The Exchanges, every show

Q What did you not do with Box that you wish you'd done? You know, everyone has to prioritize. Everyone has strategic decisions on, we'd focus here. What decision did you decide not to do that you wish you had done?

A Earlier in our journey, I would have focused more on cash flow. I have become a little bit of a, of, of religious around cash flow. Um, uh, I think, I think owning your own destiny as a company is important. I think, um, you know, caring about every, and inspecting every single dollar of spend, In the business is very important. Um, I think, um, uh, I, I think these things, uh, you know, in, in, in sort of very loose capital environments, it, it sort of gets forgotten about or people don't really care about it. Um, but actually I think it helps you build a better business because you, you kind of apply constraints that force better decisions, better strategy, better execution. Um, so I would have done that, you know, years earlier than, uh, when we ultimately, uh, focus on cashflow.

AI assessment note: “Earlier in our journey, I would have focused more on cash flow.”

Q and you being young at the founding, My question is, I had Joe Fernandez from Joy Mode and Klaus on the show a long time ago now, actually, but he said that serial entrepreneurship was overrated, which I thought was a very interesting, quite contrarian statement, given the praise that we lord on serial entrepreneurs. Given that Box was your first company, would you agree that serial entrepreneurship's overrated? Yeah.

A Well, you know, I guess to be fair, it was my first company that maybe had, you know, some form of success, but had definitely tried lots and lots of other ideas prior. So I tend to not get too sucked into, you know, some of the maybe kind of quote unquote best Best practices or pattern recognition that I think we tend to pontificate about it. You know, there's amazing entrepreneurs that have done it once. There's amazing entrepreneurs that have done it five times, and it all comes down to the idea, the team, and do you choose the right market at the right moment? Those tend to be the factors more than whether it's your first or, or end company.

AI assessment note: “Those tend to be the factors more than whether it's your first or, or end”

Q How do you think it impacts, like, traditional enterprise and storage?

A You know, realistically, it largely doesn't. You know, the way to think about it is any design of a decentralized system has to have a certain amount of redundancy built in to obviously, you know, ensure against Censorship resistance and whatnot. And so whether that's storing something a hundred times or a thousand times or 10,000 times, you are storing something at an order of magnitude or two or three or four orders of magnitude more than what the direct value proposition requires. So for most things that you do on the web, for most software you use, you don't have a censorship resistance sort of use case or an immutability sort of oriented use case. And when you do, you have a lot of choices of what to do with your data. You can back it up. You can Put it somewhere else if you'd like. So I think there's a small, narrow fraction of data that could be very relevant on a blockchain, but that data is likely going to be limited in size, and it might be, you know, things like, let's say we do an e-signature. Maybe we want that e-signature recording to go on a blockchain, so that way in 50 years from now, we know that we can look it up and sort of, you know, check the hash of our e-signature and be able to validate it. So I think use cases like that, where we're talking about sort of like kilobytes of information, absolutely could have very relevant use cases, but the idea of Takin…

AI assessment note: “realistically, it largely doesn't.”

Q And, and is it early? Is it just starting really?

A It is because if you literally look at people's vendor stack, and if you were to go interview any, any CIO of any top 10,000 enterprise, the majority of their dollars are going into brand names, That, that existed a decade ago. So that kind of tells you we're still pretty early because it can't possibly be the case that for all of the world's largest organizations, all the software that they're using is still the same software as 10 years ago when we didn't have hybrid work as the main fixture of how we operate. So something still is, is yet to completely go and, and actually change, um, and make these markets, you know, continue to evolve. So you got hybrid work. Uh, you know, everybody knows everything's going to go digital. There's literally not going to be, you know, anything other than a digital transaction. So think about all the software that has to get written To go and help every company and every industry and every size organization all around the world be able to process everything digitally. We're still in the very early endings of that. Um, and then you've got the mega tailwind and just, you know, tectonic shift of security, privacy, you know, global data privacy challenges that, that every organization is facing. So you compound those three things and, and there just have never been more tailwinds in enterprise software than right now for, uh, for this, uh, this t…

AI assessment note: “It is because if you literally look at people's vendor stack”

Q So you went from So you got pretty far spending really zero percent of your time directly interacting with. So is the learning that you would have done more?

A I would have done a lot more. Um, and I, I think we got away with it because we could be our best customer. So we were, we were sort of our own company was scaling at the rate that our customers, uh, environment sort of adopted. Um, so like when we were 200 employees, you know, our biggest customers were maybe 500 user deployments. So we kind of just knew like, okay, what is the security you need? What is the content management capability need? Um, and then, and then it started to really, the, the size of our customer started to dramatically outpace our own ability to sort of, um, you know, uh, uh, kind of, uh, assume or, or, or kind of guess what was right for them. And this is the really hard part about enterprise software versus consumer.

