, where does it get done? And the argument that I'm making or trying to tease out here is, does all this stuff end up just happening within the chat GPT interface? You know, I think it's kind of been this debate that's gone on where people say that any

AI application is just a wrapper, like perplexity is just an AI wrapper that you do search in. And so then how do you invest? And so I'm trying to like think through the beginning of our conversation here where we're talking about all these distinct and discrete different applications, legal, but you know, even more applicable coaching, fitness, search. It's all going to happen within these broad, multi-general purpose bots. And so then I like throw my hands up and say, well, what's going to happen? Like, what's going to happen to start? Startup founders and investors, what's going to happen? Podcasters.

But no, but really in terms of the economic activity. But we can get to, we are going to get to jobs, but the economic activity is interesting. Probably two pieces. And one is slightly red teaming. It is, all right, so can Chad CheapD be better at everything than everybody? Probably not. There's going to be limitations. If you ask Sam, Altman, he'll say yes.

And then there's an asymptote where, you know, are the latest models, the best model? And are you still seeing even a step function improvement in chat GPT? Conventional wisdom is probably not. You're seeing like, oh, it gets most of the things and that's good. And what does that mean for the broad-based ecosystem to get maybe that last 10%? Do you need a specific model to travel or to law? The second piece is, all right, well, how these models will get better is through better data. And then is there specific data which people might not trust in Open AI or

or chat GPT. And we're investors in a couple of companies that does do data security. What data are you sharing with what models? Are they staying inside your environment? Are we making sure that all our pieces of that data are not leaking out into a model or into another part of that ecosystem? So if you have a private walled garden of your data, your model, and your security, you know, will that be better because it's more specific to you?

you even on a personal basis. If you're talking about your relationship or where you're going on vacation, where your finances or your will, or on an enterprise basis. So, you know, here are all my legal documents on all my deals. I probably don't want that out in the world, but I want to have some parameters around it where here are all my returns for my funds. I want to make sure that that's confidential. So, you know, are people going to get scared no differently than they then they become suspicious of other large companies, are they going to become overly suspicious of OpenAI, chat GPT, the larger models,

and is that data privacy going to be a key limiter to how the next generation of companies evolve? I mean, I would imagine security is like a highly investable place here. We're spending a lot of time around that, on every level of the data security, model security, you know, every around the enterprise environment, and all of those pieces, I think we're maybe not even in the first inning. Yeah, we just did a podcast with Enoncostica, the co-founder of WIS.

Yes. And it was just sold to Google for $32 billion. Biggest venture outcome ever. Ever. Yes. For now. For now. And we had comments coming in being like, you need to speak about this more often.

And it was just like, here's a general lay of the land, but clearly there's real concern there. So, okay, so security is one place. Yes. There's certain specific enterprise use cases elsewhere. Is there anywhere like on a consumer or I don't even know, should I call it traditional technology investment place where you would see a generative AI startup, like a startup, let me put it this way, a startup using generative AI at the heart of it that you would invest in. On the application layer, I assume. Yes. Yeah.

So on the application layer, we do. I think we like the enterprise space. We're investors in a couple of things in the enterprise AI. they tend to have two things. They tend to have a defined set of customers, which have, therefore, a defined set of data. And they have some rules around what is shared data and which own data,

and that data is the competitive advantage, not necessarily the model, that outputs to the right application and the right answers. And sometimes they use it within their own walled garden. So if you were a company that says, I want to have all my leases historically, and therefore I want to understand all my leases across all of my, you know, Starbucks franchises. All right, well, getting very specific lease data is going to be very much different than

getting, you know, generic answers from, you know, what downtown New York looks like in the Open AI models. So having the specific data, having specific rules around your company, and having kind of a walled garden within a particular industry, that that model can be tuned to that particular industry. And then there's some benefits that maybe even collaboration or a co-op database that makes that more sustainable in the medium or long term. So, you know, if data is kind of the oxygen for a lot of these applications and models, having some kind of ownership on that. So I think when people talk about tech startups, what makes a good tech startup? I'm sure you have a

philosophy. I think one of the consistent philosophies I've heard is that it solves a problem. Yes. And I think that's kind of nice. Like one of the nice parts, like take the fitness example that I was, or the diet example, is that you get a company with, uh, that gets together with fitness experts or diet experts and says, let's try to see what the problem is and pay a lot of attention to it and then try to solve it for people. Yeah. And now you have large language models that are like doing just as good or not not just as good. Almost as. good. And so that would make that category less investable for you. Do we lose something if people, instead of, you know, getting a chance to get this advice from the specialists, are instead of going

