Agents in the Enterprise | Aaron Levie, CEO of Box | Ep. 3

Jack Altman 0:00 [upbeat music] All right, Aaron, thanks for doing this. Really appreciate you making time. I know you're really busy, and it's really good to get to sit down and talk to you.

Aaron Levie 0:06 Good to be here. Uh, I'm, I'm actually always here, and so thank you for coming.

Jack Altman 0:09 My pleasure.

Jack Altman 0:10 Um, so I wanna 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-

Aaron Levie 0:20 Yeah

Jack Altman 0:20 ... and how it relates to Box. You've got this-

Aaron Levie 0:22 I thought you were gonna say that we were talking about it first.

Jack Altman 0:24 Um, [chuckles]

Aaron Levie 0:24 Okay. [chuckles]

Jack Altman 0:25 You got the- that's right, too. But can, can you tell me sort of briefly just, like, where are you sort of, um, where are you thinking about, you know, AI as it relates to Box?

Aaron Levie 0:34 Yeah.

Jack Altman 0:34 How do you think agents are playing out right now? Obviously, this is what you're talking a ton about, but, like, what's sort of the kinda high level about what's in your mind right now?

Aaron Levie 0:40 So for us, the reason I'm, I'm just so, so pumped about AI right now is we've been building this platform for nearly two decades, uh, to help enterprises store, manage, share, collaborate on their most important data. And, um, and, you know, th- 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, what you mostly do with your files. You, you know, you create one, you share it, you collaborate, and then it goes somewhere, and you never see it again. And that, that... We, we, we just see that with the life cycle of data. Data, you know, starts out hot for the first couple o- you know, hours, couple 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 up, like, five years later, or there might be some legal reason why you need it, but, uh, 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, of, of value for an organization because it might have an insight that would lead to your next product discovery. It might re- 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, A- 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, uh, 115,000 customers trust. 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, of everything we're doing. So we're sort of running the company and, 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, 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. Uh, you, you don't reimagine your business model for that new era that, that's emerging. And so we're trying to, you know, learn all those lessons, m- 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.

Jack Altman 3:00 You've been talking a bunch about agents.

Aaron Levie 3:02 Yeah.

Jack Altman 3:02 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 company. So, 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 gonna get to-

Aaron Levie 3:14 Yeah

Jack Altman 3:14 ... 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-

Aaron Levie 3:23 Yeah

Jack Altman 3:23 ... whatever they kinda wanna do? Like, what does that look like?

Aaron Levie 3:25 Yeah, so we imagine f- within the Box environment, that you'll create agents, and we already have actually, the, the, some, 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, uh, 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, uh, can look at digital assets, um, you know, pull out the data from those digital assets, and then automate a, you know, marketing campaign sort of workflow process. 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 e- you know, every segment of, of, uh, of enterprise and, and public sector, private sector, and so on. That's what we're gonna build out, and, and we think that, you know, creates this, you know, huge, um, 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, a new earnings cy- cycle, and I want it to look at all that data and run a full report on what are the trends happening in the semiconductor industry, you know, where are there GPU shortages, you know, what should I invest in?" And that agent is gonna go out, look at your data, pull back, run a report, maybe connect to outside systems. Um, you know, the, the, you know, recently, O- OpenAI has a, 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 kinda, like... You know, this requires you to, to kind of extend out, you know, certainly beyond an- any given SaaS, uh, product or, or existing platform. And you say, "Okay, but Box is not gonna be the only place where work happens," you know, 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 gonna eventually need agents between these platforms to talk to each other. So, so how do you have, uh, 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 ChatGPT, and I'll say, "You know, run a report on this customer," 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, ZoomInfo and, and, and 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 Agentforce, you might run that, and then that's gonna go call out to Box, and... Or you might be running an ITSM workflow in ServiceNow, and that's gonna go call out to Box. But, but no matter what, our agents are gonna eventually have to talk to each

Aaron Levie 6:50 other.