AI assessment note: “I would have done a lot more.”

Q Does that increase the value of your business? When I think about that, I, I asked Aaron from Monday, if you become, you know, a data repository, which agents crawl on top of, how do you retain value in that? I would ask the same to you with respect.

A It's, it's, it's the question on the mind of every investor on the planet right now. So we're, we're used to it and it's not a, it's not, it's not a scary question. Um, one thing that, that helps us is we've always had a, a, an API sort of, maybe not first, but equal strategy. Um, uh, if, if I told you the number of API calls we did last year, you'd, or you guessed first, you'd probably be off by an order of magnitude. Um, uh, so, so the volume of, of API usage on our system is already enormous and already, you know, is outsized relative to any of the end user interactions in the system. Um, and that's just a virtue of you use content in a variety of applications and workflows that, that, you know, far exceed what, what people, you know, kind of, you know, Open up their finder and upload a document to like, like an ERP system generates files, a, a wealth management portal. You have clients uploading documents into the portal and they never see box. Um, you have workflows of invoice processing that's happening behind the scenes. So the headless version of box has been alive and well for, you know, almost since the day we started the company. And so agents to me, just again, represent a force multiplier on that. So it's not a, it's, it's, it's actually an exciting proposition for us. We already know how to monetize it. The question is like, will the exact dollar and cents be the …

AI assessment note: “agents to me, just again, represent a force multiplier on that. We already know how to monetize it.”

Q No, I get you totally. Is that anything that you think we don't spend enough time talking about, or there's not enough light shone on in the AI discussion and that we haven't discussed today?

A To me, there's just interesting downstream, um, kind of consequences if everything plays out as, as it should on like on paper. So, so, you know, I, I'm fascinated by like, I'm fascinated by the idea of, You know, what SAS did was it made it so I have a friend who has, uh, he sells balloons online. Um, and it's actually like not a bad business. It's like a, like it makes real money. Um, and he sells balloons online and, um, and I don't think he would have started the business if Shopify didn't exist. Um, like, I, like, I think like the existence of Shopify made it so he could like be like, oh, well I had this like random idea. Let's just see if it works. It lowered the barrier. To then going out and, and basically starting a business. And I, I know that Toby has, you know, thousands or tens of thousands of these types of stories. So, you know, if you think about it, you know, if Shopify caused businesses to get started because it lowered the barrier to being able to sell online, if AWS caused applications to get started because, because I was like, oh, I could just build an app and, and run it in the cloud. I don't have to think about servers anymore. Um, if, uh, if Stripe, you know, cause businesses to get started, cause I don't think about payments anymore. Then in a, in a land of AI agents, you can almost similarly be like, well, you know, somebody literally one day could ju…

AI assessment note: “there's just interesting downstream, um, kind of consequences if everything plays out”

Q No, I get you totally. Is that anything that you think we don't spend enough time talking about, or there's not enough light shone on in the AI discussion and that we haven't discussed today?

A To me, there's just interesting downstream, um, kind of consequences if everything plays out as, as it should on like on paper. So, so, you know, I, I'm fascinated by like, I'm fascinated by the idea of, You know, what SAS did was it made it so I have a friend who has, uh, he sells balloons online. Um, and it's actually like not a bad business. It's like a, like it makes real money. Um, and he sells balloons online and, um, and I don't think he would have started the business if Shopify didn't exist. Um, like, I, like, I think like the existence of Shopify made it so he could like be like, oh, well I had this like random idea. Let's just see if it works. It lowered the barrier. To then going out and, and basically starting a business. And I, I know that Toby has, you know, thousands or tens of thousands of these types of stories. So, you know, if you think about it, you know, if Shopify caused businesses to get started because it lowered the barrier to being able to sell online, if AWS caused applications to get started because, because I was like, oh, I could just build an app and, and run it in the cloud. I don't have to think about servers anymore. Um, if, uh, if Stripe, you know, cause businesses to get started, cause I don't think about payments anymore. Then in a, in a land of AI agents, you can almost similarly be like, well, you know, somebody literally one day could ju…

AI assessment note: “To me, there's just interesting downstream, um, kind of consequences”

Q Very, very fair. It does seem to be, uh, a topic, uh, that's top of mind though. And again, I can, it'll be that, that tension between like the tech ecosystem, Silicon Valley, where like token maxing is, is really a thing, whereas large enterprises, uh, are worried about, uh, costs. So what do you hear and, uh, what do you recommend people? Do your customers.