to these apps that we've seen, you know, for the better part of 20 years, come up and serve use cases and sometimes do a good job and sometimes not? But do we lose something if instead of seeing these apps come up and these technology companies come up, all this basically gets handed over to chatbots that do like 75% as good of a job, but just don't take the startup and capital to get there. Well, you hope that there is a bit of creative destruction, right? So if you say they're doing 75, I was going to guess 80, you know, you pick a number in between, and only the expert is going to sit on top of it and say, hey, I'm going to be your dietitian. I'm going to use the back end of chat GPT like you would, but I'm going to give you some more advice

because I know you're going to this steakhouse tonight and you're trying to watch your cholesterol, whatever that may be. So does chat chippy tea, though. So it probably made that reservation for you. It probably made the end. It knows what the menu is and knows what your goals are and how to do it. But there might, maybe there's an interface on top of it,

which might even be a human. So how do you know and understand your discrete value at? So your discrete value at is a human. It's not being able to Google the restaurant menu and pick out fish. That's really good. People get paid a lot of money for that. They currently do. But it might be.

I know you better. I know that salmon might be the right answer for you, but you just don't like salmon. Or you ate salmon the last two nights or whatever it is. So I'm going to find something specific to you that I know you'd like. Or I talked to you today and you said, you know what? I'm not in the mood for fish or I just want to, you know what?

I just want to steak tonight. I'm going to go down that path. So their ability, and maybe this becomes personalized over time, which your chat bot knows that your, tired because it's plugging in your route data or it knows that, uh, you had salmon the last two nights because it also tracked your food and your restaurant reservations over the last two weeks, you know, it could get an additional level of personalization, but like every time

through history, the human's job is just saying just ahead of that technology and understand where they could create unique and discreet value on top of technology. Yeah. I think that's going to be tough. Maybe I'm, I have confidence in the humans. Okay. I do, too. Yes.

And it's interesting to be even having this discussion because there's clearly so many holes in the generative AI technology today. Like, at all of these tasks, it's not as good as a human today. Yes. But it's getting close enough to make the questions relevant. It's getting much closer. And if you look at where it was five years ago and the progress it's made, it's getting closer. I mean, we're looking at AI companionship.

And whether that's dating or whether that's for elderly people or whether that's for kids or whether that's for tutoring. And as we looked at it even last year or two years ago, like, this isn't very good. Like, I'm like, I'm not sure, you know, my elderly grandmother or my kid is really going to engage with a chatbot that acts like this. Now it's really good. Now it's pretty clear. And now, you know, people are engaging in, I'm sure you read about it all the time, more and more meaningful relationships. Or everyone could tell what was AI generated advertising or AI-generated advertising or AI-generated.

video, or even AI-generated actress. And, you know, there's this now famous AI-based actress who is in a bidding war to be represented by the major talent agencies that you can't tell. And that person is almost as good as a human. And I think this is going to continue to happen. But it's going to be very disruptive for people who can adjust their mindset or think about creating value to stay ahead of the curve. Yeah, there's some fascinating applications. I mean, of course, there's concerns here as well people becoming overly dependent on these bots the bots being sycophantic encouraging them to do self-destructive behavior but on the other side there's some amazing applications we've talked about on the show here there's uh in korea there is a like a stuffed

animal with an l-lm baked in yes that's like hanging out with elderly people who are lonely yeah keeping them company and then when they sense issues or they check whether they're taking their medication and the person who's become friends with this LLM stuffed animals says, I'm done taking my meds. Then they send a message to the nurse. Or I don't know or, you know, it's like the nth degree of my fall and I can't get up that, you know, all these things. And, you know, it started off very simplistically. I'm going to send a text at 8 o'clock every morning making sure that this elderly person took all five of their meds and, you know, maybe you had to ask a minute. Now it's become much more conversational, much more engaging.

It could be via chat. It could be via audio and voice, which is better than, you know, having, you know, someone have to go into each line of a text thread. So that's becoming much more approachable. But I'm not sure, yeah, I'm not sure if we're ready to, you know, there's always the dark side, which you touch on the self-harm, the, you know, the different personalities, actually, that each of these bots have, and thinking about that, and what is the, what's the unintended consequence of something to be getting that good that quickly?

