Uncapped #3 | Aaron Levie from Box

This week I sat down with Aaron Levie, Co-Founder and CEO of Box. Aaron came up with the idea behind the cloud computing company as a 19 year old college student and has led the company since its inception in 2005. Today, Box does over $1B in revenue with a market cap of $4.4B, and has raised over $560 million from the likes of DFJ, Andreesen Horowitz, and Meritech Capital. --- Timestamps: (0:00) Intro (0:10) Excitement in AI (6:50) Startups vs incumbents (15:04) Pricing agents (17:42) AI over or under hyped (19:17) Being first to cloud (24:55) Staying motivated (28:29) Shifting political landscape --- Linktree: https://linktr.ee/uncappedpod Twitter: https://x.com/jaltma Email: [email protected]

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Jack Altman?

  All right, Aaron, thanks for doing this. Really appreciate you making time. Know you're really busy and it's really good to get to sit down and talk to you.

• 0:06Speaker 01

  Good to be here. I'm actually always here and so thank you for coming.

• 0:09Jack Altman?

  My pleasure. So I want to start by talking about something that you've been super vocal about online lately, AI agents, AI software in the enterprise. Obviously, everybody's talking about it, but you've been talking about it in like great detail and how it relates to Box. You've got this-

• 0:22Speaker 01

  I thought you were gonna say that we were talking about it first.

• 0:24Jack Altman?

  Okay, you got that's right too. But can you tell me sort of briefly, just like, where are you sort of, where are you thinking about, you know, AI as it relates to Box? How do you think agents are playing out right now? Obviously, it's what you're talking a ton about, but like, what's sort of the kind of high level about what's in your mind right now?

• 0:40Speaker 01

  So for us, the reason I'm just so pumped about AI right now is we've been building this platform for nearly two decades to help enterprises store, manage, share, collaborate on their most important data. And, you know, that data is their financial documents, their contracts, their marketing assets, their employee records, all that data. And inside of that information contains an incredible amount of value, but most of it is underutilized. And so, you know, you just think about what you mostly do with your files. You know, you create one, you share it, you collaborate, and then it goes somewhere and you never see it again. And that, we just see that with the lifecycle of data. Data, you know, starts out hot for the first couple of hours, couple of days, week or two, and then it sort of, you go, it goes into a place where you just manage it. It's actually really important to keep around because you might need to pull it

• 1:24Speaker 01

  up like five years later, or there might be some legal reason why you need it. But, but you never tap into it in the meantime. You don't ask it questions, you can't pull out value from it. And yet, it actually contains an incredible amount of wealth of value for an organization, because it might have an insight that would lead to your next product discovery. You might, you know, have information that would make a sales rep better at selling their product. It might have information that a new employee onboarding into a company will ramp up faster, but you have not been able to tap into it. So for us, AI is just this massive breakthrough, which is we can finally actually open up the value of all of this data that organizations are sitting on. We kind of are in the right place, right time, in terms of having built out a platform that 115,000 customers trust.

• 2:07Speaker 01

  We're in about 67% of the Fortune 500. And companies have been using Box to be able to manage that data, automate workflows around it, secure that data, and now AI kind of plugs in right at the core of everything we're doing. So we're sort of running the company and imagining the company as if, you know, if we had started the company in 2025- What would we be building? How would we be running it? What would our business model be? And we're asking ourselves like, like, are we doing everything as if we were starting from scratch in this new era of AI as opposed to, you know, the traditional challenge with, with being either an incumbent or, or some, some company that's been around for a while is you, you take too long to, to address a new technology. You don't sort of pivot hard enough. You, you don't reimagine your business model for that new era that, that's emerging.

• 2:51Speaker 01

  And so we're trying to, you know, learn all those lessons, maybe to some extent to prevent anything bad from happening. But then I think just generally, I'm just way more excited about the upside of, of what's going on.

• 3:00Jack Altman?

  You've been talking about, about agents.

• 3:02Speaker 01

  Yeah.

• 3:02Jack Altman?

  And so it's like, you've got all this data, you know, obviously with Box, you, you know, you're storing all of the documents and the files and you know a ton about the companies. Like what in your mind are the agents then like doing? Like, let's say these agents get to a place that we all think they're going to get to in one, two, three years. Like, what does that world look like now where I've got like Box with all this data? And then I've got agents that can do whatever I want them to do, whatever they kind of want to do. Like, what does that look like?

• 3:25Speaker 01

  Yeah, so we imagine within the Box environment that you'll create agents. And we already have actually the, the, some of the core primitives available to, to customers in our AI studio, but we imagine a world where you'll have AI agents that, that you create or that are automatically created that are really, really good at content oriented workflows. So, you know, what are those in an organization? Well, that's a, a legal assistant reviewing a contract for clauses that, you know, you don't want to agree to. That's a procurement assistant that is reviewing invoices or, or payment terms and then automating, you know, some part of that process. That's a marketing assistant that can look at digital assets, you know, pull out the data from those digital assets and then automate a, you know, marketing campaign sort of workflow process.

