Where Are The AI Startups? — With Rick Heitzmann

15 Oct 2025 · 59 min

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Big Technology Podcast: Episode Summary

Episode Title

Where Are The AI Startups? — With Rick Heitzmann

Host

  • Alex Kantrowitz - Silicon Valley journalist

Guest

  • Rick Heitzmann - Founder and Managing Director of FirstMark Capital

Episode Overview In this episode, Heitzmann discusses the current landscape of AI startups, the impact of dominant players like ChatGPT, and the future potential of AI innovations. The conversation touches on the challenges faced by new startups, the economics of AI investing today, and the implications of data privacy concerns in the AI sector.

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Key Discussions

The Current State of AI Startups

  • Lack of Individual Startups: Heitzmann highlights the absence of a wave of new AI startups, questioning why the market is not seeing a proliferation of applications building on generative AI technologies.
  • Dominance of Major Players: The success and rapid development of OpenAI and ChatGPT have set a high bar, making it difficult for smaller startups to compete.
  • Specific Solutions: While there are some niche players like Harvey (legal tech) and Evolution IQ (insurance), the broader consumer AI applications have lagged.

Challenges for New Entrants

  • Data Requirements: Startups need robust, specific datasets to build effective AI solutions, which poses a significant barrier to entry.
  • Regulatory and Compliance Issues: Certain sectors, like health tech, require discrete applications due to regulatory constraints, which complicates the startup landscape.

Investment Landscape

  • Venture Capital Sentiment: Heitzmann expresses frustration at the lack of investment in sustainable startups that can differentiate themselves from generic AI applications.
  • Future of Funding: The episode discusses whether the frenzy of funding in AI will pay off and whether the application layer is investable.

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Economic Implications of AI

  • Automation of White-Collar Jobs: The discussion covers the potential for AI to disrupt various job sectors, particularly in white-collar roles, and how companies are adjusting hiring practices in response to AI capabilities.
  • Historical Perspective: Heitzmann draws parallels to past technological revolutions, arguing that while certain jobs may diminish, new opportunities will arise as the economy adapts.

Consumer Behavior and AI

  • Shifts in Social Media and Commerce: The episode examines how social media dynamics are shifting towards privacy and smaller community interactions (e.g., Discord) and how commerce might increasingly involve chatbots for customer engagement.

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Entrepreneurship and the Future

  • Gen Z and Innovation: Heitzmann expresses confidence in Gen Z’s entrepreneurial spirit and adaptability, suggesting that they will find new paths despite current job market challenges.
  • The Role of Creatives: As traditional roles evolve, there’s an emphasis on the rise of the creator economy, enabling individuals to pursue meaningful work beyond conventional corporate roles.

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Key Takeaways

  • The landscape for AI startups is complicated by the dominance of established players and the necessity for unique, specific datasets.
  • Investment in AI is high, but the future of application-level startups remains uncertain as innovators try to differentiate themselves.
  • Automation will reshape job markets, but historically, economies adapt, creating new opportunities even as old roles fade.
  • Gen Z's adaptability and the rise of the creator economy may lead to new innovative ventures that leverage AI.

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Conclusion Heitzmann's insights into the AI startup ecosystem offer a nuanced understanding of the current challenges and future possibilities in the tech landscape. As companies navigate a rapidly changing environment, the role of innovation and adaptability becomes paramount.

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For more insights on technology and AI, tune into Big Technology Podcast and explore episodes featuring key industry figures and discussions.

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Transcript

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0:00Where are the AI startups? Are they actually coming or will chat GPTGPT gobble it all? We'll talk about it with Rick Heitzman of 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 in value. advanced, intuitive, and deployed. That's how they stack. That's technology at Capital One.

0:41Welcome 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.

1:16Rick, 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 CNBC. 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?

1:50Of 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 ChatGPT, 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 an 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. 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.

2:28First of all, I think OpenAI and ChatGPT have done a great job of making a very good product that has both breadth 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, OpenAI has done an excellent job of not being any of those things, hiring great people, continuing 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.

3:05So a lot of the training data in general consumer is general broad-based web. And obviously, you're seeing litigation around who's training what 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 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.

