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- [00:00]
A
Where are the AI startups? Are they actually coming or will ChatGPT gobble it all? We'll talk about it with rick Heitzman of FirstMark 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 chat bots, 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 firstmark Capital and he is here with us in studio today to talk all about it. Rick, welcome to the show.
- [01:18]
B
Thank you, thank you for having me, a longtime listener, first time guest, so it's always exciting.
- [01:22]
A
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 or right after. So today we actually have some time to speak with each other one on one.
- [01:31]
B
I'm usually your opening act or the other way around.
- [01:34]
A
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 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?
- [02:17]
B
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. First 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, 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 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 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, the answer's for 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 chatgpt 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.
- [04:16]
A
Right. By the way, Harvey, Henry, I'm sensing a trend here.
- [04:19]
B
There's a trend? Yeah.
- [04:20]
A
Is it the new Ly? You just take a random guy's first name?
- [04:24]
B
I think so. It's easy to say, easy to pronounce. We'll see. I mean, there was Blue Nile and there was Amazon and there was a bunch of things in the 90s.
- [04:31]
A
Maybe this is the thing in waves there.
- [04:33]
B
Yes.
- [04:33]
A
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 were, 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 ChatGPT 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 ChatGPT, ChatGPT is going back to.
- [05:32]
B
It's a really good product.
- [05:34]
A
Absolutely.
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B
It's a really good product that has breadth and, you know, so it's, it's solving your problem.
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A
But 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, 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 ChatGPT, we've seen a lot.
- [06:06]
B
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? You don't need a discrete application. Certain things for a bunch of different reasons, including regulatory and compliance in areas like health, 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 is something ChatGPT 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 ChatGPT that are maybe a little bit better at travel. They might be a little bit better at being your math tutorial, 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 multibillion dollar outcome that was vertical search for travel. And 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 ChatGPT has made that more difficult than ever.
- [07:29]
A
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 ChatGPT. We've talked about it here on the show and the number one use that people go to it is for practical guidance.
- [07:40]
B
Yes.
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A
And let's just do a thought exercise. If there was no ChatGPT and no broadly available generative AI technology. So think about it, you can't license an LLM.
- [07:52]
B
Yeah.
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A
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, you upload photos or videos of your soccer practice and we'll talk to you about positioning and form, each one of those ideas, to me sounds like they would be like billion dollar ideas, right?
- [08:22]
B
Yeah, Very financeable, very. If maybe not billion dollar ideas, and 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 not that different. Right. Law is a huge, huge pool of knowledge that you put certain rules around it. Historically, they just thought that was a thought exercise. And rules today we could call it LLM. And then that produces better, faster, cheaper results of how to be more efficient in your life or job.
- [09:02]
A
I mean, even Harvey, we talk about Harvey, right? Which is, again, this is his legal AI that knows the laws, knows the rules, has these big context windows, so you can go to it for 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 figure 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.
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B
Yes.
- [09:42]
A
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.
- [09:49]
B
Yeah, 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, you know, here is a first mark company that's going through a series A financing. Could 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.
- [10:23]
A
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 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 you know, even 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 startup founders and investors, lawyers, what's going to happen?
- [11:15]
B
Podcasters.
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A
But no, but really in terms of the economic activity. But we can get to, we are going to get to jobs, but the.
- [11:21]
B
Economic activity is probably two pieces and someone is slightly red teaming is all right. So can chatgpt be better at everything than everybody? Probably not. There's going to be limitations.
- [11:33]
A
You ask Sam Altman, he'll say yes, yes.
- [11:35]
B
And then there's an asymptote where you know, are the latest models the best models and are you still seeing even a step function improvement in ChatGPT conventional wisdom is probably not. You're saying 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 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, 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. Or here are all my returns for my funds. I 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?
- [13:22]
A
I mean, I would imagine security is like a highly investable place here.
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B
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.
- [13:39]
A
Yeah. We just did a podcast with Enon Costica, the co founder of Wiz.
- [13:43]
B
Yes.
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A
And was just sold to Google for 32 billion.