• 4:08Speaker 01

  So, you will have, you know, millions and millions of those kinds of agents that get created. They'll help you automate the work that, that you do with content in every field, every industry, in, you know, every segment of, of, of enterprise and public sector, private sector and so on. That's what we're going to build out and, and we think that, you know, creates this, you know, huge productivity boost for, for organizations because now as an employee, I can have agents sort of running in the background, executing tasks for me around my data. I can say, hey, you know, I'm a financial analyst. I want an AI agent to go do a deep research on 20 financial documents of the latest, you know, notes I took or other people took on a, on a new earnings cycle. And I wanted to look at all that data and run a full report on what are the trends happening in

• 4:53Speaker 01

  the semiconductor industry, you know, where their GPU shortage is, you know, what should I invest in? And that agent is going to go out, look at your data, pull back, run a report, maybe connect to outside systems, um, you know, the, the, you know, recently OpenAI has a, a sort of agent SDK where you can have tool use. So you could pull from, from, from the web. So that might combine into that agent, you know, generating a full report for financial analysis. And again, you could imagine the same thing in legal or life sciences or healthcare and so on. So that's what the box agents will do. Then I think you kind of like, you know, this requires you to, to kind of extend out, you know, certainly beyond any given SaaS product or existing platform. And you say, okay, but box is not going to be the only place where work happens, you know,

• 5:35Speaker 01

  very clearly, um, uh, work happens in Salesforce and work happens in ServiceNow and work happens in Slack and work happens in, in Workday, um, and, and, you know, 500 other technologies. And so we're going to eventually need agents between these platforms to talk to each other. So, so how do you have a, an agent that can go off and pull data from five or 10 different systems to construct a full picture of, of, of, you know, the report you're trying to run or the workflow you're trying to automate or the decision you're trying to make? And that's where the industry is so unbelievably early, but we're starting to see this emergence of either protocols or at least, you know, concepts of how agents will talk to each other. Where I'll go to something like a chat to BT and I'll say, you know, run a report on this customer

• 6:18Speaker 01

  and it's going into box and pulling data, it's going into Salesforce and pulling data. Uh, it's going into, um, you know, zoom info and, and in looking at, you know, kind of, you know, proprietary, but, but semi-public data, and then it runs a full report on that. And, and we imagine a world where you might go to, you know, three or five or 10 different sort of horizontal systems for that query, or you might go to Salesforce and via something like agent force, you might run that and then that's going to go call out to box and, or you might be running an ITSM workflow in ServiceNow and that's going to go call out to box. But, but no matter what, our agents are going to eventually have to talk to each other.

• 6:50Jack Altman?

  It seems like anybody who's in, any like enterprise software company would want these agents because they're going to be so valuable. But my guess is that the thinking would be whoever owns the data and whoever has all the integrations is going to be in the best position to sort of make the agents that do all this stuff inside the company. Do you think that

• 7:08Jack Altman?

  new startups that want to get into like building agents and stuff like that, as I'm listening to you talk, it seems to me that in most cases incumbents ought to have the structural advantage. Like unless they're asleep at the wheel, basically incumbents have the data and the integration of the customer relationships already. So how are you thinking about where a startup ought to win? Like, are there places where a startup ought to win other than the incumbent being asleep at the wheel? Or for the most part, is it really just the incumbent should always win, but big companies are tired and they're for startups?

• 7:36Speaker 01

  So I think you're going to see, first of all, there's plenty of opportunity just in that latter category. Like, like most large companies today exist because of just incumbents who are asleep at the wheel. There did not have to be white space in that Netflix found. Like, that could have just been Blockbuster one day saying, I'm going to go digital and we're going to do the, the digital version of our, of our business model. You know, the, the classic of, of Barnes and Noble didn't have to let Amazon sort of, you know, get e-commerce and then, and then they built out from there. So, so first of all, I, I could, you could underwrite probably a trillion dollars of startup opportunity simply because of the kind of like asleep at the wheel, you know, kind of dynamic that, that's just going to exist in, in a whole bunch of categories. It won't be boxed because we're not, we're like, like we're religiously betting on this.

• 8:19Speaker 01

  But we're very worried about competition from lots of angles, but it won't be because we're asleep at the wheel. So, so we're going to be 100% focused on making sure we're building out a platform that works in a, in an agentic way. But lots of, lots of companies maybe won't be the case and it's very early to kind of figure out, you know, who's in, who's in which bucket. But, you know, you can, you could tell Salesforce is not asleep at the wheel. ServiceNow is not asleep at the wheel and, and, and the list goes on. Okay. So, so that, that's sort of the asleep at the wheel case. Then there's the innovator's dilemma problem, which is maybe it's like the sister to asleep at the wheel. Innovator's dilemma problem is, okay, I'm an incumbent company. I really like this sort of recurring revenue thing I'm getting on a seat basis. You know, it's, it's a very clean business model. I can price in a Certain way. And this is an opportunity for a startup to come in and say, you know what?