3:49But 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, answer is Fort Charles. but if you're trying to find those things and I'm not available on a podcast 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 and their ability to invest along those lines right by the way Harvey Henry I'm sensing a trend here there's a trend there yeah is it the new.ly you just take a random guy's first name I think so it's easy to say easy to pronounce we'll see there was Blue Nile and there was Amazon and there was a bunch of things in the 90s, maybe this is the thing.

4:32These things go in waves. There are meetings. 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 meals 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.

5:05And it's something I know it's not just me. Many people have been using Chai Chi PT 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 2000 calories a day, or I want to eat whole foods. And then you can upload photos. I 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 ChatGPT... ChatGPT is a really good product. Absolutely. It's a really good product that has breath. And, you know, so it's solving your problem.

5:40But this is my question then from your perspective. Are we about to see a wave of consumer startups that never happen? 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, 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 Chachipa? We've seen a lot. We've seen nutritionists. We've seen a bunch of different things that have come out. So I would say there's buckets of do you need a discrete application or you don't need a discrete application.

6:15Certain 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 rappers 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.

6:55And 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're 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 ChatGPT has made that more difficult than ever. Yeah. And it's very interesting because OpenAI recently released data.

7:32And of course, it's coming from OpenAI. But data about how people use ChatGPT, we've talked about it here on the show. And the number one use that people go to it is for practical guidance. And let's just do a thought exercise. If there was no chat CPT 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.

8:05If they came to you and said, we have a natural language fitness coach, if they came to you and said, we have, uh, you upload, uh, photos or videos 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 financeable, very, 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 uh 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 llm 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 You know, we talk about Harvey, right, which is, again, this is legal AI that knows the laws, knows the rules, has these big context windows.

9:11So you can go to it for like legal advice or a lawyer would use it 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 in the state. Yes. Upload it into the context window. Download the specifics of the case, upload it into the context window, and maybe get close to as good as Harvey is.

9:48Yeah. I mean, and that's a very specific thing on a case where you might need a specific attorney. If you think about probably 80%, unfortunately not a lawyer, but probably 80 % of all legal work is, this is Rick, he needs a will. This is – 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 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?

10:25And the argument that I'm making or trying to tease out here is, does all this stuff end up just happening within the ChatGPT 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 even more applicable coaching, fitness, search. It's all going to happen within these broad, multi-general purpose bots.

11:05And so then I like throw my hands up and say, well, what's going to happen? Like what's going to happen to startup founders and investors? Lawyers. What's going to happen? Podcasters. But no, but really in terms of the economic activity. We are going to get to jobs, but the economic activity is interesting. So there's probably two pieces, and one is slightly red teaming. It is, all right, so can Chad GPT be better at everything than everybody? Probably not. There's going to be limitations. If you ask him Altman, he'll say yes. And then there's an asymptote where, you know, are the latest models the best models?

11:40And are you still seeing even a step function improvement in Chad 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 OpenAI or ChatGPT? And we're investors in a couple of companies that do data security. What data are you sharing with what models? Are they staying inside your environment?

12:21Are we making sure that all our pieces of that data are not leaking out into a model or into another part of that ecosystem? system. So if you have a private walled garden of your data, your model, and your security, will that be better? Because it's more specific to you even on a personal basis, if you're talking about your relationship or where you're going on vacation or your finances or your will, or on an enterprise basis. So 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.

12:59I want to make sure that that's confidential. So are people going to get scared no differently than they become suspicious of other large companies? Are they going to become overly suspicious of OpenAI, ChatGPT, 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, all of those pieces. I think we're maybe not even in the first inning.

13:39Yeah, we just did a podcast with Eno Enkostika, the co-founder of Wiz. Yes. And 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. Yes. 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 if I should call it traditional technology investment place where you would see a generative AI startup like a startup?

14:19Let 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.

14:56And sometimes they use it within their own walled garden. So I want to have all my leases historically, and therefore I want to understand all my leases across all of my Starbucks franchises. All right, well, getting very specific lease data is going to be very much different than getting generic answers from 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 of maybe even collaboration or a co-op database that makes that more sustainable in the medium or long term.