A I don't know if I have good recommendations that actually, um, but I would say the token, the, uh, when we go and talk to organizations right now about where they are with agents, uh, tokens, the cost of tokens and budgeting and budget planning and all of this probably is at least one third of the hottest button issues that relate to AI. Um, and it might even be like tied for number one, like half the time, because what they've seen is, is this move from, You know, everybody started calling it like we were doing subsidization as an industry. I don't, I don't really think about it like that. I would say that the costs were just low enough that these things were included, like cursor just included, you know, a lot of usage and maybe it was subsidization, but it was actually just like they could model that under their subscription fee, um, you know, in a, in a, in a fairly clean way. And then all of a sudden what happened was these agents just can do way more work. Their context windows are way larger. The cost of inference is way more because they have way more parameters and their capabilities way better. So, so we've just gone from, you know, like the, a pricing model of a chat bot or like type ahead functionality and get up co-pilot to a, to that pricing model no longer working when, when one, you know, coding agent could be consuming, you know, a thousand dollars of, of compu…

AI assessment note: “when we go and talk to organizations right now about where they are with agents”

Q It's just a, just a DLP problem at worst, right?

A Just a DLP problem. And honestly, like in many ways, not that different from somebody going to Google to say like, I want to go research this customer versus going to chat to BT and say, I want to reach us to kind of like, like almost nothing has changed about the security paradigm of that enterprise. So maybe the prompt could include a little bit more IP, but like, But like the work you were doing was not like, like that, the blast radius of that work was, was kind of quite contained. Conversely, I go to an agent and I happen to have access to the Salesforce MCP server. And, um, uh, and, and it's, it's actually incredible. And it's actually one of the reasons why I totally believe in headless software, but I can do like, I could do a lot of work with that and I could pull out a lot of data and I can ask a lot of very powerful questions. And a company is going to have to say, well, should every employee have the same level of access? And how should we make sure that we've cleaned up our access controls for that? And how do we tell people again, like what types of queries should they be doing that are going to have different kind of cost profiles? And now you have to do that for each of your software, you know, vendors and applications. And then you have to figure out, like, what is the new workflow on the other end of this? Do you really want employees prompting, you know, thei…

AI assessment note: “Just a DLP problem. And honestly, like in many ways, not that different”

Q might kill me for this, because he gets a little bit more sensitive about when I quote him or misquote him more appropriately, but like, he basically says, It, and this is Jason again, if you can't, like, charge way more for your agent product, That Wall Street doesn't give a shit that you have to re-accelerate revenue with agent products. Can you charge significantly more for an agent product?

A The answer is yes, but, but there's a little bit of nuance, which is our, our business model is we have a new plan tier that we just introduced last year that basically houses our, you know, best workflow capabilities, our business automation, you know, uh, our app application development capabilities. And then the agent is sort of central to that. Because it's going to help you automate the work that you're actually doing with your content. So it'll read a document and extract metadata from it. It'll process information inside of a, of a, of a workflow. So that is actually causing a real reacceleration of our revenue growth. Last year, we, we, we saw an inflection in our revenue growth. And so that, that it's already happening in our business. Um, and, and so we are, we're doing the thing that I think Rory is sort of probably saying is the new benchmark. Now to be Fair to what's, what's happening though, is I think Wall Street still is sort of saying, we kind of need to just step back and see where everybody lands in this because of how much change there is. So, um, so this is very much a year where if you're in software or infrastructure or building agents, you just, it's a year of complete unrelenting execution.

AI assessment note: “The answer is yes, but, but there's a little bit of nuance”

Q here's my computer, have my files, take actions on my behalf. And, and honestly, they work better when you take the guardrails off and trust them to do things for you. Um, do you think we're like, again, for this product vision to work, that has to happen. Do you think we're in a place where it's feasible for people to give up that type of control to these bots?

A Well, so this is, this is where the diffusion, this general category is where the diffusion will be longer than, than where people in Silicon Valley think. So if you're in Silicon Valley and, you know, every tweet that you and I read, you know, that goes viral in, in the Valley is, is often It's coming from like a 10 person startup. They have, they have basically like, they started from a completely clean slate of, of the way that they work, that their environment, the tools they use, the data that they have, and they can just, they can build their organization around, around getting, uh, output from agents. And, uh, you go to the rest of the world, take a company that has, you know, 10,000 employees, been around for, you know, decades. Their data is in, Again, 2030, 50, a hundred different systems. The, uh, if you go and ask that company, um, where are your latest, you know, contracts for this client? It could be in five different places. If you go and say, where's the latest marketing campaign assets? It could be in 10 different places. If you say, where's the research for the new, um, uh, for that new breakthrough that you're working on, it could be in, you know, five different repositories. So the challenge is if you're in, if you now want to go deploy an AI agent in that environment, Uh, you can almost think about it like, like a new employee joining that company and that …

AI assessment note: “this general category is where the diffusion will be longer than”

Q then we're presenting that In Slack to our team. So this is coming fast and furious, and we spend, I don't know, probably 15 minutes on each of those incoming applications to start doing the math on that. Try about 5000 hours of work. Aaron, what are you seeing on the street? What are you doing at box in terms of agents landing right now in Q two of 2025?