• 9:03Speaker 01

  Actually, AI has has sort of flipped the model. You know, it's a consumption oriented model as opposed to your pre buying a number of seats model. And, you know, a great category where where that becomes pretty obvious is things like, let's say, customer support software, right? Where where the innovator's dilemma dynamic is I used to sell, you know, 500 seats of software to the 500, you know, kind of customer support agents. And now we have a world where, you know, AI is going to start to automate more of that. Can my business model evolve to be able to go and and support that? Because that that really like innovator's dilemma, it's funny that, you know, we think about that as a tech oriented issue. It's it's a business model oriented oriented issue. It it sort of it works on every industry.

• 9:43Speaker 01

  And it's just it just exists because the incumbent, they don't want to do something that that that basically erodes their core profit. Like, nobody in the management team wants to have less revenue the next year. Of course. And then have, you know, Wall Street hate them and so on. And so the CEO just keeps kind of grinding it out until basically it's too late. So it's a business model dilemma ultimately in innovator's dilemma. And there will be companies that sort of face that. And and it's going to be in a variety of ways. There'll be consumer versions of this, there'll be enterprise versions. And then there's a third category. So I think you can underwrite a lot on Asleep at the Wheel. I think you could underwrite, you know, quite a bit in innovator's dilemma. And then I think probably the biggest category will be kind of net new use cases for AI. Where there's not an obvious incumbent who who sort of is in that market in in traditional software.

• 10:27Speaker 01

  Where an agent is sort of now better off serving the problem. Replacing human work, basically. Replacing human work or or just doing the human work that we never got around to. And I I think this is probably one of the the things that we we haven't been able to quantify. Which is like, how much of AI are we going to use in the future? That like, you know, Goldman Sachs or or, you know, economist view of of these kind of analyses is like, let's look at all of human labor. And then we're going to just like figure out ingredients, like, how much can AI replace? It's a pretty myopic approach because it just implies that like the world is like perfectly right now. You know, we have this perfectly equilibrium of of supply, demand for talent. And we can all pay for the talent, you know, and and it's it all kind of works. But but actually, it just turns out that like.

• 11:10Speaker 01

  We have a lot of things within Box that I'd like to do that we don't have people doing right now. And we might be willing to spend X amount, millions of more dollars of just net new spend.

• 11:21Jack Altman?

  In other words, it's not just a cost-saving endeavor, like we should be generating new work.

• 11:24Speaker 01

  You'll be generating new work with AI. And so there's going to be a lot of startups that will emerge in categories where there's just not an incumbent software player or even incumbent, you know, services player that will, that will begin to automate things that are just net new spend categories. You know, we're already seeing this in a bunch of examples, but like, you know, code gen is kind of an interesting one. You know, obviously two different takes on, on what the future of now, you know, coding as a, as a profession will look like. I'm, I'm more in the optimistic take, but like, let's just say if you froze right now and you just said, okay. You know, at today's, you know, moment when you add up Cursor and Replit and Codeium and everybody's revenue. I would argue that all of that spend on AI coding is, is sort of net new spend in, in the software stack.

• 12:08Speaker 01

  Like it's all just like, all we, every company and every individual just has now decided to swipe their credit card and now buy AI to augment how they work.

• 12:16Jack Altman?

  Right. People haven't been replaced, you're saying?

• 12:18Speaker 01

  No, no, nobody's been replaced in those categories. Again, there's going to be asterisks, like, like there, there could be, you know, long-term kind of, you know, consequences of this. And we can talk through what will that look like, but it's net new spend. There's not an incumbent that, that's sort of inherently being disrupted because there was no incumbent called like the code writing incumbent. And we very clearly have new startups that are actually out executing the, the incumbents that were in adjacent categories, all at GitHub.

• 12:42Jack Altman?

  Yep.

• 12:42Speaker 01

  And delivering better products. And so, so that actually, I think you can also underwrite to hundreds of companies that are going to be worth, you know, billions or tens of billions of dollars.

• 12:51Jack Altman?

  I mean, my mental model there is there are some activities where it's just the more, the better. So writing code, you know, selling products, like those things are the more, the better. There are some that are not like that though, you know, like customer support's an example that's not really like that. Like once all the tickets have been answered, the tickets have been answered.

• 13:06Speaker 01

  Yep.

• 13:07Jack Altman?

  Agents are good at answering tickets. So I do think we will probably have some areas quickly where like not as many jobs are available on a per million of ARR basis on a company.

• 13:15Speaker 01

  Yeah.

• 13:15Jack Altman?

  For a company.

• 13:16Speaker 01

  Yeah. And, and I guess the, um, you know, the, like, if you, if you sort of. Looked at like global customer support and you you probably broke it out by different categories. There's definitely some categories that AI, you know, is going to be very, very good at and and it's going to, you know, the next task or or, you know, password reset email, or I can't log in. It's just going to happen through AI. But even for us, let's say, and we're, you know, we're going to be deploying more AI around these types of use cases. If I can save money, let's say, in customer support or customer success. A lot of times, the dollars that we save there are going back into that exact same function. It's just, it's moving upstream to now I want to do proactive customer success.