15:45So 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. Yes. 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 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.

16:23And now you have large language models that are like doing just as good or 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 getting a chance to get this advice from the specialists, instead of going to these apps that we've seen 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.

17:03Well, 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 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 dietician. I'm going to use the back end of ChatGPT 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 ChatGPT, though. It probably made that reservation for you. It probably knows what the menu is and knows what your goals are and how to do it.

17:36But 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 add? So your discrete value add as a human is 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.

18:16Or 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 chatbot knows that you're tired because it's plugging your Whoop data or it knows that 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 to staying just ahead of that technology and understand where they could create unique and discrete value on top of technology.

18:52Yeah, I think that's going to be tough. 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.

19:27And 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 really good. It's pretty clear. and now people are engaging and I'm sure you read about it all the time, more and more meaningful relationships where everyone could tell what was AI-generated advertising or AI-generated video or even AI-generated actress and 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.

20:24Yeah, there are 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 are some amazing applications we've talked about on the show here. There's – in Korea, there is like a stuffed animal with an LLM baked in. Yes. That's like hanging out with elderly people who are lonely, 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 animal says, I'm done taking my meds, then they send a message to the nurse.

21:01Or I don't know or it's like the nth degree of I fall and I can't get up that all these things. And, you know, it started off very simplistically. I'm going to send a text at eight o 'clock every morning, making sure that this elderly person took all five of their meds and, you know, maybe had to ask them it. 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 if we're ready to, you know, there's always the dark side, which you touched 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 getting that good that quickly.

21:58And 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 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. 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 um you know are going to be out there uh 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 what 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 too hard on them.

22:49They stopped talking to me. Now I'm a little more sycophantic. They're losing weight lower. I'm sorry about that. You could have had the stake. 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 the tech industry or investors are putting too much money 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.

23:26I mean what's been very clear is all the hyperscalers 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 a VC during that last time in the late 90s. Those markets were largely reliant on external capital, right? If you were building out a CLEC or if you were building out 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 build out.

24:14The 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$100 million in energy for my data centers, and I'm just going to take 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 in hand asking for capital.

24:55So 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 build a railroad to nowhere because that doesn't make sense anymore. or despite where the hype was in the market. 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 egos, market caps, and dollars involved, I think that would be too hard to do.

25:41So just give us some context here. Do you know off the top of the head the largest check that FirstMark has put into a company? Or can you 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 in certain years of all venture capital. 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$100 billion in a company? Do you need to get a trillion dollars at least back in return?

26:24Well, it depends on who you are and that kind of goes to the recycling or the circularness of some of these things. Obviously, the OpenAI, Microsoft or OpenAI Oracle goes back to the OpenAI Oracle deal. And 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.

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27:05But – and then also, you know, NVIDIA is worth so much money that, you know, Jensen can 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. You know, and, you know, not that long ago,$100 billion was greater than the market cap of all but a few companies. So the numbers are so mind-blowingly disproportionate, it's hard to really contextualize them. Right. And we should say, again, with many open AI investments, it's kind of funny math, at least to the beginning. It's$10 billion to start with plans to contribute another$90 billion in increments.

27:49And the best part of – one of the good parts of open AI being private is they could do a lot of these deals. Right. Where they don't have to be disclosed, obviously, because NVIDIA is public. They're going to have to disclose that or Oracle or whatever it is that they're able to put up great top line numbers, no different than maybe AOL did in the late 90s of, hey, here's 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.

28:30We'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 a 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. Yes. I'm curious if you've ever heard. And a lot of them are both.

29:09And we've invested a lot that are both. So I'm curious if you've 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 way, earnestly. I did have a founder a couple of years ago, several years ago, who basically said, I asked him a question.

29:45He 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 you could get it. Amazingly, we invested. You invested after that? We made money. So this is a good strategy then. Yeah, maybe it is. Maybe it is. No, I think that is, hey, my ambitions are so broad 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.

30:27We'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 feels a little bit harder to 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.