And as an investor, is that something that you want to touch or you're... No, we're looking. We're spending a lot of time. I think, you know, AI companionship is an incredible thing, and it's a broad-based companionship. It could be your medical buddy. If you're an elderly person, it could be your math buddy. If you're a student, it could be your friend who, it could be your surf buddy. if you're trying to figure out where to go on vacation.

So all these buddies, some of which are going to be chat GPT, you know, are going to be out there. And then I think you have to think about, you know, how much is that self-directed? So how much is it understanding your personality and where you're inputting? And are they sycophantic? Are, you know, do you have a drill sergeant type nutritionist? And is that what you want or what you need? You'll be able to tune it yourself. Or it will adapt because you're going to give it numbers and it will be like, oh, I was

hard on them. Yes. Stop talking to me. Now I'm a little more sycophantic. Yeah. I'm sorry about that. You could have had the stake. You know, French fries aren't the end of the world and you earned a cheat day.

Okay. I will sign up for that. So now after spending our first bunch of minutes together talking about how AI is going to gobble things up, maybe everything, I'm going to now ask you whether we're in whether a tech industry or investors are putting too much money into AI. into AI. It sounds inconsistent, but I think it could both be true because... I think they both could be true. It's hard to say what too much money is. I mean, what's been very clear is all the hyper-scalers are investing as much as they possibly can. And maybe even differently than probably prior times in history and the two ones I've seen cited the most are the railroads and then the infrastructure of the internet. And I'm familiar

with the last one. Amazingly, I was VC during that last. time in the late 90s, the, they were, those markets were largely reliant on external capital, right? You were, if you were building out a CLEC or if you were building out, you know, internet infrastructure, dark fiber, you were relying on equity or debt from the capital markets. And therefore, when that shut off or that became more expensive or the markets didn't buy in, it was able to control that oxygen and that buildout. The different thing this time, or one of the different things this time, is that the hyperscalers are actually paying for this through their own earnings. So effectively, obviously, the market gets to vote through your

stock price, but they don't have to go out and say, I'm investing, you know, $100 million in energy for my data centers. And I'm just going to take, you know, this quarter, half of this quarter's EBITDA and build that out because I believe that's an important part and an important use of my cash flow. And maybe the market will frown on Mark Zuckerberg if he chooses to do it. But he's not going to be beholden to anybody as you are when you go hat and hand asking for capital. So I think this is not going to stop. And I also think the hyperscalers, all of their ambitions are so big and so broad. And they're also pot committed. I don't think anyone's going to stop. So, you know, it's going to take something incredibly material where there's not an outside person

who's saying, hey, I'm stopping writing the checks for you know, for you to buy dark fiber that you're not going to light up or I'm not going to, you know, build a railroad to nowhere because that doesn't make sense anymore despite where the hype was in the market. You know, that has to be internal and that has to be, hey, I'm bowing out of this part of the AI race, which I think given the ego's market caps and dollars involved, I think that would be too hard to do. So just give us some context here. Do you know off the top of the head? had the largest check that First Mark has put into a company? Or can give us a ballpark?

$200 million. Okay. Jensen just committed, or recently committed, $100 billion to Open AI. One day, one check. I mean, it's more than what's been a couple of years, certain in certain years of all venture capital. So what, so you obviously, when you're putting in these checks, you have to think about what am I going to get in return.

Yes. What do you have to get, if you invest a hundred billion in a company, do you need to get a trillion dollars at least back in return? Well, it depends on who you are, and that kind of goes to the recycling or the circularness of some of these things. Obviously, the Open AI Microsoft, or Open AI, goes back to the Open AI Oracle deal. And, you know, I'm going to give you money that you're going to invest in our infrastructure. or how does this cycle of capital work, which tends to be towards the end of these cycles, right, where you can't generate enough money yourself. You might have exhausted the capital pools externally.

So now we're going to all give each other revenue and cash flow to keep the train going. So that is actually a little bit of a canary in the coal mine of how this is working. But, and then also, you know, Nvidia's worth so much money that, you know, Jensica almost say, $100 billion is not that big of a deal if we believe this is a generational company and have somewhat of a leg to stand on. Right. And, you know, not that long ago, $100 billion was greater than the market cap of all but a few companies.