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B
Biggest venture outcome ever.
- [13:47]
A
Ever. Yes, for now.
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B
For now.
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A
And we had comments coming in being like, you need to speak about this more often.
- [13:55]
B
Yes.
- [13:55]
A
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 are certain specific enterprise use cases elsewhere. Is there any would. Is there anywhere like on a consumer or. I don't even know if. 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.
- [14:23]
B
Of it, that you would invest on the application layer, I assume.
- [14:26]
A
Yes.
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B
Yeah. So on the application layer, we do, I think we like the enterprise space where 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 OpenAI models. So that 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 and 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.
- [15:54]
A
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.
- [16:04]
B
Yes.
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A
And I think that's kind of nice. Like one of the nice parts, like take the fitness example that I. 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. And now you have large language models that are doing just as good or not just as good, almost as good. 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, 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.
- [17:04]
B
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 pick a number in between. And. 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 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.
- [17:29]
A
So does ChatGPT, though. So it probably made that reservation for you.
- [17:32]
B
It probably made it. And 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 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. Like, 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, you know, you ate salmon the last two nights or whenever 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 chatbot knows that you're tired because it's plugging in 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.
- [18:52]
A
Yeah, I think that's going to be tough. Maybe I'm.
- [18:55]
B
I have confidence in the humans.
- [18:57]
A
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, but it's getting close enough to make the questions relevant.
- [19:12]
B
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. I'm not sure 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. Pretty clear. And now 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 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 are can adjust their mindset or think about creating value to stay ahead of the curve.
- [20:25]
A
Yeah, 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's some amazing applications we've talked about on the show here. There's in Korea there is a stuffed animal with an LLM baked in 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 LM stuffed animal says I'm done taking my meds. Then they send a message to the nurse.
- [21:01]
B
Yes, or I don't know or you know, it's like the nth degree of I 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 is took all five of their meds and you know, maybe they had to ask them. 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. Yeah, I'm not sure if we're ready to stay. 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. And what's the unintended consequence of something getting that good, that quickly?
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A
And as an investor, is that something that you want to touch or you're.
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B
No, we're looking, we're spending a lot of time, I think, you know, AI companionship is an incredible thing and 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 your friend who could be. 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 chatgpt, 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 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.
- [22:45]
A
Or it will adapt because you're going to give it numbers and it will be like, oh, I was too hard on them. They stopped talking to me. Now I'm a little more sycophantic. They're losing their mind.
- [22:54]
B
Sorry about that. You could have had the steak. French fries aren't the end of the world and you earned a cheat day.
- [23:00]
A
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 the tech industry or investors are putting too much money into AI. It sounds inconsistent, but I think it could both be true.
- [23:22]
B
Because I think they both could be true. It's hard to say what too much money is. What's been very clear is all the hyperscalers are investing as much as they possibly can, maybe even differently than probably prior times in history. And the two ones I've seen cited the most are or the railroads and then the infrastructure of the Internet. 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. 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. 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 $100 million in energy for my data centers. And I'm, 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, 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. 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'd be too hard to do.
- [25:41]
A
So 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.
- [25:49]
B
You give us a ballpark, $200 million.
- [25:51]
A
Okay. Jensen just committed or recently committed $100 billion to OpenAI one day, one check.
- [26:00]
B
I mean, it's more than, you know, more than what's been a couple years, certain, certain in certain years of venture capital, of all venture capital.
- [26:07]
A
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?
- [26:13]
B
Yes.
- [26:14]
A
What do, what do you have to, to get? If you invest 100 billion in a company, do you need to do you need to get a trillion dollars at least back in return?
- [26:24]
B
Well, it depends on who you are and that kind of goes to the recycling or the circularness of some of these things. And obviously the OpenAI Microsoft or OpenAI or goes back to the OpenAI Oracle deal. And you know, I'm going to, 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 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 then. Also, Nvidia is worth so much money that. But Jens 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. Not that long ago, $100 billion was greater than the market cap of all but a few companies. The numbers are so mind blowingly disproportionate, it's hard to really contextualize them.