31:02Definitely. I mean, there's a balance here between like you can appreciate and I certainly do what Sam has done at the helm of OpenAI and continues to do even though they've lost a lot of talent. Yes. The company continues to ship. But then when you're asking this broader question of are things a little frothy? Yes. And you see a quote like that in a story about this$100 billion investment. That's where I start to ask questions. $100 billion or non-investment made substantive. One of the key pillars of the$100 million partnership is they're going to do things that I couldn't explain to you because you wouldn't understand.

31:39you're like, hmm, that might be on the cover of a book of what I saw at the top of the market by 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 - Because you have Microsoft, Oracle, CoreWeave, NVIDIA. They are now all relying on OpenAI to deliver. And I don't even know what more, I mean, to deliver what exactly.

32:20And then you think about all those ecosystems. So the energy companies are relying on CoreWeave to build out the infrastructure. You think about all the things that Microsoft's doing that are reliant on some of the things that OpenAI 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 are done, that it's just escalating the expectation and commitment, which, again, you know, starts to starts to make you feel a bit uncomfortable. Right. And I think the answer for OpenAI has to be that in order to meet these enormous expectations, I just set it up.

33:01I 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 spear's edge of this and not able to find jobs right now. I want to talk about that right after this. Shape the future of enterprise AI with Agency. A-G-N-T-C-Y. Now an open source Linux Foundation project, Agency is leading the way in establishing trusted identity and access management for the Internet of Agents, a collaboration layer that ensures AI agents can securely discover, connect, and work across any framework.

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37:12So let's just start broad as we begin the second half here. Are we marching towards technology companies like OpenAI, like Anthropic, basically trying to automate all work, all white collar 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 farming where there's bulldozers and there's steam engines that are automating blue collar work, you know, this has been very different.

37:54And 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.

38:37At 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'd be 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 a creative destruction that I think capitalism is really good at. And I think that you're, you're seeing, you saw that repurposement in the industrial revolution.

39:17You saw a repurposement several times, uh, in the automation, the ability to have factories and all the technology, 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, um, 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. Now we're not going to need, people are going to be able to print these documents, use word processors.

39:51Since the I have been in word processors, there's four times more lawyers in America than there was at the time. The same thing if you think about spreadsheets and 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 a huge, huge factor. So, you know, what is it going to be? Now we're able to automate a lot of white collar tasks. You're able to automate basic business processes today, probably better in the medium term.

40:26And 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, I think it was the worst year last year since the 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?

41:06Because the best people are going to be the people who understand it a little ahead of time. And we're beginning to see people spin out law firms that their entire associate infrastructure is AI. So they're able to be the partner who's able to add that level of judgment, client interface, all those things. And their back end 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, 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.

41:54And 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 these jobs will be automated. Yes. That's what that money from NVIDIA into OpenAI 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 NVIDIA wants that investment to pay back, there's going to be massive disruption. But then you also look at what happens in the day-to-day of many companies. There's a great – a thought-provoking substack post in this, substack called Still Wandering.

42:28And 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 people. Which means like – It's also funny. Yeah, but it resonates with people.

43:04Funny 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 hiring consolidate or stop in many ways is a realization by companies that's going on. There's a great New Yorker political cartoon, which is the same thing of someone types out an email and they say, AI, turn this into a 100-page PowerPoint presentation. and they turn it into a 100-page PowerPoint presentation and they email it to their colleague and then says, AI, take this 100-page PowerPoint presentation and turn it into a short email.

43:40Exactly. So everybody is using AI to automate different pieces. I just think that to have those people who are 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.

44:25You'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 will do some more meaningful work than, you know, 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.

45:05You're here for a good reason. We have an audience. I hope. Everyone out there. Yes. So I think that 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, or seems like it's a cartoonish type thing. And they're finding meaning, creativity, and dollars in doing this side hustle. And sometimes that side hustle turns into their main job, and that becomes a more meaningful opportunity.

45:49I think it's going to happen more and more. Yeah. I mean, that happened to me. I started my career in 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 video, audio, some TV like we talked about, which has been nice. But 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.

46:25So 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 to that and be done with it in five seconds. My first job was an entry level investment banker that I was printing off documents and then keying that into a spreadsheet. That's been done for years. I mean, if you look at some of the basic capital IQ things and probably the first couple years of my career are now completely automated due to technology. But even people who are now entering investment banking are doing different stuff and that's becoming more meaningful.