So, you know, it's, it's, the numbers are so mind-blowingly disproportionate, it's hard to really contextualize it. Right. And we should say, again, with many open AI investments, it's kind of funny, at least at the beginning. It's 10 billion to start with plans to contribute another 90 billion in increments. And, you know, the best part of one of the good parts of, you know, opening eye being private is they can do a lot of these deals. Right. Where they don't, you know, definitely don't have to be disclosed, obviously, because in video is public, they're going to have

to disclose that or Oracle or whatever it is, that they're able to put up, you know, great top line numbers, no different than maybe AOL did in the late 90s of, hey, here's a, here's a, the top line, but it's really a contribution in kind and there's really some milestones to it and there's really some other things, which also is very much a symbol of like a very frothy market of, hey, we're not talking about actual financial metrics or actual gap revenue or actual cash on the barrelhead. We're talking about a theoretical milestone-based broader in-cash, in-kind, dollar amount, which might not be real dollars. Right. I think Jensen has referred to it as partnership first and investment second. And that's interesting because it would be by far the

biggest investment in history. Yes. Yes. But not an investment. Right. Exactly. You've spoken, sat across the table with lots of founders that are trying to pitch you on fundraising. I'm sure there's a spectrum of really grounded founders to founders who will try to sell you a dream. And I'm curious if you've ever heard. And a lot of them were both. And we've invested a lot that are both. So I'm curious if you ever heard anything like this. We've talked about this on the show. This is from Sam Altman when he was talking about the NVIDIA investment. He says the stuff that will come out of the super brain will be remarkable in a way.

I think we don't really know how to think about yet. Yes. Is that, if someone came and told that to you, that what is coming, what you're investing in will be so amazing, you don't even know how to wrap your head around it? What's your reaction? I'm asking this, by the, earnestly, because like. I did have, I did have a founder a couple of years ago, several years ago, who basically said, I asked him a question. They said, I can explain it to you, but it's probably not worth my time because you probably couldn't understand it. Okay.

And I said, try me. And they said, no, I don't think, I don't think you could get it. Amazingly, we invested. And I think we made money. You invested after that? We made money. So this is a good strategy, then. Yeah, maybe it is.

Maybe it is. No, I think the, that is, hey, my ambitions are so. and my expectations I'm setting, I'm setting expectations so high, words cannot do the expectations justice, which also is another little canary in the coal mine of, I actually, maybe it's my personality, I like concrete things, like, hey, we're going to do this. We're going to be a big company and we're going to be a big company because we think we could sell a billion dollars of this product given how this world works out. And you'd be like, oh, that's big, hairy, audacious goal, but I could track that because that makes sense.

to me. When people say, we're going to be the biggest company ever because we're going to do things that your brain can't even track, that's, you know, that it feels a little bit harder track. But, you know, given what Sam has done, if anybody has earned the right to say things like that, you know, maybe him, Elon, rare air of folks who could get away with that type of comment. Definitely. I mean, there's, there's a balance here between like you can appreciate and I certainly do what Sam has done at the helm of Open AI and continues to do, even though they've lost a lot of talent, the company continues to ship. But then when you're asking this broader question of, are things a little frothy? And you see a quote like that in a story about this

$100 billion investment. That is, that's where I start to ask questions. A hundred million dollar non-investment and subs, made substantive. One of the key pillars of what's the $100 million our partnership is they're going to do things that I couldn't explain to you because you wouldn't understand. You're like, hmm, you know, that might be, that might be on the cover of a book of what I saw, what I saw at the top of the market by, you know, a writer to be unnamed in five years. Yeah, I better get pitching that one. But then we should talk about then what it means for the market, right? Because you follow, of course, the private markets, the public markets. And if you think about how much the public market is relying on Sam to do well,

Sam to deliver on that promise that he's made. Well, Sam has to do that because they're relying on Microsoft, Oracle, CoreWeave, Nvidia, they are now all relying on Open AI to deliver. And I don't even know what more, I mean, to deliver what exactly. And then you think about all those ecosystems. So the energy companies are relying on CoreWeave to build out the infrastructure. You think about, you know, all the things that Microsoft's doing that are reliant on some of the things that Open AI is doing, you know, if just nothing

else, the pure valuation that people are baking in given all the contracts or forward contracts or promises or partnerships or handshakes that are done, that it's just escalating the expectation and commitment, which again, you know, starts to make you feel a bit uncomfortable at times. Right. And I think the answer for Open AI has to be that in order to meet these enormous expectations. I just set it up. I don't know what they're building towards. That wasn't quite right. What they need to do is to automate a tremendous amount of white collar labor. So I want to talk about that and what's happening with Gen Z who's at the seems like the Spears edge of this and not not able to find jobs right now. I want to talk about that right after this.