A Uh, yeah, I mean, I think, I think Saks represented it well, which is, which is, you know, you have to now think about AI as, as effectively being able to do anything on a, on a computer or another piece of software as, as a human can do. And the little distraction that, that I think happened two years ago after the ChatGPT moment was we sort of thought about that as, oh, we're just gonna, you know, do like typing information retrieval. And that's a new paradigm for user interfaces, let's say. So you just like talk to your software and you like search Zillow via chat. That was sort of a little bit of a distraction that that's super helpful, like when you want basic information, look up or whatnot. The big breakthrough is starting to think through these things as, as full, you know, effectively, uh, uh, you know, agentic systems that, that operate on any amount of data, any amount of tools for as long as you want to complete any tasks that you want. And this is sort of the big year where agents are starting to, you know, enter the vocabulary of enterprises of IT people, Of, you know, larger and certainly smaller organizations. Um, and, and it kind of requires you to have a little bit of a, of a reset moment on how you think about AI, which is, which is, it's not just now a kind of a co-pilot that you talk back and forth with. It's actually something running behind the scenes. Th…

AI assessment note: “this is sort of the big year where agents are starting to, you know, enter the vocabulary”

Q All right, let's get into, um, all the, uh, awesome things that you guys have been building at Box over the last couple of years. Uh, maybe give us a tour of, uh, from hubs to agents. Uh, what are the different moving parts?

A Yeah. So, um, so the way to think about Box is we're a platform that helps you store, share, manage, collaborate on data. We have a layer of, you know, security. We have a layer of file permissions. We have a layer of data governance. So that's what we've been working on for, you know, basically two decades. What we added was a layer, uh, which is just, we call it the AI platform. Uh, and it has kind of all the plumbing that you would expect you would need to do to be able to work on content in an AI. Uh, in an AI, uh, uh, context. And so, uh, so what do you need to be able to do? Well, you need to be able to like, you know, uh, some of it, some of it, by the way, benefits directly from other use cases that we've had. So for instance, for 15 years, you click on a document, you see it in your browser. Well, why is that possible? It's because we have a conversion engine, takes the Word doc, makes it into a PDF. We stream the PDF to the browser with, with PDF JS, and, and that's how you get it. Well, guess what? In that process, you've extracted, we've, we've, we, we can easily do text extraction. We can then do the embeddings on that text extraction. So that's a service that, that largely was built out for a different reason that now we kind of have as a standing start. We then put that into a vector database. Um, uh, so now we do, you know, we have, we have a layer that does the…

AI assessment note: “What we added was a layer, uh, which is just, we call it the AI platform.”

Q What is not working yet with agents? You know, a lot of people talk about how, uh, if you have chain of agents, then you end up with compounding errors. Have you experimented with that?

A Yeah, we we've seen every problem that that anybody's ever heard about. Um, so, uh, uh, You know, the more, the more agents you have, obviously you're like adding probabilistic on probabilistic on probabilistic. So like, good luck, like, you know, with, with what that could lead to, um, uh, you know, general search problems still exist, uh, at the end of the day, a lot of AI will be dependent on search technology and, uh, the quality of the search index, the quality of the ranking, uh, you know, most of our biggest ideas and biggest problems intersect with search. Um, and so, and so, you know, the moment that the AI finds the wrong thing, you know, the entire, your path dependent now on the wrong thing. So, so it's going to just make a whole series of, of bad decisions because it found the wrong thing as the, as the starting point. And we can just see this in our, in our personal lives, you know, using AI. It was funny. We asked a, um, we just do this, we, you know, a funny test. We said to every AI, uh, uh, kind of search product, um, uh, for consumers, we said, if you just do a query as simple as, as simple as, Tell me the last time, the last five times that the giants beat the Astros on a Tuesday. Okay. So you've got like, like, you know, a very complex problem in terms of the data set that has to be kind of combed through and then looked at from a logic standpoint and all o…

AI assessment note: “Yeah, we we've seen every problem that that anybody's ever heard about.”