Jack Altman 6:50 It seems like anybody who's in, any, any, like, enterprise software company would want these agents because they're gonna be so valuable. But my guess is that the thinking would be whoever owns the data and whoever has all the integrations is gonna be in the best position to sort of make the agents that do all this stuff-

Aaron Levie 7:04 Yeah

Jack Altman 7:04 ... inside the company. Do you think that, um-... s- 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-

Aaron Levie 7:22 Yeah

Jack Altman 7:22 ... of the customer relationships already. So how are you thinking about where a startup ought to win?

Aaron Levie 7:27 Yeah.

Jack Altman 7:27 Like, are there places where a startup ought to win other than the incumbent being asleep at the wheel?

Aaron Levie 7:31 Yeah.

Jack Altman 7:31 Or for the most part, is it really just the incumbent should always win, but big companies are tired, and therefore, startups?

Aaron Levie 7:36 So I think you're gonna 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 were 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 gonna go digital, and we're gonna do the, the digital version of our, of our business model." You know, the, the classic of, of Barnes & 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 gonna exist in, in a whole bunch of categories. It won't be Boxed because we're not- we're like, uh- like, we're religiously betting on this, um, but we're very worried about competition from lots of angles, but it won't be because we're asleep at the wheel.

Jack Altman 8:22 Yeah.

Aaron Levie 8:22 So, so we're gonna be 100% focused on making sure we're building out a platform that works in a, uh, in an a- a- 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 can tell Salesforce is not asleep at the wheel. ServiceNow is not asleep at the wheel, and, 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? 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, 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, um, you know, cu- kind of customer support agents, and now we have a world where, you know, AI is gonna start to automate more of that. Can my business model evolve to be able to go and, and, and support that?" 'Cause that, that really... Like, innovator's dilemma, it, it's funny that, you know, we think about that as a tech-oriented issue. It's, it's a business model-oriented, o- oriented issue. It, it sort of- it works on every industry, and it's just- it just exists because the incumbent, they don't wanna do something that, that, that basically r- erodes their core profit. Um, like, nobody in the management team wants to have less revenue the next year-

Jack Altman 9:54 Of course

Aaron Levie 9:55 ... and then have, you know, Wall Street hate them and, 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 an innovator's dilemma, and there will be companies that sort of face that, and, and it's gonna 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 can underwrite, you know, quite a bit at, at 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, where an agent is sort of now better off serving the problem.

Jack Altman 10:31 Replacing human work, basically?

Aaron Levie 10:32 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, like, you know, Goldman Sachs or, or, um, you know, an economist's view of, of these kind of analyses is like, "Let's look at all of human labour, and then we're gonna just, like, figure out in gradients, like, how much can AI replace?"

Jack Altman 10:56 Mm-hmm.

Aaron Levie 10:56 It's a pretty myopic approach because it just implies that, like, the world is, like, perfectly right now. You know, we have this perfect equilibrium of, of supply, demand for talent, and we can all pay for the talent, you know, and, and it's- it, it all kind of works. But, but actually, it just turns out that, like, 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.

Jack Altman 11:21 In other words, it's not just a cost-saving endeavour, like we should be generating new work.

Aaron Levie 11:24 You'll be generating new work with AI, and so there's gonna be a lot of startups that will emerge in categories where there's just not an incumbent software player or even an incumbent, you know, services player that will, that will begin to automate things that are just net new spend categories. You know, we're, we're already seeing this in a, in a, in a bunch of examples, but like, you know, codegen is, 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 Codium 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. Like, it's all just like all we... Uh, every company and every individual just has now decided to swipe their credit card and now buy AI to augment how they work.

Jack Altman 12:16 Right. People haven't been replaced, you're saying?

Aaron Levie 12:18 No, no, nobody's been replaced in, in those categories. Again, there's gonna 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 is 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, a la GitHub-

Jack Altman 12:42 Yeah

Aaron Levie 12:42 ... and delivering better products. And so, so that actually, I think you can also underwrite to hundreds of companies that are gonna be worth, you know, billions or tens of billions of dollars.

Jack Altman 12:51 I mean, my mental model there is there are some activities where it's just the more, the better.

Aaron Levie 12:55 Mm-hmm.

Jack Altman 12:55 So writing code, you know, selling products-

Aaron Levie 12:58 Yep

Jack Altman 12:58 ... 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.

Aaron Levie 13:06 Yep.

Jack Altman 13:07 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-

Aaron Levie 13:15 Yeah

Jack Altman 13:15 ... for a company.