• 13:58Jack Altman?

  Yep.

• 13:58Speaker 01

  We have always been constrained on the number of customer success managers that we can afford. Like, I would, like, you know, anybody in SaaS knows this, you you have all these, like, sort of ratioed roles. Like, how many SDRs do you have per sales rep? How many CSMs do you have per customer? And we've always, I've never been happy about the ratio. I've never been like, oh, like, we have, we have too many customer success managers. And it's always been because of the cost of of it in the business model. So if I can get more efficient in one area of that function.

• 14:25Jack Altman?

  Yeah.

• 14:25Speaker 01

  I can just move now to human labor in other parts. Now, you gotta, you have to get trained up. But but, you know, even today, most of our customer success managers were probably customer support reps five years ago or 10 years ago, either at Box or a different company. And so so I think there's actually a journey here in a lot of jobs. I don't want to be like overly optimistic and and totally say nothing's, nothing's going to happen and there's no transition. Because there will be areas that that are more disrupted, like, like, you know, you know, I think we're all kind of familiar with those. But I tend to think we we have more of a myopic view about how talent sort of mobilizes over time. And then the new skills or the new demands that the company has as this technology rolls out.

• 15:04Jack Altman?

  Connecting this back to the innovator's dilemma business model thing. One of the things that I find at least interesting at the moment is like, you know, software can charge, you know, 10 bucks, 20 bucks, 30 bucks a month. But agents, now you're comping to human labor. And so as a result, some of these agent companies can charge like surprisingly large amounts. Because even being a quarter of the cost of a person is like a lot more than you would have expected it to be.

• 15:27Speaker 01

  Yep.

• 15:28Jack Altman?

  But you would think that that's gonna sort of. Play out quickly over time and that, you know, we won't stay with agents staying priced relative to labor. It should eventually come back to cost.

• 15:37Speaker 01

  Yes.

• 15:38Jack Altman?

  How are you thinking about this from a business model and disrupting yourself in that whole picture?

• 15:42Speaker 01

  I mean, if I had to bet on, let's say, let's just make it really binary, like, does AI remain comped at labor? Or does it remain comped at, at sort of like infrastructure cost plus software and some margin? I'm going to bet on the latter, just because competition almost sort of is going to cause that to happen. Let's say there's this human, you know, type of task that costs a hundred dollars an hour. And you're just like, I'm going to build AI to do that at fifty dollars an hour. And but like the underlying cost is one dollar, you know, an hour of compute. Somebody's just going to say, okay, I'll just do it at forty. And then somebody else is going to say, I'll do it at thirty. And then somebody's going to do it at twenty. And eventually it's going to converge to, okay, we're like, just going to do it like a normal software gross margin type model.

• 16:20Speaker 01

  So unless you have incredible proprietary access to something like, you know, for anybody listening, like, read Seven Powers.

• 16:30Speaker 01

  It's, it's, it's one of the best books on this, but there's this concept of cornered resources. And, and if you have like a cornered resource that just like literally nobody else has on the planet, like a proprietary data set that's just like everybody needs and you're the only one to get it, sure. I think you could like always have AI agents that then get comped as people. But if you're automating, you know, work and it's code work, or it's, you know, outbound sales rep work, or it's, I'm going to generate, you know, marketing asset work. I think eventually it's going to converge on, on more software type margin. But the benefit is, is that you're no longer capped by the number of, of people that can use the software. So the thing I'm most excited about is not necessarily that AI will get comped at the price of labor, but it's that AI doesn't have the same cap as labor. Like right now, in, you know, in the SaaS world, when you're selling seats of software,

• 17:15Speaker 01

  you can only sell the number of people in the company. Like, that's like, that's the TAM. So, so if you have a twenty person company, you're selling twenty seats. But like now with AI, that twenty person company could have like ten AI lawyers and ten AI SDRs and ten AI marketers. And all of a sudden now you're going to be spending way more on software than you were in a, in a prior generation of that company. And so that's the, that's like the big TAM expansion. And, and I haven't seen great math yet on what that will look like, but I, I'm betting that that would be a very large number.

• 17:42Jack Altman?

  I would say generally like the consensus AI view right now is like it's slightly overvalued in the short term and things are, you know, things, people are too excited, prices that people are paying for these companies are too high.

• 17:53Speaker 01

  Yeah.

• 17:53Jack Altman?

  But in the long term, it's all good. And maybe we're like-

• 17:55Speaker 01

  That's your fault, though.

• 17:56Jack Altman?

  Yeah, that's probably my fault. No, I'm very early.

• 17:59Speaker 01

  I mean, if you're naming your podcast uncapped, like you are the problem.

• 18:02Jack Altman?

  Yeah, you gave me good feedback. We might need to adjust that.

• 18:05Speaker 01

  Maybe just like medium sized cap.

• 18:07Jack Altman?

  Medium cap.

• 18:07Speaker 01

  Medium cap.

• 18:08Jack Altman?