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talent, I'd go with Indeed. Post your first job and get $75 off at Indeed.com slash tech talent. That's indeed.com slash tech talent that claim this offer. Indeed, built for what's now and what's next in tech hiring. And we're back here with Rick Heitzman. managing director of First Mark Capital. Rick, we talked before the break about how OpenAI is going to need to automate a lot of jobs in order to justify this valuation. So let's just start broad as we begin the second half here. Are we marching towards technology companies like Open AI, like Anthropic,

basically trying to automate all work, all white color work, and if they're successful, what happens? Well, I mean, I would say, automating all work, right? Because if you think about some of the robotics things that are happening now, some factory automation things that are happening now, it's both blue collar and white collar, I think maybe differently than any kind of automation going back to, you know, farming where, you know, there's bulldozers and there's steam engines that are automating blue color work. You know, this has been very different. And so I do think, and in talking to the

bankers and the lawyers who usually hire a whole lot of folks or, you know, entry-level consulting firms, BPO firms, they are pausing or taking a slower approach or a more thoughtful and cautious approach to how they fill in the bottom of the pyramid. And that makes them, you know, rethink their business. You know, I do believe that they're going to rethink their business. I think you're going to lose some people, but those people are going to be repurposed, right? So if you go back to the beginning of the 20th century. So beginning of the 20th century, about 93 people, 93% of Americans were in the agrarian economy, farmers, basically.

At the end of the 20th century, it was about 3% of the American workforce as farmers. And if you looked at just those two stats, you were like, oh, my God, something horrible must have happened. All these people must have lost their jobs. what happened. It was terrible. What happened? Oh, it was the greatest century of an economy of any civilization's economy in the history of civilization. You know, the American 20th century and everything that happened. So there is a creative destruction that I think capitalism is really good at. And I think that you saw that repurposement in the Industrial Revolution. You saw a repurposement

several times in the automation, the ability to have factories and all the technological advances during that century, I think you're going to see a rethinking about some of those things, especially around white collar work. And, you know, there's a bunch of different things that are analogous to it. You know, word processors came out and they said, I forget what it is, we call it 35 years ago, so I'll be imprecise. And they said, oh, my God, this is going to be the end of the legal industry. You know, now we're not going to need, you know, now people are going to be. able to, you know, print these documents, use WordPressers. Since the I have any word processors, there's four times more lawyers in America than there was at the time. You know,

the same thing if you think about spreadsheets. And, you know, Lotus 1, 2, 3 comes out. There's going to be spreadsheets. And they said, well, we're not going to need all these bankers. We're not going to need slide rules. We're going to have spreadsheets. We're going to automate this whole finance thing. There's more bankers than there were before spreadsheets by, you know, a huge, huge factor. So, you know, what is it going to be? Now we're able to automate a lot of white color tasks. You're able to automate basic business processes today, probably better in the medium term. And do you believe that Gen Z is going to be creative enough and entrepreneurial enough to reinvent themselves? I think so. I have confidence in that. I do feel for I have friends

who are going through recent college graduates, and it's the worst, it was the worst year last year since financial crisis for recent college graduates. I have a son who's a junior in college. He feels anxiety of, you know, what does this mean? Is AI going to take my job? So I have empathy for that, but I also push him to say, well, what could you do that AI can't do? Or what are you thinking about that's thinking about something differently? Because the best people are going to be the people who understand it a little ahead of time. And, you know, we're beginning to see people spin law firms, that their entire associate infrastructure is AI. So, you know, they're able to be the partner who's able to add that level of judgment, client interface, all those things. And their

backend is AI. And they're not beholden to the pyramid model of law firms to be able to make their business work. So you're going to see entrepreneurship. You're going to see creative destruction. I think that on the whole, we should all, we're all, almost all of us will be better off for it. You know, I really go back and forth on it because on one hand, it does seem like AI is becoming more and more capable. And again, you know, I just start in so many times in business, it's worth just starting at the money, right? Yes. The money is betting that all this, all these jobs will be automated. Yes.

That's what that money from Nvidia into open AI is, is trying to do. And then the question is what happens afterwards. And you could have, it seems like if they get there, right, in the time that Invidio wants that investment to pay back, there's going to be massive disruption. Yeah. But then you also look at what happens in the day-to-day of many companies. There's a great, thought-provoking substack post in this substack called Still Wandering, and it was called The Death of the Corporate Job. And the author was trying to track what their friends and counterparts did in their work. Here's what the author said.