Aaron Levie 13:16 Yeah, and, 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 pr- 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, is just gonna happen through AI. But even for us, let's say, and, and we're, you know, we're gonna be deploying more AI around these types of use cases, if I can save money, let's say, in customer support-... um, 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."

Jack Altman 13:58 Yep.

Aaron Levie 13:59 We have always been constrained on the number of customer success managers that we can afford. Like, I would, like, you know, a- 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-

Jack Altman 14:16 That's enough, yeah.

Aaron Levie 14:16 ... 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-

Jack Altman 14:25 Yeah

Aaron Levie 14:25 ... I can just move now to human labor in other parts. Now, you gotta- you have to get, uh, 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 wanna be, like, overly optimistic and, and, and totally say nothing's, nothing's gonna happen and there's no transition, 'cause there will be areas that, that are more disrupted. Like, like, I, you know, um, 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

Aaron Levie 15:04 rolls out.

Jack Altman 15:04 Connecting this back to the innovator's dilemma-

Aaron Levie 15:07 Yeah

Jack Altman 15:07 ... 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.

Aaron Levie 15:18 Yeah.

Jack Altman 15:18 And so as a result, some of these agent companies can charge, like, surprisingly large amounts, 'cause even being a quarter of the cost of a person is, like, a lot more than you would've expected it to be.

Aaron Levie 15:27 Yep.

Jack Altman 15:28 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-

Aaron Levie 15:36 Yeah

Jack Altman 15:36 ... it should eventually come back to cost.

Aaron Levie 15:37 Yes.

Jack Altman 15:37 Like, how are you thinking about this from a business model and disrupting yourself and that-

Aaron Levie 15:41 Yeah

Jack Altman 15:41 ... whole picture?

Aaron Levie 15:42 I mean, i- if I had to bet on, let's say, let's, let's just make it really binary, like, does, 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 gonna bet on the latter, just because competition almost sort of is going to cause that to happen. Let, let's say there's this human, you know, type of task that costs $100 an hour, and you're just like, "I'm gonna build AI to do that at $50 an hour," and but, like, the underlying cost is $1, you know, an hour of compute. Somebody's just gonna say, "Okay, I'll just do it at 40," and then somebody's gonna say, "I'll do it at 30," and then somebody's gonna do it at 20. And eventually it's gonna converge to, "Okay, we're, like, just gonna do it like a normal software gross margin type model." So unless you have incredible proprietary access to something, like, you know, for anybody listening, like read Seven Powers. Um, uh, it, it's, it's, uh, 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 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 gonna generate," you know, "marketing asset work," I think eventually it's gonna 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, you can only sell to the number of people in the company. Like, that's, like, the- that's the TAM. So, so if you have a 20-person company, you're selling 20 seats. But, like, now with AI, that 20-person company could have, like, 10 AI lawyers and 10 AI SDRs-

Jack Altman 17:27 For sure

Aaron Levie 17:27 ... and 10 AI marketers, and all of a sudden now you're gonna 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.

Jack Altman 17:42 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.

Aaron Levie 17:53 Yeah.

Jack Altman 17:54 But in the long term it's all good, and maybe we're like-

Aaron Levie 17:56 That's your fault, though.

Jack Altman 17:56 Yeah, that's probably my fault. [laughing]

Aaron Levie 17:57 Okay. [laughing]

Jack Altman 17:58 No, I'm very early stage.

Aaron Levie 17:59 I mean, if you're naming your podcast Uncapped, like, you are the problem.

Jack Altman 18:02 Yeah, you-

Aaron Levie 18:03 Okay

Jack Altman 18:03 ... you gave me good feedback on that.

Aaron Levie 18:04 [laughing]

Jack Altman 18:04 We might need to adjust that.

Aaron Levie 18:05 Maybe just, like, medium-sized cap.

Jack Altman 18:07 Medium cap.

Aaron Levie 18:07 Medium cap.

Jack Altman 18:08 Yeah, exactly. Yeah, but, like, do you think that we- 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 gonna 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...

Aaron Levie 18:29 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, 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 tho- 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 kinda 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 gonna 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.

Jack Altman 19:13 Yep.