  Exactly. Yeah. But like, do you think that, do you see us there? Or do you see it somehow differently? Like, are we, is this the internet in 1999? And it's a little bit of a bubble, but it's all going to be good in the long term? Or does it actually not even feel like it's over, like the excitement is too great right now? Cause it's kind of all, you know, like the, these recent YC batches, everybody's working on it, it seems, right? But-

• 18:28Speaker 01

  You know, it's, it's, it's a funny concept of like, can things be overvalued in the near term that are undervalued over the long run? Cause by definition, the value should price in what the long run value is. So, so like, I have a hard time with that particular framing. As much as just I'd say that there'll be a lot of companies that don't work and a lot of companies that do. And the companies that do, today's prices will look, will actually look small. And those that don't, they'll look big. And in a market where you have a lot of energy and hype and excitement, you'll have probably more on average companies that don't work that will get valuations that don't make sense. That's, that's kind of true of every environment, but it's like, it almost like, there's nothing you can do about that. Like, because like, the good assets are still going to be the good assets. And in a lot of cases, you don't know the good asset until, until you see three or five attempts at a particular kind of product area.

• 19:13Jack Altman?

  Yep.

• 19:14Speaker 01

  So I, you know, it's like, it's like, yes, but then what do you do about any of that?

• 19:17Jack Altman?

  Yeah, sure. So, okay.

• 19:19Speaker 01

  Who cares?

• 19:20Jack Altman?

  So, okay. So on that point, so you're 20 years now into Box.

• 19:23Speaker 01

  Yeah.

• 19:23Jack Altman?

  Which is amazing. And you, I think you launched 2005.

• 19:26Speaker 01

  Yeah.

• 19:27Jack Altman?

  And that was like before AWS, I think slightly.

• 19:31Speaker 01

  We were like three months before AWS or five months before AWS. And it's, it's sad because, um, because that actually meant that we had to get good at infrastructure. And then, and then you had this sort of path dependency where like, because we were good at infrastructure, we kept building out infrastructure. So it actually took us like a decade to like, like, like actually be like, no, like we're, we should probably be a cloud company. And then, and then another five years to actually make the transition. But yeah.

• 19:53Jack Altman?

  But so you kind of saw, I mean, but you were at the beginning of cloud and you saw a cloud.

• 19:56Speaker 01

  Hundred percent.

• 19:57Jack Altman?

  And you know, then GCP comes out and Azure, I mean, the timing, like looking back on some level, it's like shockingly, like you were kind of first at this layer.

• 20:06Speaker 01

  Thank you.

• 20:06Jack Altman?

  In cloud. So congratulations. That's really good. As you kind of look back, did it play out the way you expected? If you, aside from that sort of like, you know, you wish you could have launched a year later or something like that. Are there other things, knowing what you know now, looking back at that last cloud cycle that you would do differently? Or are there things that you like got lucky with that were super right? That you're like, thank God we did it that way?

• 20:27Speaker 01

  If I have any regrets or, or, or things that I would postmortem, it would usually just be situations where like, I wish we moved faster on X project or X thing that, that eventually did work. There were some key decisions that we made early on. This is more the positive, uh, where even in, even the very early days, you know, for obvious reasons, customers would say, hey, could we run you on prem? And we, we were just very stubborn and steadfast and we said, no, like we're a cloud company. It's, it's all multi-tenant. It's all SaaS. You can't deploy this on prem. And for a number of years, it was like, is this the right decision? We didn't really question it that much, but the market certainly did. And, and, and customers were, you know, we lost a lot of customers in the process. You know, I'm, I'm extremely thankful for some very religious architecture decisions that we made early on that we stuck with, because now it's set us up where, you know, you know, apropos AI,

• 21:13Speaker 01

  every AI capability we add to the platform, it instantly works if a customer turns it on for the entirety of our customer base. You don't have to be on like version, you know, 19 of box. Like it's just like box is box. Everybody's on the same exact version. And when you have AI, it just like plugs into everything you're doing when you, when you turn on the capabilities. So, so we, we've been able to kind of keep this architecture, uh, kind of clarity, uh, the, the whole, the whole journey. Like even when we make acquisitions, we're very, again, like rigorous on, like we don't keep other things running with different architectures. Like it's sort of, it has to plug into the platform. It's got to be on the common file system. It's got to be on our cloud. And it contributes to all of the other kind of multi-tenant, uh, capabilities we have.

• 21:56Speaker 01

  So, so I think we're benefiting from a lot of that and, um, and then drafting off of, of just, you know, some, some fortunate architecture. Decisions, you know, a number of years ago.

• 22:03Jack Altman?

  Do you think like the the sort of end state of the market where you had, you know, you had the hyperscalers and then you have you and maybe there's like one or two others that kind of play at the sort of slightly more neutral layer across the hyper. Do you think the market was always destined to be oligopolist at the hyperscalers with, you know, their version and then there's going to be, you know, a player like box that is going to sort of sit neutrally across or do you think that the market could have been shaped other ways and it was just like happenstance that it played out the way that it did?