I keep meeting people who describe their jobs using words they'd never use in normal conversations. They attend meetings about meetings. They create PowerPoints that nobody reads, which gets shared in emails that no one opens, which generate tasks that don't need doing. This post was liked 11,000, close to 12,000 times on Substack, which on Substack, that's a lot of, a lot of people. Which means, like, it's also funny. Yeah, but it resonates with people. Yeah, funny because it's true.

Right. Like, the fact that that resonated that way with so many people who are in the knowledge economy, it's just so telling. And maybe AI eliminates that stuff. And maybe this moment where we've had hire and consolidate or stop in many ways is a realization by companies that's going on. There's a great New York political cartoon, which is the same thing of, you know, someone types out an email and they say, you know, AI turn this into a hundred page PowerPoint presentation. And they turn it into 100 page PowerPoint presentation. and they email it to their colleague and then says, AI, take this 100-page PowerPoint presentation and turn into a short email.

Exactly. So everybody is using AI to automate different pieces. You know, I just think that, you know, to have those people who are doing writing emails that no one reads or creating decks that people only weigh but not read, I think having them not do that is better for everyone. Right. But the question is, like, what business looks like?

afterward. So there's like two possibilities. One is that all those people end up on higher value tasks. Two is companies go, oh my goodness, we need one third of the people. Yeah. And you're seeing some companies already do that. You know, some companies, Shopify increased revenue and took out a fair amount of their employee base. You're not seeing engineers go away, but you're seeing companies keep engineering flat but getting a lot more productivity due to all the coding tools. I think you're seeing a lot of kind of business process outsourcing or call centers and customer service things that are getting shrunk due to technology. So I do think there's going to be a substantive job loss in certain fields. You hope that people do some more meaningful

work than having to go. And I think we're both very fortunate that our job is not writing emails that people don't read or producing content. that people don't listen to, I hope. You're here for a good reason. We have an audience. I hope everyone out there. Yes. So I think that I think you're going to see more people doing different stuff.

I mean, part of that is the rise of the creator economy. Right. And you're seeing more people be entrepreneurial in the creator economy. And even as we've talked to folks out there in the creator economy, it's often a side gig. And sometimes either their day job is not very meaningful, not very lucrative, seems like it's a you know it's a cartoonish type thing and and they're they're finding meaningful creativity and dollars in doing the side hustle and sometimes that side hustle terms into their main job and that becomes a more meaningful

opportunity I think it's going to happen more more yeah I mean that happened to me I was started my career marketing and sales and writing freelance journalism on the side and then flip that to a full-time career and then flip that into something that's now not just writing but is audio, some TV like we talked about, which has been nice. But I actually, you know, it brings me back to my first job, which was I would put together media plans that would go through those email chains and the decks that no one would read and eventually someone would approve it or not approve it.

And of course, that process has been disrupted by programmatic advertising where you just automate it all today. So maybe that would be a new job. But I'm just thinking like that job, that entry level job that I had that got me into the workforce, you could chat GPT that and be done with it in five seconds. My first job was, you know, entry level investment banker that I was, you know, printing off documents and then keying that into a spreadsheet. You know, that's done, that's been done for years.

I mean, if you look at, you know, some of the basic capital IQ things and probably the first, you know, a couple years of my career are now completely automated due to technology. But even people who, you know, are now entering investment banker, are doing. different stuff and that's becoming more meaningful and there's more investment bankers than ever so i think although it's changing it doesn't mean it's ending and we talk about like there's a thriving economy out there somewhere and then you think about what's happening with all right two groups of people gen z yep who's really struggling like you mentioned to find jobs and also people that lose their jobs or leave their jobs are taking longer than usual to find new work what is happening

I can't all be AI. Jerome Powell recently came out and said AI might contribute to it, but we're in a slow-to-high or slow-to-fire economy. And so what is the driving force behind this economy that feels to a lot of people to be, you know, doing well if you look at the top-line numbers, but if you're an individual trying to, you know, navigate your career path, feels like everything is just stuck. I agree with almost everything you just said. I think that the economy is very strong and the fundamentals are strong.

And we see it in both our enterprise and consumer companies. So we actually feel good about the economy. The second piece of that is I do believe that, you know, companies are slow to hire. And I think, you know, coming off of, which was a massively inefficient COVID time, spurred by low interest rates, low cost to capital, work from home, it was basically the perfect way to create an efficiency. That no accountability for dollars and no accountability for performance. so coming out of that companies now even five years later are saying okay i'm not going to i'm not going to do the sin i had yesterday i mean that's companies like individuals are always reactionary

to the last phase so you know companies like individuals are always reactionary to the last phase or their last mistake um so i think companies are now thinking about all right how are we more efficient how do we make sure that we're spending that time and money wisely and we're not hiring someone to write emails that no one reads. So I think that's been slower. But at the same time, unemployment remains low. And, you know, there is a sense of, you know, when I was coming out of school, that there is some time.