Aaron Levie 19:14 So I, I- you know, it's like, it's like-... Yes, but

Aaron Levie 19:17 then what do you do about any of that?

Jack Altman 19:17 Yeah, sure. So, okay, [laughing] so-

Aaron Levie 19:19 [laughing] Yeah, who cares?

Jack Altman 19:20 That's fair.

Aaron Levie 19:20 [laughing]

Jack Altman 19:20 So okay, so on that point, so you're twenty years now into Box.

Aaron Levie 19:23 Yeah, yeah.

Jack Altman 19:23 Which is amazing, and in you-- I think you launched in 2005.

Aaron Levie 19:26 Yeah.

Jack Altman 19:27 And that was, like, before AWS, I think, slightly.

Aaron Levie 19:31 We were, like, three months before AWS or five months before AWS, and it, 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.

Jack Altman 19:44 Mm-hmm.

Aaron Levie 19:44 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 yes.

Jack Altman 19:52 Yeah. But so you kind of saw... I mean, but you were at the beginning of cloud, and you saw, uh, cloud.

Aaron Levie 19:56 Hundred percent.

Jack Altman 19:57 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-

Aaron Levie 20:06 Thank you

Jack Altman 20:06 ... in cloud, so congratulations.

Aaron Levie 20:07 [laughing]

Jack Altman 20:07 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've 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?"

Aaron Levie 20:27 Yeah. 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 w- 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, a- you know, apropos AI, 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, nineteen 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 gotta be on the common file system. It's gotta be on our cloud, um, and it contributes to all of the other kind of multi-tenant, uh, capabilities we have. 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.

Jack Altman 22:04 Do you think, like, the, the, so 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-

Aaron Levie 22:13 Yeah

Jack Altman 22:13 ... that kind of play at this sort of slightly more neutral layer across the hyper, do you think the market was always destined to be oligopolies at the hyperscalers with, you know, their version, and then there's gonna 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?

Aaron Levie 22:35 I could totally imagine a world where, where, yeah, you, you, you... It would not have played out this way. I mean, w- it was, uh, I think it was largely through brute force that we, we were able to build fast enough, better functionality, more enterprise-grade, grade 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 a, you know, a midsize to larger enterprise, but when your documents and financial documents and, you know, marketing assets or, you know, HR records are in Box, and one day there's a new model from Gemini that, like, is really breakthrough, it just works, and the next day there's a new OpenAI model-

Jack Altman 23:25 Yeah

Aaron Levie 23:25 ... 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's in some cloud that's only gonna work with the model that they choose to, to kind of deploy. Um, and so that, that sort of flexibility and, and maybe future-proof of what capabilities you have access to became very, very important. Um, but I don't think it was obvious on day one to most customers that that would matter.

Jack Altman 23:48 Yeah.

Aaron Levie 23:48 And now it's actually, you know, paying off for, for customers massively 'cause you're not stuck now in, in, you know, and, and, and not getting the access to whatever the latest innovation breakthrough is.

Jack Altman 23:56 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.

Aaron Levie 24:07 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 gonna run on anything. We'll work with whatever the models." And so, you know, you kind of have to know your... You, you, o- one thing about start-ups 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 gonna work with, the models that we're gonna support. We wanna be a, just a n- a neutral, open platform, first mover, fir- first, you know, uh, the- the first company to support any new, new, new kind of technology for our customers. If we're not training a model, we better be really, really good at, at then enabling all the models for our customers, and, like, that- that's a flip that you just make

Aaron Levie 24:55 as a strategic decision.

Jack Altman 24:56 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 wanna, 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, by, by the end, in a lot of ways, I think that happens to more people than not. You know, one of the, one of the types of founders I really love investing in is young founders who, you know, by the time they're-

Aaron Levie 25:28 They don't know how painful it's gonna be [laughing] .

Jack Altman 25:30 There's definitely that. But also, it's like by the time somebody's 25 or 27-

Aaron Levie 25:34 Yeah

Jack Altman 25:34 ... they've already got a real company-

Aaron Levie 25:35 Yeah

Jack Altman 25:35 ... and they have so long ahead of them.

Aaron Levie 25:36 Yeah, it's cool.