• 22:35Speaker 01

  I could totally imagine a world where where, yeah, you you it would not have played out this way. I mean, it was, I think it was largely through brute force that we we were able to build fast enough, better functionality, more enterprise gate great capabilities, integrate with with basically everybody's software to sort of show that, hey, maybe you don't want your data just stuck in one of the clouds because if it goes there, you're stuck in this sort of vertical stack. And and it's great on on some dimension, but then other dimensions like AI is a perfect example of this. So one of our advantages in AI is when your content is in box and this is more more relevant for, you know, a midsize to larger enterprise. But when your documents and financial documents and, you know, marketing assets or, you know,

• 23:17Speaker 01

  HR records are in box and one day there's a new model from Gemini that like is really breakthrough. And it just works and the next day there's a new open AI model. It just works and the next day that there's a new anthropic model, it just works. And I'm not stuck with like, oh, this is only gonna like all my data is in some cloud. That's only going to work with the model that they choose to to kind of deploy. And so that that sort of flexibility and and maybe future proof of what capabilities you have access to became very, very important. But I don't think it was obvious on day one to most customers that that would matter. And now it's actually, you know, paying off for for customers massively because you're not stuck now in in, you know, and and not getting the access to whatever the latest innovation breakthrough is.

• 23:56Jack Altman?

  Yeah, I mean, it seems like the neutrality is very valuable in cloud and it seems like that same reason could be a big part of the argument in, you know, equivalently in AI now.

• 24:07Speaker 01

  Yeah, you're seeing different versions and flavors of this pop up. So, you know, I would imagine like Databricks feels the exact same way. Like, we're going to run on anything, we'll work with whatever the models and so. You know, you kind of have to know your, you, you, one thing about startups that I find is like, you need to fully exploit your advantage and your position to its maximum degree. If you like only half exploit it, then like, like, then just all bets are off, like, good luck. So what we've decided is like, okay, we're a neutral platform. So then we should probably like, like, take that to the max of all the software that we're going to work with, the models that we're going to support. We want to be just a neutral, open platform, first mover, first, you know, uh, the first company to support any new, new, new kind of technology for our customers.

• 24:48Speaker 01

  If we're not training a model, we better be really, really good at then enabling all the models for our customers. And like that, that's a flip that you just make as a strategic decision.

• 24:56Jack Altman?

  One thing that I find sort of like impressive, particularly impressive is that you've been in the public markets for a long time and you've been doing the company for 20 years. And still you are extremely energetic, very positive. You have like all, you still want to like make huge bets with the company. You know, I did Lattice for nine years, which felt like a long time. I was really tired, but you know, but by the end in a lot of ways, I think that happens to more people than not. You know, one of, one of the types of founders I really love investing in is young founders who, you know, by the time they're.

• 25:28Speaker 01

  They don't know how painful it's going to be.

• 25:29Jack Altman?

  There's definitely that, but also it's like, by the time somebody's 25 or 27, they've already got a real company and they have so long ahead of them. You know, you've been doing this for 20 years and you're still young.

• 25:38Speaker 01

  Yeah.

• 25:39Jack Altman?

  And so, you know, I imagine when you started, you were like, you know, obviously you were really young. Like, how old were you?

• 25:44Speaker 01

  We launched a company, uh, I forget, it was, uh, like, basically I got the idea like late in my 19s and then we launched it when I was 20.

• 25:51Jack Altman?

  And so many of the like best companies of all time were started by people really young, who did these really long runs with it. And so I guess like my distilled question on all of this is like, what goes into you staying so excited for so long? Like, how do you bring that? Like, is that just who you are? Is that something that you learned? Is it just, you know, you just enjoy it so much?

• 26:13Speaker 01

  I mean, it has to be the, the latter of, of all those. Like, so, uh, I don't like, like, it only works because I enjoy it. And then maybe the reasons why I enjoy it are, are these sort of like somewhat timeless things, which is, you know, what?

• 26:25Speaker 01

  What we all did, you know, growing up and then eventually getting into tech and in the startups like you like to build things. You like to create things, like to solve problems. You get excited about new technologies. Probably most people, you know, in our, in our orbit all have that, you know, set of conditions. And then, and then the question is, do you have a platform in which you can do interesting stuff that keeps that, that cycle going and, and keeps, you know, you energized? And I think it's probably maybe more lucky than not that like this became a platform where I could just keep doing that. Like we never got stuck in, in like one vertical or one type of use case where you're just like grinding out just incrementally. You know, sort of improving that one use case. We've always had some range of motion.

• 27:08Speaker 01

  You know, we, we help NASA go to space, major movie studios make a, make a film. We, we help the, the research process of a, of a new breakthrough drug. So, so you can kind of be, you, you can, you can be a little bit ADD of like all the things that you're doing, the use cases on the platform. And so that's what keeps it exciting. And then my answer maybe would be like 20% less excited three years ago.

• 27:30Jack Altman?

  Yeah, but it's gotten much more fun with AI now.