- [27:38]
A
Right. And we should say again, with many OpenAI investments, it's kind of funny math, at least in the beginning. It's 10 billion to start with. Plans to contribute another 90 billion in increments.
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B
The best part of one of the good parts of OpenAI being private is they could do a lot of these deals 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 a very frothy market of hey, we're not talking about actual financial metrics or actual GAAP revenue or actual cash on the barrel head. We're talking about a theoretical milestone based, broader in cash in kind, dollar amount, which might not be real dollars.
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A
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.
- [28:48]
B
Yes, yes, but not an investment.
- [28:51]
A
Right, Exactly. You've spoken sat across the table with lots of founders that are trying to pitch you on. 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.
- [29:08]
B
And a lot of them were both, and we've invested a lot that are both.
- [29:11]
A
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 superbrain will be remarkable. In a way I think we don't really know how to think about yet, is that if someone came and told that to you, 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.
- [29:39]
B
Because I did have a founder a couple years ago, several years ago, who basically said, I asked him a question. He said, I can explain it to you, but it's probably not worth my time because you probably couldn't understand it.
- [29:50]
A
Okay.
- [29:52]
B
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 you invested. After that, we made money.
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A
So this is a good strategy, then.
- [30:03]
B
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 of 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. But 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. It feels a little bit harder to track. But given what Sam has done, if anybody has earned the right to say things like that, maybe him. Elon. Rare air of folks who could get away with that type of comment.
- [31:02]
A
Definitely there's a balance here between. 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 is 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.
- [31:26]
B
$100 million non investment made substantive. One of the key pillars of what's the $100 million partnership is they're going to do things that I couldn't explain to you because you wouldn't understand. You're like, that might be on the COVID of a book of what I saw at the top of the market by a writer to be unnamed in five years.
- [31:51]
A
Yeah, I better get pitching that one. But then we should talk about then what it means for the market 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.
- [32:10]
B
Has to do that because the Microsoft.
- [32:12]
A
Oracle, Core Weave, Nvidia, they are now all relying on OpenAI to deliver. And I don't even know what more I mean to deliver what exactly.
- [32:20]
B
And then you think about all those ecosystems. So the energy companies are relying on Core Weave 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 that 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 at times.
- [32:53]
A
Right. And I think the answer for OpenAI has to be that in order to meet these enormous expectations, I just set it up. I don't, 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 spear's edge of this and not able to find jobs right now. I want to talk about that right after this. Did you know your credit card points and miles can lose value to inflation? Credit card companies often reduce the redemption value of your points and miles. Now imagine a credit card with rewards that can grow in value. With the Gemini credit card, you can earn Bitcoin or one of over 50 other cryptos instantly with no annual fee. Every swipe at the store or gas pump earns you instant rewards deposited straight to your account. Plus sign up now for a $200 Bitcoin bonus to kickstart your rewards, visit gemini.com car today. Check out the link in the description for more information on rates. Again, if you're looking to invest in Bitcoin but don't know where to start, the Gemini Credit Card makes it easy. The Gemini Credit Card is issued by Web Bank. In order to Qualify for the 200 crypto intro bonus, you must spend $3,000 in your first 90 days. Some exclusions apply to instant rewards, in which rewards are deposited when the transaction posts this content is not investment advice and trading. Crypto involves risk. The Gemini credit card cannot be used to make gambling related purchases Shape the Future of Enterprise AI With Agency agntcy now an open source Linux foundation project, Agency is leading the way in establishing trusted identity and access management for the Internet of Agents, the collaboration layer that ensures AI agents can securely discover, connect and work across any framework. With agency, your organization gains open, standardized tools and seamless integration, including robust identity management to be able to identify, authenticate and interact across any platform, empowering you to deploy multi agent systems with confidence. Join industry leaders like Cisco, Dell Technologies, Google Cloud, Oracle, red hat and 75 plus supporting companies to set the standard for secure scalable AI infrastructure. Is your enterprise ready for the Future of Magentic AI? Visit agency.org to explore use cases now that's AGN tcy.org finding the right tech talent isn't just hard, it's mission critical. And yet, many enterprise employers still rely on outdated methods or platforms that don't deliver. In today's market, hiring tech professionals isn't just about filling roles and it's about outpacing competitors. But with niche skills, hybrid preferences and high salary expectations, it's never been more challenging to cut through the noise and connect with the right people. That's where Indeed comes in. Indeed consistently posts over 500,000 tech roles per month, and employers using its platform benefit from advanced targeting and a 2.1x lift in started applications when using tech network distribution. If I needed to hire top tier tech talent, I'd go with Indeed. Post your first job and get $75 off at indeed.com/tech talent. That's indeed.com/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 FirstMark 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 OpenAI, like Anthropic, basically trying to automate all work, all white collar work. And if they're successful, what happens?