Jack Altman 25:37 You know, you've been doing this for 20 years-

Aaron Levie 25:38 Yeah

Jack Altman 25:38 ... and you're still young.

Aaron Levie 25:39 Yeah.

Jack Altman 25:39 And so, you know, I imagine when you started, you were like, you know, obviously, you were really young.

Aaron Levie 25:43 Yeah.

Jack Altman 25:43 Like, how old were you were?

Aaron Levie 25:44 We launched the company, uh, I forget, it was, uh, like, like basically I got the idea, like, late in my 19s, and then we launched it when I was 20.

Jack Altman 25:51 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.

Aaron Levie 25:57 Mm-hmm.

Jack Altman 25:57 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 that just, you know, you just enjoy it so much?

Aaron Levie 26:13 I mean, it has to be the f- the latter of, of all those. Like, so, uh, I, 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, what we all did, you know, growing up and then eventually getting into tech and in the startups is, like, you like to build things, you like to create things, you like to solve problems, you get excited about new technologies. Prob- 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, y- 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 s- 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. 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. Um, 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.

Jack Altman 27:30 Yeah, but it's gotten much more fun with AI now.

Aaron Levie 27:32 But AI is just like, "Holy shit!"

Jack Altman 27:34 Yeah.

Aaron Levie 27:34 Like, like, like, wow! Like, like the, 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.

Jack Altman 27:43 It's shocking.

Aaron Levie 27:43 It's shocking.

Jack Altman 27:43 Yeah.

Aaron Levie 27:44 And so, like, now it's like, wow, like, you're, like, totally, like, dopamine and, like, and you're just, like, totally amped up.

Jack Altman 27:49 And, and you've got this platform with all the data, all these customer relationships, so-

Aaron Levie 27:52 Yeah, so, so you're not starting from scratch. Like, like, like I... you know, I, I, I would be very stressed out if it was like, "Oh gosh, like we're, we're..." You know, you've gotta go- totally go from zero, and I'm, and I, and I love the energy that new founders have 'cause they don't know what they're in for. [chuckles]

Jack Altman 28:04 Yep, totally.

Aaron Levie 28:04 And they're, like, t- 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 gonna... You know, I, I forget if it's Elon or, or, like, Levchin, like, somebody, like, the chewing glass thing.

Jack Altman 28:20 Yeah, totally.

Aaron Levie 28:20 Like, you're gonna do it.

Jack Altman 28:21 Yep.

Aaron Levie 28:21 Like, every... You're gonna, you're gonna chew the glass, and you're gonna, you know, bust through every wall possible, and, and you really need that, that spirit, which is, uh,

Aaron Levie 28:29 which is great.

Jack Altman 28:29 All right, we only have a few minutes left. I'd love to ask you about politics for a little bit, if that's cool.

Aaron Levie 28:32 Oh, it'd be great to not do that, yeah. [laughing]

Jack Altman 28:33 Okay, we can just, we can just wrap up. Let me ask you a couple things.

Aaron Levie 28:35 Yeah, yeah. Okay.

Jack Altman 28:36 Surprisingly-

Aaron Levie 28:37 Uh-oh

Jack Altman 28:37 ... you are kind of now one of the few vocal voices on the left in, like, this way that I think is, um, very authentic, and five years ago, I would've 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. Um, 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?

Aaron Levie 29:10 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, um, and I- I actually think it's, like, pretty accurate. You know, some people get pretty, pretty mad when they see that, but, um, but I, I think it's actually a very accurate kind of reflection of, of politics. Like, the left has moved left on a, on a number of variables. I think, uh, 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, at some point was just like, you know, w- like, "We can't go to space. I can't build things. We're regulating everything. There's a culture problem that I, that, that I have a problem with." 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 my own- on their own. And, and my set of variables have just been... You know, I, I'm, 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's really important, and, 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, uh, research things and, and whatnot." So then, so then I kind of stay still on, you know, on, on a different side. I'm actually very compelled by many of the arguments of the people that, that, you know, maybe change direction or, or move more to the right. Um, and so, uh, a- a- and, and, and if anything, I'm just actually kind of upset that the Democrats couldn't kind of get their act together.