• 27:32Speaker 01

  But AI is just like, holy shit. Like, like, like, wow, like, like the, the demos that I see now on almost a daily basis from, from the, the team are just like, like this is just absolutely crazy.

• 27:43Jack Altman?

  It's shocking.

• 27:43Speaker 01

  It's shocking. And so like now it's like, wow, like you're like totally like dopamine and like, and you're just like totally.

• 27:49Jack Altman?

  And you've got this platform with all the data, all these customer relationships.

• 27:52Speaker 01

  Yeah. So you're not starting from scratch. Like, like, like I, you know, I, I would be very stressed out if it was like, oh gosh, like we're, we're, you know, you gotta totally go from zero. And I'm, and, and I love the energy that new founders have because they don't know what they're in for. And they're like so pumped. And what's great is like some of those will be like freaking fantastic and they'll be $50 billion companies. Some won't work, but like you kind of need that, you need that energy, you know, no matter what, because you are going to, you know, I, I forget if it's Elon and, or like Lev Chin, like somebody like the chewing glass thing.

• 28:20Jack Altman?

  Yeah, totally.

• 28:20Speaker 01

  Like you're going to do it. Like everybody, you're going to, you're going to chew the glass and you're going to, you know, bust through every wall possible. And, and you really need that, that spirit, which is, uh, which is great.

• 28:29Jack Altman?

  All right, we only have a few minutes left. I'd love to ask you about politics for a little bit.

• 28:32Speaker 01

  Oh, it'd be great to not do that. Yeah.

• 28:33Jack Altman?

  Okay, we can just, we can just wrap up. Let me ask you a couple things.

• 28:35Speaker 01

  Yeah, yeah, okay.

• 28:36Jack Altman?

  Surprisingly, you are kind of now one of the few vocal voices on the left in like this way that I think is very authentic. And five years ago, I would have been shocked to see that. And you've been willing to sort of through, you know, the text shift to the right, you've stuck to, you know, the side that you believed in and you've kind of, you've kind of watched a shift around you, I think. And you've done it sort of, you know, very vocally on Twitter where, you know, you're a public CEO and all this other stuff. Has it been a weird experience to like, watch it shift around you? Or has it been predictable to you in any ways?

• 29:10Speaker 01

  Elon and others have had this like chart that sort of says like, like, I've always been here and the Democrats have kind of, you know, moved here. And, and I actually think it's like, pretty accurate. You know, some people get pretty, pretty mad when they see that, but, but I think it's actually a very accurate kind of reflection of, of politics, like the left has moved left on a number of variables. I think depending on who you are and what you're impacted by, those, those variables have become just like, like they raise in importance, or they're just, they're not as, as sort of so fundamental. And so I can actually appreciate, let's say, you know, Elon at some point was just like, you know, like, we can't go to space, I can't build things, we're regulating everything, there's a culture problem that I, that I have a problem with.

• 29:53Speaker 01

  And so, so obviously then you have to, you eventually switch parties, you know, to, to kind of go against that. And I, I think everybody has their own version of, of, of that, that I can't speak for. People can, can do that on their own. And, and my set of variables have just been, you know, I'm, I'm completely convinced that all those variables are probably true. And then I just have a different set of variables that are just like, okay, well, I also think that like high skilled immigration is really important and, and like, you know, I don't think that like we need to have, you know, so many culture wars on, on certain topics. And, and I think we probably, you know, should fund different, different maybe kinds of, of research things and whatnot. So then, so then I kind of stay still on, you know, on, on a different side.

• 30:32Speaker 01

  I'm actually very compelled by many of the arguments of the people that, that, you know, maybe changed direction or, or moved more to the right. And so, and if anything, I'm just actually kind of upset that the Democrats couldn't kind of get their act together.

• 30:45Jack Altman?

  That's what I was gonna say. I mean, one of the things that's been sad watching that this whole shift over the last, you know, four to six years thing play out is that I feel like the left moved really far. The right made clear arguments and the left has clear arguments to make, but like hasn't made them in a lot of ways.

• 31:00Speaker 01

  Yeah, I think they have clear arguments, but they have some also bad policy, right? So, so we, we live in California. It should be like the greatest place on earth on every dimension. Like, like holy, like, how do you beat this weather? How do you beat the, just you've, you've completely created the atmosphere of every major tech company? You know, you have Stanford, you have Berkeley, you have Caltech, you have all the surrounding institutions. You have all the venture capital, like you're sitting on this incredible asset. And then like literally you, you can't make it affordable to live here. Like, that's just insane.

• 31:25Jack Altman?

  Yeah.

• 31:26Speaker 01

  Obviously, that's, that's totally insane and that is a hundred percent due to the bureaucracy of our state. So, and that's basically a Democrat problem. So, and unfortunately, like Democrats can't out message that with their policy views, because their policy views are in many cases, just the wrong policy views. Like, you actually just have to build and you have to create an environment where like you can build things. During the election cycle, when, when, you know, one of my, one of my whole kind of pushes was like, hey, maybe like we could like get some tech policy and, and sort of pro-progress policy, you know, in the Harris orbit. She actually had some very strong people, like, like studying this, these issues, caring about these issues. And so it was like, okay, let's like nudge them on all these topics. And as I would talk to friends and, and, you know, folks around tech and, you know, they would, I would say like, what, what's the problem with the Democrat party as an example?