Q I'm curious, um, as a public company CEO, um, Uh, not just, uh, you know, tariffs, but, um, how do you navigate uncertainty and volatility in public markets? You've, you've, you've been a public company CEO for 10 years now. Yeah. Do you worry about, uh, the ups and downs of the stock price, or do you have such a long-term view that it matters less?

A Well, uh, depends on if I can decouple the stock price from a more technical, uh, uh, you know, actual issue that, that we're dealing with. And so, I would say, I'm less worried about the stock price in the sense of moving because of, of Wall Street trading up or down and any particular, uh, you know, for any kind of particular reason, but, uh, very worried about, about the embedded issue that, that might be related to that. So, you know, let's say sometimes it's self-caused. So we have to execute better in a particular area. And the stock price in those situations is just, uh, another, uh, it's a symptom of the, of the actual thing that you're dealing with. And, and it's your kind of like, you know, real time KPI of, of that problem. And then in the case of tariffs, the thing that, that, you know, scares the living, you know, heck out of me is, is just actually the economic impact that this would, this would have. So I don't really care about the stock price, you know, it per se, I care about the health of, of the country economically. And then obviously there's lots of follow through that, that would happen and ripple effect that would happen if, if as of, you know, Tuesday, Uh, afternoon, you know, the, the tariffs that have been proposed, if those roll through, um, uh, you know, this is going to be a total disaster. So hopefully, whenever this airs, we'll be able to look ba…

AI assessment note: “I'm less worried about the stock price in the sense of moving because of”

Q think that, um, these guys are going to be successful in. Tearing down all of this infrastructure inside the United States? Do you look forward to it? Do you think it's has a chance? What do you. Um, so, uh, are we talking, maybe, maybe more pointedly, like, is it hard for you to do business in the United States in ways where you wish that it would be easier?

A Uh, we're, we're really lucky. I mean, in the land of bits, it's, uh, it's about as, as simple as it gets. Um, I think where, where we clearly have a crisis is, uh, energy, transportation, EVs, anything autonomous. You know, you can, you know, list 20 things that, that run into just unending regulation. You have the state regulation, you have the federal regulation, um, you know, it's just endless loops that people go into. Um, do you, ah, so, so like no matter what, we need to go and solve that. Actually, I felt like Kamala was one of the first sort of Democrat presidents that had that as a message. It was like not the most expansive part of the message because there's like 50 things you have to get out in three months. But she talked about red tape, she talked about we have to beat China, we have to move faster, all that. You know, in, in the, in the Trump outcome scenario, you have obviously Elon as this sort of superpower that can go and drive a lot of that way faster. I'd hope it's kind of applied somewhat surgically versus a total hammer because, um, uh, I just think there's, there's, you know, like, I, I think having some degree of thoughtfulness of where can we go and, you know, create these fast lanes for innovation and for acceleration, I think is a good thing. Um, uh, but, uh, but yeah, like getting drugs approved faster, building more, building more houses. It's ins…

AI assessment note: “in the land of bits, it's, uh, it's about as, as simple as it gets”

Q Final one. We've talked about regulation, we've talked about model quality, um, that you've tweeted before about kind of the job displacement concern. If there was one thing that did worry you, what would that be?

A I think we have ways of defending against this, but like, you know, you can, You can, it doesn't take like that much imagination to be like, ah, you know, one of those like robot dogs with like a gun and like, you know, and a multimodal AI, like, wow, wouldn't want that thing running around. So, so I, I think there are real reasons we should, you know, sort of pay attention to some, some of the, the, uh, more, um, uh, you know, uh, dangerous use cases of AI. I just think we have in many cases sufficient, uh, Legal frameworks for addressing those things. And, and then for any net new one that we come up with, let's, let's actually, you know, have, have regulation to go and support that. But what I'm, I'm less worried about at the moment is probably the more fringe extreme things of the AI sort of self-replicates. It, it sort of, you know, jumps over outside the data center to another data center and then self-propagates. And I'm, I'm less nervous that that is, is sort of on the, on the docket of events. And so.

AI assessment note: “one of those like robot dogs with like a gun and like, you know”

Q Can you not micromanage at scale? Jensen Huang has told us with 60 direct reports. Who fucking needs to delegate?

A I, I cannot wait until we're a two trillion dollar company and I will be able to, I will be able to go back into that mode. Um, I'm in a brief period where I have to delegate to keep people happy, but, um, uh, but eventually we will, we'll be back to, uh, to, to that land. Um, I, I think, I think that the real lesson is now is, is you choose the areas that you, you need to exert that level of involvement. So, um, and in places like, um, you know, let's say critical areas like AI or, Or end user experience and, and some product, you know, strategy, you know, you, I, I still kind of revert back to, you know, early startup self, but there are many areas where just honestly, either because of the amount of hours that the job takes, um, or just the fact that like, you want to be able to bring on great people that, that are motivated to go execute, uh, delegation is actually extremely important.