- [36:59]
B
Well, 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, 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 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 rethink their business. 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. 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're 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, the American 20th century and everything that happened. So there is a creative destruction that I think capitalism is really good at. I think that you saw that repurposement in the Industrial Revolution. You saw a repurposement several times. And 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 there's a bunch of different things that are analogous to it. 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. Since the Ivan 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 huge, huge factor. So 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. 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, 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 I 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 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 gonna see entrepreneurship, you're gonna 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.
- [41:15]
A
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?
- [41:28]
B
Yes.
- [41:29]
A
The money is betting that all this, 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 gonna be massive disruption. Yeah. 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 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 using words they'd never use in normal conversations. They attend meetings about meetings. They create PowerPoints that nobody reads, which get 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.
- [42:33]
B
Funny because it's true.
- [42:34]
A
Right. Like, 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.
- [42:51]
B
There's a great New Yorker political cartoon which does the same thing of someone types out an email and they say AI turn this into a hundred page PowerPoint presentation and they turn into 100 page PowerPoint and they email it to their colleague then says AI take this 100 page PowerPoint presentation and turn into a short email.
- [43:09]
A
Exactly.
- [43:10]
B
So everybody is using AI to automate different pieces. You know, I, I, I just think that, you know, to have the, 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.
- [43:30]
A
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.
- [43:46]
B
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 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.
- [44:35]
A
We have an audience. I hope everyone out there. Yes.
- [44:39]
B
So I think you're going to see more people doing different stuff. I mean, part of that is the rise of the creator economy 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. I think it's going to happen more and more.
- [45:20]
A
Yeah, I mean that happened to me. I started my career in marketing and sales and writing freelance journalism on the side and then flipped that to a full time career and then flipped that into something that's now not just writing, but is video, audio, some TV liked 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 chatgpt that and be done with it in five seconds.
- [46:05]
B
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. 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. And there's more investment bankers than ever. I think although it's changing, it doesn't mean it's ending.
- [46:39]
A
And we talk about like there's a thriving economy out there sometimes and then you think about what's happening with all right, 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. 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, feels like everything is just stuck.
- [47:21]
B
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 companies are slow to hire. 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. And 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 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. 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'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.
- [49:13]
A
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, use them more so let's just go through four of them if we can. We have about eight minutes.
- [49:28]
B
Great.
- [49:29]
A
Discord.
- [49:30]
B
Yes.
- [49:30]
A
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 and 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.
- [49:50]
B
So I think. And moving to Discord servers. Right.
- [49:52]
A
And is that good for us basically?
- [49:55]
B
Well, somewhat. It is. I mean, I don't think everybody. The old joke, you know, you don't have to broadcast to anyone. Everybody 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, 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 a League of Legends clan, all of those things, you find that they're there. 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 there's the right level of discourse in those Discord servers and it makes sure that works.
- [50:51]
A
But that's on the administrator of the Discord.
- [50:54]
B
It's on the administrator. Yeah. Of the server.
- [50:56]
A
Of the server.
- [50:58]
B
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, you know, sports or music or technology or relationships. Just because I think that people might be a little bit over living in public.
- [51:20]
A
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.
- [51:36]
B
That's awesome.