Like, they told us when we were in school. Like, if you quit your job or you lose your job, you need to have a little bit of time because it takes months to find a new job, you know, in some of the boom times. human capital has been tight over the last 20 years, it's taken hours to find a new job. So I think that you're moving more to historical norms as people are, maybe because the economy's doing well, maybe because the market's doing well, because the managers are being more performance driven, are moving more towards historical norms around performance. Okay.

I want to use our remaining time to lightning round through a couple of your investments. You've invested in some fascinating companies. Thank you. Thank you. I use all the time. Great. Use them more. So let's just go through four of them.

If we can, we have about eight minutes. Great. Discord. Yes. What do you think about the fact that so much of the dynamism of social media has moved private, right? Mark Zuckerberg had this pivot to privacy. Everyone's like, he's into encryption. It's like, no, he realizes social sharing is happening in the group chat.

Yes. And that's where he wants things to happen. So talk a little bit about that. And moving to Discord servers, right? And is that good for us, basically? Well, somewhat is, somewhat it is. I mean, I don't think everybody, you know, the old joke, you know, you don't have to broadcast anyone, everybody you ever met what you had for lunch.

That's not pushing forward anybody's life or economy and you don't need to see a picture of the tuna sandwich. So that's, I think I'm somewhat glad we're out of that phase of social media. At the same time, you know, therefore having servers that are very specific. whether you're in a Discord server for the next World Baseball Champion New York Yankees or whether you're in it for, you know, a League of Legends clan, you know, all of those things you find that they're there. You know, the negative, as we've talked about are these are very, some of them are very intense

echo chambers around particular beliefs that can spin people up. So I think there is, I think Discord does an excellent job of moderation to make sure that, you know, there's the right level of discourse in those Discord servers and to make sure that works but that's on the administrator of the discord it's on the administrator of this of the server so uh that is true but i think you're going to see um you're going to see more more social media move to semi-private that look more like group chats and it can be around you know sports or music or technology or relationships uh just because i think that people might might be a little bit over we're living in public.

Yeah. We love Discord over here, Big Technology. We have a private Discord server for our paying subscribers. So if you're interested, scroll down, sign up, and we'll get you a link. And I think it's the best thing that Big Technology has done in years. That's awesome. The conversation is high quality. It's interesting.

And I love being in there. I get a lot of value out of it. Yeah. And curation has been, you know, for the last 10 years of social media after the initial explosion, curation has been the most important thing in the keeping a good thriving community. All right, Draft Kings. Yes.

Did Shohay Otani actually bet on baseball or was it his interpreter? I do not know that. Do not know. I'm not sure if they would tell me if I asked, I think, what do I think or what does Draft Kings think? Let me ask it in a little bit less facetious way. Obviously sports betting's been popularized.

Yes. The leagues all promote it. Yes. The players are getting into it. Yes. Is that a problem? Well, you're seeing more and more investigations and suspensions around the use and misuse of gambling. So I think, you know, like any new technology, it explodes out of the gates. It's a little bit of the Wild West.

I think, you know, Draft Kings being a large public company who is a leader probably has more guardrails around it than maybe prediction markets or some of these, you know, sweepstakes type's gray area. markets. I think, you know, the government always struggles to keep up with where technology is going and is oftentimes focused on yesterday's problem, not tomorrow's problem. So I believe there's going to be more clearer rules around, especially players, coaches, umpires managers and what they're able to do on either gambling or prediction markets. Okay, let's talk about Shopify. Yes. You're an investor in Shopify. I am. Is all online commerce? going to go from applications and websites to into chatbots. And if so, what happens? So I think that that's, I don't think all, it's never all or nothing. So I think you're going to

move to more chatbots. I think you're going to still need an ecosystem of whether it's, you know, headless stores or whether it's a back end infrastructure of you're still, whether you're buying a sweater because your AI girlfriend tells you it looks good and you're buying a chatbot based on your AI girlfriend's recommendation. That's why I usually make most of my purchases. Yes, yes. Your AI girlfriend is your stylist. That's it. That'd be a good t-shirt for my AI girlfriend pick this out for me. That'd be great. So, you know, so but you know, there still needs to be a t-shirt, which needs to be in a warehouse, which needs to go in an envelope, which needs to ship to you. There needs to be a payment process. There needs to be fraud around that payment. So I think the