AI assessment note: “you choose the areas that you, you need to exert that level of involvement”

Q There's many points I want to touch on in that one. Do you think we're still in the experimental budget phase for enterprises? We mentioned there about how we can change functions and optimize them. Do you think we're still in the experimental budget phase and how will the best and the worst enterprises engage and adopt with AI?

A I think there's two types of spend happening. Um, there's probably the bulk of the dollars that you see in the headlines. I would argue are likely experiments, uh, where, you know, you'll have some kind of hit rate success rate, um, that, that happens. And then those experiments graduate into production spend. And I think we just don't have a, an accurate kind of pie graph yet of what's in the production category versus what's in the experiment category, but it would be, it would be probably too generic to say it's all experimental and it's certainly not accurate that it's all production. Um, and so the exact sort of split of those two things is, is sort of hard to diagnose at this point. Um, I've just been on the, the road. Uh, we've done maybe about a dozen or so AI events, um, uh, throughout the US, um, you know, in the past quarter, the vast majority of companies have, have a meaningful number of AI experiments happening with, with lots of different, you know, kind of areas of their business, lots of different applications. Um, uh, but the vast majority also have, you know, uh, areas that are in production already. So unfortunately it all would get lumped into the same Kind of category of AI spend by the time the CFO, you know, gets the AI bill, but we, we are seeing real production and, and lots of experimentation.

AI assessment note: “we are seeing real production and, and lots of experimentation.”

Q Can you not micromanage at scale? Jensen Huang has told us with 60 direct reports. Who fucking needs to delegate?

A I, I cannot wait until we're a two trillion dollar company and I will be able to, I will be able to go back into that mode. Um, I'm in a brief period where I have to delegate to keep people happy, but, um, uh, but eventually we will, we'll be back to, uh, to, to that land. Um, I, I think, I think that the real lesson is now is, is you choose the areas that you, you need to exert that level of involvement. So, um, and in places like, um, you know, let's say critical areas like AI or, Or end user experience and, and some product, you know, strategy, you know, you, I, I still kind of revert back to, you know, early startup self, but there are many areas where just honestly, either because of the amount of hours that the job takes, um, or just the fact that like, you want to be able to bring on great people that, that are motivated to go execute, uh, delegation is actually extremely important.

AI assessment note: “you choose the areas that you, you need to exert that level of involvement”

Q And I know maybe this is an obvious question, but it might shock people, uh, that, that listen or watch. Is this the world we're going to be in forever? This world where everyone's just got to be more efficient than we've been in years. It puts pressure on sales comp. It puts pressure on marketing budgets, or you think things will reflate a little bit across, across assassin cloud.

A I think, I think it would be, it would be healthy if they didn't reflate too much. I think it would be healthy if, if they looked like when you and I were, were doing this and it was like, you know, you were, you were trying to get a six to eight X multiple. Like that was, that was fantastic. Like, and, and like the only problem with the, the, the market is just like the moment that the market sees something that's growing 50 or a hundred percent, they just, they get, they get overly excited and they instantly Jack it up to 15 X, you know, multiple or 20 X for multiple. And in some sense, it makes sense because you're, you just, if you can just, you know, extrapolate out two extra years, then maybe you're willing to pay that extra dollar for that company than, than the other, than the other investor is. Um, but ultimately when you do that indiscriminately across categories and across software companies, you get, you get these bubble dynamics. And I think, I think where Wall Street kind of got it wrong is, is they were treating literally all software the same. Again, indiscriminate of, of what's the gross margin? What's the, what is the, you know, contract value size? What is the renewal rate of that company? Is, are they doing five or 10 year deals or are they on monthly billing? And like all these things end up sort of compounding over time one way or another, where service no…

AI assessment note: “I think, I think it would be, it would be healthy if they didn't reflate”

Q always you who takes them. It's sometimes team members. My question to you is how do you create an environment of safety, especially as a public company in a sizable organization now where people have the ambition to take big bets and aren't afraid of what happens if it goes wrong, but also don't feel no accountability. It can't be free reign to fail. How do you bridge that balance?