Jack Altman 30:45 That's what I was gonna say. I mean, one of the things that's been sad-

Aaron Levie 30:47 Yeah

Jack Altman 30:47 ... 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-

Aaron Levie 31:00 Yeah

Jack Altman 31:00 ... and just, like, hasn't-

Aaron Levie 31:00 I think they have clear arguments, but they, they have some also bad policy, right? So, so w- 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, you know, 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.

Jack Altman 31:25 Yeah.

Aaron Levie 31:26 Obviously, that's, that's totally insane, and that is 100% 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, o- 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, and there's actually... Like, 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.

Jack Altman 32:18 Yeah.

Aaron Levie 32:18 And so, like, how, how inane is that, where a climate tech entrepreneur-

Jack Altman 32:22 It's, like, the top issue.

Aaron Levie 32:22 D- doesn't like Democrats? Like, that is a big cell phone. Um, and, uh, and so there's a lot of these types of things where, where just, like, what if we could just, like, stop doing cell phones? Like, what if you could just, like, build houses and do manufacturing and, um, 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. Um, 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, 'cause I didn't want to talk about politics. Now I'm just gonna, like, unravel. [laughing]

Jack Altman 33:03 Sorry. Yeah.

Aaron Levie 33:03 Um, the, uh, 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, 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-- tried to be centrist? Like, it didn't even work." And it was like, it was like: "No, no, what, like, you d- don't understand. Like, like, nobody believed that, that it was actually centrist."

Jack Altman 33:27 The left feels less unified than the right, and so on-

Aaron Levie 33:30 100%.

Jack Altman 33:30 And so on the left, you got two sides-

Aaron Levie 33:32 Yeah

Jack Altman 33:32 ... one that is actively, you know, or feels kind of anti-capitalism, even if they won't... You know, they'll say we're not, but then every policy is-

Aaron Levie 33:38 Yes

Jack Altman 33:38 ... and, like, that just can't, that can't possibly win.

Aaron Levie 33:41 No, it w- 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, 5 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, to kind of, you know, br- bring back that, that cohort, however we lost them." 'Cause literally, the, I don't think... Yeah, like, like, the country's not gonna lean even more to the left over time.

Jack Altman 34:15 It does seem, it seems like a big cell phone that the left didn't get tech, you know, a- as, like, a close ally, which, you know, there's, f- 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.

Aaron Levie 34:29 100%.

Jack Altman 34:29 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-

Aaron Levie 34:35 Yeah

Jack Altman 34:35 ... is that, that, do you see that as a strong positive at least?

Aaron Levie 34:37 I do.

Jack Altman 34:37 Yeah.

Aaron Levie 34:37 Yeah. So I, 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. We'll, 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 'cause it was like, it was such a shock to my world understanding that I was like, you know, like, "Oh, everything's bad," and, 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, I don't agree with at, at times, but then there's probably gonna be a lot of things I do agree with. And so, um, one of the things I do largely agree with is, um, is there is a, a very pro-tech, very pro-innovation, vo- pro kind of like, let's advance in a number of categories, set of, of, of individuals around the Trump administration in key cabinet positions that are gonna make really positive, I, I believe, positive decisions for, for the future of, of technology. I care more than anything just about, like, America continuing to be the best place to, to build companies, to build technology, to, to drive innovation. And so I, and I think there's a number of people that, that are good and strong allies in the administration to go drive that in a way that actually didn't exist in, in the first, you know, presidency. And so basically, I'd say, like, I'm optimistic on tech policy during this administration for sure. I'm, like, anti-tariffs, uh, just 'cause I think that's, like, I believe in just, like, a global trade system that we actually, you know, get a lot of benefit from that. And there's other things that I'll be, you know, kind of against, but, um, but, but, you know, I think there's, there's actually a number of, of potential for, 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, of where we're at in AI right now, where we just need more progress. We need more attempts at innovation. Um, I think that's gonna be strong, and, um, and then I think we're gonna need, uh, to, to deregulate in certain categories where we need to be do more, doing more building, and I think that's gonna be positive.

Jack Altman 36:39 Cool. All right, well, Aaron, thanks a bunch for doing this.

Aaron Levie 36:41 Thanks for having me.

Jack Altman 36:41 Really great to have you. [upbeat music]