• 32:09Speaker 01

  And there's actually, it was a very long list. Like, it was like, hey, I'm in like climate tech and I can't build in California because of, of the regulations in California.

• 32:17Jack Altman?

  Yeah.

• 32:18Speaker 01

  And so like, how, how inane is that where a climate tech entrepreneur?

• 32:21Jack Altman?

  It's like the top issue.

• 32:22Speaker 01

  Doesn't like Democrats. Like, that is a big cellphone. And, and so there's a lot of these types of things where, where just like, what if we could just like stop doing cellphones? Like, what if you could just like build houses and do manufacturing? And, and we could like lower the cost of things because we actually can like, like have more competition as opposed to more regulation. So I, I do think the party does need to do a bit of a reset. The next four years will be super interesting to watch, like which side comes out ahead. Cause you do have this warring, you know, dynamic of, of the, the, you know, more progressive, more left versus the more centrist and even watching the, it's funny because I didn't want to talk about politics. Now I'm just gonna like unravel.

• 33:03Speaker 01

  Um, the, uh, you know, post, post-election, you could just watch that like there were two completely different understandings of the election, right? Like one side, on the left, uh, one side was like, we weren't centrist enough. And, and, and then, and then the other side was like, see what happened when Harris was, would try to be centrist? Like, it didn't even work. And it was like, it was like, no, no, like, you don't understand, like, like, nobody believed that, that it was actually centrist.

• 33:26Jack Altman?

  The left feels less unified than the right. And so on, and so on the left, you've got two sides.

• 33:31Speaker 01

  Yeah.

• 33:32Jack Altman?

  One that is actively, you know, feels kind of anti-capitalism, even if they want, you know, they'll say we're not, but then every policy is, and like, that's just can't, that can't possibly win.

• 33:40Speaker 01

  No, that will never win a national election. Uh, it's, it's not possible. So, so basically, the powers that be have to get in a room and figure out that probably the way to win future elections is there's like five or 10% of people that shifted to the right. And you have to figure out why that happened. And you have to be like, well, maybe it's because our policies lost them. And we have to like be, be able to, to kind of, you know, bring back that, that cohort, however we lost them. Cause literally the, I don't think, yeah, like, like the country's not going to lean even more to the left over time.

• 34:15Jack Altman?

  It does seem, it seemed like a big cell phone that the left didn't get tech, you know, as like a close ally, which, you know, there's, to my eye, at least, there's no particular reason that this closeness that tech and the government have now couldn't have happened under like a Democrat.

• 34:29Speaker 01

  Hundred percent.

• 34:29Jack Altman?

  You know, at least now it's there. Are you like, when you think about now sort of tech's sort of like government kind of connection, is that, that, do you see that as a strong positive at least? Yeah.

• 34:37Speaker 01

  Yeah. So I, I, I made a decision, um, like, uh, actually like three months before the election, uh, which was just like, okay, post-election, no matter what happens, like, I'm just all in on the country. So like, whatever happens, like, cool. Like just like lean in whatever direction. And, you know, in 2016, it was a little bit different. 2017, it was a little bit different because it was like, it was such a shock to my world understanding that I was like, you know, like, oh, everything's bad and whatever. And, and it just wasted a lot of time. Like, like, there's no positive energy that was, was generated in that. Um, and so, so this time around, I was like, okay, like, like, let's find the positives. Obviously, there'll be negatives of things I don't agree with at times. But then there's probably going to be a lot of things I do agree with.

• 35:18Speaker 01

  And so one of the things I do largely agree with is is there is a very pro tech, very pro innovation, pro kind of like let's advance in a number of categories, set of individuals around the Trump administration in key cabinet positions that are going to make really positive, I believe, positive decisions for the future of technology. I care more than anything just about like America continue to be the best place to build companies, to build technology, to drive innovation. And so I think there's a number of people that are good and strong allies in the administration to go drive that in a way that actually didn't exist in the first presidency.

• 35:59Speaker 01

  And so basically, I'd say like, I'm optimistic on tech policy during this administration for sure. I'm like anti tariffs, just because I think that's like, I believe in just like a global trade system that we actually get a lot of benefit from that. And there's other things that I'll be kind of against. But I think there's actually a number of potential for pro tech. You know, the AI, the AI, you know, sort of messaging coming out of the government aligns more to my view of where we're at in AI right now, where we just need more progress. We need more attempts at innovation. I think that's going to be strong. And then I think we're going to need to deregulate in certain categories where we need to be doing more building. And I think that's going to be positive.

• 36:39Jack Altman?

  Cool. All right. Well, Aaron, thanks so much for doing this.

• 36:41Speaker 01

  Thanks for having me.

• 36:41Jack Altman?

  Really great to have it.