commerce infrastructure is not going to go away regardless of who initiates that transaction. And, you know, whether you're, you know, getting that T-shirt on T-Spring versus your AI girlfriend chatbot versus, you know, the gap, it's all going to happen. So I don't, I think it's somewhat disruptive on the front end, more to customer acquisition and, and the front end of stores. But I think the commerce infrastructure is only going to continue to grow. And I don't see any way that e-commerce is going to slow down any foreseeable time. Right. So the interface might be a chap up, but everything could be managed. Everything you're managing. You're still going to. Yes. You're still that, again, you know, every, just all those little pieces of flows of transaction processing and fraud prevention and, you know, where that goes. And is there a return? And if you say, hey, you're breakup with your AI girlfriend and you don't want that T-shirt anymore. Can you return it? There's all, there's a lot of things that have to happen besides just the front end store. I think Shopify, since we invest in the series A has built out. whether individually or through their ecosystem,

all kinds of things that are very hard to replicate. Okay. And then finally, Airbnb. Okay. Is New York, is New York's decision to ban Airbnb the greatest own goal in municipal history or something close to it? What do you have the greatest own goal? I thought just a terrible shoot yourself.

There was a great quote. So let me, let me. Oh, own goal. It's own goal. Like when you kick it into your own net. soccer. I just heard a quote from a Jets player yesterday. He's like, other teams shoot themselves in the foot. Yeah. And then we shoot ourselves in the head. Yeah. Yeah. So, sorry. I just didn't catch it. So I asked a question and I'll respond to that again. Was, okay, you invested in Airbnb.

Yes. Was New York City's decision to ban Airbnb one of the greatest disasters in municipal government history? Yeah. I mean, it's definitely an own goal. If we want to use that format, that, you know, you want to have a great fiber and ecosystem that allows free trade, allows people to stay in places, but and you want very little regulatory capture. If you want a fervent place for, you want New York to be open for traveling business people, for tourism, for everything that happens. And you don't want the regulatory capture from the hospitality and hotel industry. So I think that's, it was silly.

I think a lot of the large municipalities have played with it. But I think in the, you hope in the long run, cooler heads prevail and everybody winds up doing the right thing. I understand the concerns that the rents might be too high and you don't want to have residential properties being converted into hotels. But there has to be a balance and the fact that it just got banned, you know, effectively turned a hotel stay in New York City from something that was affordable. So if you had guests, for instance, into something that's now $700 a night. And that drives me nuts. And it's not like people are, they should fix the underlying problem. You're right. There's a housing issue in New York City. There's also a hotel rev par issue. So you need to be able to do both. You hope that by providing incentive, you could get people to do that. And whether it's incentive that, hey, we're limiting the regulatory boundaries to get housing permits to be able to build more housing, especially affordable housing, or you're doing things to open up to make it easier for people to build any type of residential properties here. That should have been the goal and not trying to,

not trying to do regulatory capture. All right, Rick, you have, First Mark has a podcast. Do you want to talk a little bit about if people are interested in our conversation today where they can follow you or the podcast? Sure. Shout it out. So we do a bunch of different podcasts. You know, you can follow me, simple X address of just at Rick.

At Rick. If you want to. When did you get that? It's a long, long story. That's probably for phase, for chapter two of our conversation. So I'm at Rick on Twitter X. You can find me there. I actually have a very clean and deliberate Twitter largely about what I think is going on in the markets

and what we're seeing and hopefully to be more clear about that. And then, you know, First Mark, we have a full parade of podcasts you should follow at First Mark Cap on Twitter and Instagram, but also my partner Matt has a very large podcast called Data Driven, which talks about what he calls the Mad Landscape, Machine. learning, artificial intelligence and data, and that's really been on the forefront of AI with some of the best thinkers in AI on over the last actual decade. So I think we do produce a lot of content around data, around financial technologies, around a lot of things we do, even OK computer that's part of the risk reversal ecosystem about what the state of the private markets are.

So find me any of those places as well as on our friend Scott Wapner's closing bell on CNBC. Which you're about to go to so we'll get you to set. Rick, great to see you. Thanks for coming on the show. This was awesome. Thank you very much. I'm happy to be back anytime. Definitely. All right. We'll have to get the story of at Rick. So we will have you back for that and much more. All right, everybody. Thank you so much for watching. And we'll see you next time on Big Technology Podcast.