- [51:36]
A
Conversation is high quality, it's interesting and I love being in there. I get a lot of value out of it.
- [51:42]
B
Yeah. And curation has been for the last 10 years of social media. After the initial explosion, curation has been the most important thing to keeping a good, thriving community.
- [51:53]
A
All right. DraftKings.
- [51:54]
B
Yes.
- [51:55]
A
Did Shohei Ohtani actually bet on baseball or was it his interpreter?
- [51:58]
B
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 DraftKings think?
- [52:09]
A
Let me ask it in a little bit less facetious way. Obviously, sports betting's been popularized.
- [52:14]
B
Yes.
- [52:15]
A
The leagues all promote it. Yes. The players are getting into it.
- [52:18]
B
Yes.
- [52:18]
A
Is that a problem?
- [52:21]
B
Well, you're seeing more and more investigations and suspensions around the use and misuse of gambling. I think like any new technology, it explodes out of the gates. It's a little bit of the wild west. I think DraftKings, being a large public company who is a leader, probably has more guardrails around it than maybe prediction markets or some of these sweepstakes types, gray area markets. I think the government always struggles to keep up with where technology is going. It's oftentimes focus 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.
- [53:10]
A
Okay. Let's talk about Shopify.
- [53:12]
B
Yes.
- [53:13]
A
You're an investor in Shopify.
- [53:14]
B
I am.
- [53:16]
A
Is all online commerce going to go from applications and websites to into chatbots? And if so, what happens, happens?
- [53:23]
B
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 chat bots. 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 it in a chatbot based on your AI girlfriend.
- [53:49]
A
That's where I usually make most of my purchases.
- [53:50]
B
Yes. Yes. Your AI girlfriend is your stylist. That's. That'd be a good T shirt for.
- [53:55]
A
My AI girlfriend picked this out for me.
- [53:57]
B
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. Transaction. Whether you're getting that T shirt on Teespring versus your AI girlfriend, Chatbot versus the Gap, it's All going to happen. 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. I don't see any way that E Commerce is going to slow down in any foreseeable time.
- [54:45]
A
Right. So the interface might be a chatbot, but everything could be managed.
- [54:48]
B
Everything managed, 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 AI girlfriend and you don't want that T shirt anymore, can you return it? There's a lot of things, things that have to happen besides just the front end store. And 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.
- [55:20]
A
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?
- [55:34]
B
What do you mean by the greatest own goal?
- [55:36]
A
I thought just a terrible shoot yourself. There was a great quote. So let me, let me. Its own goal. Like when you kick it into your own neck. Soccer. I just got a quote from a Jets player yesterday. He's like, other teams shoot themselves in the foot and then we shoot ourselves in the head.
- [55:52]
B
Yeah, I just didn't catch it. So when I asked the question again, I'll respond to that again.
- [55:58]
A
Was okay, you invested in Airbnb?
- [56:00]
B
Yes.
- [56:01]
A
Was New York City's decision to ban Airbnb one of the greatest disasters in municipal government history?
- [56:08]
B
Yeah, I mean, it's definitely an own goal if we want to go use that format that, you know, you want to have a great, vibrant 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. 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 you hope in the long run, cooler heads prevail and everybody winds up doing the right thing.
- [56:49]
A
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 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.
- [57:09]
B
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. But 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 do regulatory capture.
- [57:44]
A
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, shout it out.
- [57:53]
B
So we do a bunch of different podcasts. You can follow me. Simple X address of just Rick. Rick, if you want to.
- [58:02]
A
When did you get that?
- [58:04]
B
It's a long, long story. That's probably for phase for chapter two of our conversation. So I'm ick 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 firstmark, we have a full parade of podcasts you should followerstmarkcap 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. 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. Find me any of those places as well as on our friend Scott Wapner's.
- [59:06]
A
Closing bell on cnbc, which you're about to go to. So we'll get you to set. Rick, great to see you than for coming on the show.
- [59:11]
B
This was awesome. Thank you very much. Happy to be back anytime.
- [59:13]
A
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.