A A huge challenge, and I don't know of a company that has sort of perfectly optimized, you know, this particular variable. I would say, you know, a couple things to keep in mind. One, whenever possible, have as ambitious of a goal as possible, and so goal setting should be sort of ambitious and idealistic in terms of what you're trying to achieve. That is, needs to be separate, though, from sort of like what maybe we would consider like harsh accountability, i.e. you're going to get fired or down-leveled if we don't achieve that goal. So, so that sort of job number one is ambitious goals, but reasonable sort of accountability, you know, around achieving those goals. So that way people are willing to sign up for them and aren't sort of afraid of putting ambitious, you know, statements out there. You know, obviously you need a certain degree of autonomy to ensure that people can actually go and execute on the ambitious goal. You know, we've had a lot of situations where you might have an incredibly ambitious individual, an incredibly ambitious goal, but there's still a sort of a morass of, of complexity that ends up slowing them down. So they Could not have even achieved that goal in any perfect scenario because of the bureaucracy or interdependence on other kind of, you know, functions in the business. So, so you had to also, you know, make sure that you've wired up the team and …

AI assessment note: “ambitious goals, but reasonable sort of accountability, you know, around achieving those goals”

Q I do want to finish, though, on what the next five years hold for you, and what does the next chapter of success look like? We have this interview in 2026. Where do you want to be then?

A I personally think we're at one of the most exciting points of the web, and it's Direction going forward that I've ever seen. So if you think about how much, you know, compute we have to work with, how many new amazing APIs we have to work with, how much the internet is becoming more real time, more collaborative, more multimedia driven. Software is going to be more multiplayer and more real time. So I think in three years or four years or five years from now, I think we can expect more immersive applications, better collaboration, being able to do completely new things with our data. Maybe some of that will be driven by AI. Maybe if it Some of it will be just driven by completely new formats that we work with, and our job at Box is we just want to be a platform that helps people work with their content in that future state, and we're going to continue to stay focused a hundred percent on that and not deviate from the strategy.

AI assessment note: “our job at Box is we just want to be a platform that helps people”

Q Well, that, you know, it is interesting. Everyone needs, everyone needs a wedge. A, a 10 x feature, right? And so that, that, that ism, that trite ism of a, a feature versus solution is pretty stupid if you've been out in the field, isn't it?

A It's, ah, it is because the, the, you know, your, your, your, especially incumbent competition is always trying to deposition you as a feature, and, um, but, but the, what they don't realize is, you know, hopefully what you're building behind the scenes, and I think the thing that, that I look back on is, um, ah, as maybe one of the biggest lessons of this, of that journey, Is architecture matters more than almost anything else you can imagine, uh, in that journey. Because if your feature is then completely disconnected to the next feature, and then thus the next feature, then you really aren't on your way to building a platform. Uh, and so we, we made a bunch of, now in retrospect, kind of lucky, fortuitous decisions in our platform architecture that were not intentional. We just, we just lucked out that we made them the right way, and then eventually they started to become much more intentional because we knew that we were building a platform, but, um, One of the small things that you really actually, it's worth paying attention to even when you're just three people in a garage.

AI assessment note: “It's, ah, it is because the, the, you know, your, your, your, especially incumbent competition”

Q Even now. Yeah, it spends a year for Box to get through that, right?

A Yeah, CR Financials. So, you know, you spend a lot of money, Because not everybody buys this stuff on day one. So for sure. So you have to spend a lot of money to invest in working with these customers. And so for, let's say a year, all of the time around auditing, testing, selling, marketing to GE is unprofitable. And then, and, and then we're just, you know, praying every night that that GE, um, you know, kind of comes on board and agrees with our strategy and, and then, and then converts. And so, um, so we've done a lot of that work now. For a large number of enterprises. So if we can hopefully save people on, on that time and energy and instead let you focus on, um, building a world class mobile application or a world class, you know, workflow application, um, then, then, you know, hopefully, uh, we can actually drive way more innovation in the enterprise. So that, that's our, that's essentially our, uh, our, our platform model and our, uh, our API model right now.

AI assessment note: “for, let's say a year, all of the time around auditing, testing, selling”

Q Who is going to win the enterprise race, OpenAI or Anthropic?

A Oh god, that, that's impossible. Back to the cloud piece, I think, um, you know, I think it's, it's totally fair to think about it as a race, and certainly if you're, if you're in either of those companies, you have to treat it like a race, because, because, you know, like, you obviously want 80% market share, not 55% market share. So, like, you have to treat this as a, you know, we gotta dominate, uh, that's exactly how, they, they should be executing that way, everything is going according to plan. If you compare it to other areas of compute, Um, and I, I ran this analysis recently. In 2010. 2010. Not, like, you know, maybe you were 12, but, like, the rest of us, we were just, like, in companies doing things. Uh, in 2010, AWS made five hundred million dollars in revenue. Azure had just launched, and GP, and GCP was called Google App Engine, and it had a little, like, a turbine logo, uh, with, like, wings or something. So, that was the state of cloud. Fast forward to this year and it's a couple hundred billion dollar a year revenue ecosystem, right? So, so in 15 years, right? So, and we were in that moment being like, who's going to win? AWS or Azure or GCP? What's, how is this all going to play out? And it just turns out the market was so large, like obviously it was due to their execution that they kept it going and kept it large and the competition kept up, but it, it just …