47:03And 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 two groups of people, Gen Z. 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? It can't all be AI. Jerome Powell recently came out and said AI might contribute to it, but we're in a slow-to-hire, slow-to-fire economy. And so what is the driving force behind this economy that feels to a lot of people to be doing well if you look at the top-line numbers, But if you're an individual trying to navigate your career path, it feels like everything is just stuck.

47:51I 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 companies are slow to hire. And I think coming off of, which was a massively inefficient COVID time, spurred by low interest rates, low cost of capital, work from home, it was basically the perfect way to create inefficiency. That no accountability for dollars and no accountability for performance. So coming off of that, companies now, even five years later, are saying, okay, I'm not going to do the sin I had yesterday.

48:36I 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. 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 there is a sense of 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.

49:21You know, in some of the boom times when 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 is doing well, maybe because the market is doing well, maybe because the managers are being more performance driven. They're 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. Ones that I use all the time. Great. Ones that we talk about.

49:54Use 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. And that's where he wants things to happen. So talk a little bit about that. So I think in moving to Discord servers, right? And is that good for us, basically? Well, somewhat it is. I mean, I don't think everybody, you know, the old joke, you know, you don't have to broadcast to anyone.

50:33Everybody you ever met, we 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 and 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.

51:11So I think there is – I think Discord does an excellent job of moderation to make sure that 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 the server. So that is true. But I think you're going to see more social media move to semi-private that look more like group chats. And it can be around sports or music or technology or relationships just because I think that people might be a little bit over living in public. Yeah. We love Discord over here, big technology. We have a private Discord server for our paying subscribers.

51:58So 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. Conversation is high quality. It's interesting. And I love being in there. I get a lot of value out of it. 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 keeping a good thriving community. All right. DraftKings. Yes. Did Shohei 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.

52:36I think, what do I think or what does DraftKings think? Let me ask it in a little bit less facetious way. Obviously, sports betting has 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, DraftKings 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 types, gray area markets.

53:20I 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.

54:02I 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. You're still, whether you're buying a sweater because your AI girlfriend tells you it looks good and you're buying it in 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 would be a good T-shirt. My AI girlfriend picked this out for me. That would be great. So, 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 be shipped to you.

54:38There 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 whether you're getting that T-shirt on Teespring versus your AI girlfriend chatbot versus the gap, it's all going to happen. So I think it's somewhat disruptive on the front end, more to customer acquisition 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 in any foreseeable time. Right.

55:16So the interface might be a chatbot, but everything could be managed. Everything can be managed. You're still going to – yes. You're still going to – again, just all those little pieces of flows of transaction processing and fraud prevention and where that goes. And is there a return? And if you say, hey, you break up with your girlfriend and you don't want that T-shirt anymore, can you return it? There's a lot of things that have to happen besides just the front-end store. I think Shopify, since we invested in the Series A, has built out, whether individually or through their ecosystem, all kinds of things that are very hard to replicate.

55:51Okay. And then finally, Airbnb. Okay. Is New York's decision to ban Airbnb the greatest own goal in municipal history or something close to it? What do you mean by the greatest own goal? I thought just a terrible, shoot yourself. There was a great quote. Let me. let me uh it's own goal like when you kick it into your own net in soccer i just heard a quote from a 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 it's like sorry yeah great so sorry i just didn't catch it so when i ask the question again 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.

56:39Yeah. I mean, it's definitely an own goal. If we want to use that format, that you want to have a great vibrant ecosystem that allows free trade, allows people to stay in places, but you want very little regulatory capture. If you want a fervent place for 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 hope in the long run, cooler heads prevail and everybody winds up doing the right thing.

57:20I 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 REVPAR issue. So you need to be able to do both. You hope that by providing incentive, you could get people to do that.

57:54And 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 do regulatory capture. All right, Rick. First Mark has a podcast 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 can follow me.

58:29Simple X address of just at Rick. At Rick. When did you get that? It's a long, long story. That's probably 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 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.

59:14And 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 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 at 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.

59:45Definitely. 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. Thank you.

From the publisher

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.

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