AI assessment note: “everybody kind of won. And so I, I sort of think of AI in a similar fashion”

Q And then we're gonna unpack. Yeah, we're gonna unpack that. Aaron, your thoughts on the first hundred days? Obviously, you are a Democrat, and, uh, you were pretty vocal, not in support of Trump, so what's your take on the first hundred days? Any, any bright spots for you? Things you, you know, support?

A Actually, uh, Sax's world I'd say has, has been a bright spot. So especially, I mean, I think we have a very clear message on AI and, uh, and that, that is, that's been, I think a huge net positive is, um, you know, if you look at the, the past, you know, few months, uh, out of all the, the AI push from the administration, it's unmistakably, you know, pro open source, you know, pro, you know, bring as much AI innovation, you know, to the U S obviously the, the tariffs, you know, add a little bit of a headwind to that. I have some very strong asks, you know, around high skilled immigration, because I think that, you know, AI talent is going to be super critical to, to actually win the AI war. So, so I'd say that, that directionally has, has had some positive momentum. You know, from my perspective, this is kind of playing out, uh, almost exactly how I thought it would six months ago. And then three months ago, I, I think there was some signs that maybe, maybe, you know, it wouldn't play out this way, um, just based on some of the Some of the, you know, kind of early groups that were coming to the White House, the, the, the, the, the sort of deep business, you know, kind of centricity of the White House, you know, I think it was day one or two that Stargate was announced, you know, at the White House, we're going to go build massive infrastructure. I think the case I'd like to ma…

AI assessment note: “Sax's world I'd say has, has been a bright spot.”

Q Over the last, uh, couple of days, uh, Toby from Shopify had this very interesting tweet that I think you commented on, uh, about how he's, uh, effectively making AI usage, uh, mandatory within Shopify. I, I, I, is that something that you do that, uh, how do you, I guess, create an AI culture, uh, within Box?

A Yeah, so, uh, we, we have told everybody in the company that we wanna use AI, uh, to be as Productive as possible and aggressively use it, um, uh, across the business, you know, with an asterisk on, on certain kind of production use cases and whatnot. Um, and, uh, we, we do internal things where we, we have, uh, members of the team, uh, show up at our, our kind of internal all hands event, um, which is a weekly kind of, uh, a video call show what they're using AI for within box, uh, how it's helping them. So we're trying to get everybody's kind of just Just, you know, kind of creative juices flowing. I thought Toby's memo was fantastic. Um, it was, it, it, it hit on all of the, the, basically the, the kind of the, the, the core topics you need to start to think about as a company. Here's how we should start to experiment. Here's how we should, uh, you know, do product development. Here's how you should be thinking about, you know, when can this augment, you know, how we work and move faster. Um, so, uh, so I thought it was a, a great conversation starter for, for a lot of folks.

AI assessment note: “we have told everybody in the company that we wanna use AI, uh, to be as Productive as possible”

Q And you think that's, uh, mostly the chat GPT moment of like people seeing this in their, in their lives? Yeah.

A Without chat GPT, none of this would have happened. Um, now maybe, you know, a different timeline, somebody else would have done chat GPT and Gemini would have launched first and whatnot. So we, we could still have been on this timeline. I think somebody would have figured out like, Hey, why don't we put what, you know, GPT three into a chat wrapper, but like it could not have happened in a better sequence that it just exploded. Consumers got it. The next generation workforce Is like fully addicted to this stuff. So what, what, you know, you have, you actually have two really interesting pressures that, that are, I don't know if they're totally unusual, but, uh, but they, but this didn't happen because in cloud, maybe it happened in mobile, maybe it happened in PCs, but what happened, maybe it happened in internet actually. Um, uh, I just wasn't in a corporate environment to kind of feel it, but, but you have like the CEO is sort of like, Hey, what are we doing about AI? And then you have the new workforce coming in and they're like, I don't know how to work. Like if I don't have like a thing that can like help me answer questions and autocomplete stuff and do this, you know, like, I can't believe you guys type all these words out. Like, what are you doing with your time? Like, like it will actually, you know, it's, it's, I'm going through a journey mentally of this whole thing…

AI assessment note: “Without chat GPT, none of this would have happened.”