The Exchanges, every show

Q Uh, what's, uh, what are you guys doing in, in, in some granular detail, uh, around agents? What's, uh, what are you building? What's working? What's not working yet?

A Yeah. So, um, so, so back to the whole kind of layer of the, of, of, of how we think about an agent internally so far is, and these are the kind of core primitives, um, you've got access to data, you've got the user permissions, you have a set of tools in box. The tools right now are things like, um, uh, you know, crack open a document and, you know, feed the model, um, you know, uh, uh, you know, chunks, uh, based on the user's query, Uh, search is a, is a tool we're working on. So you have a set of tools, and then you have the model. And then we're adding, you know, kind of an agentic workflow layer as well. And in combination, you can just think about it as, you know, agents for content. And so whatever you would, whatever you think a human does with, with documents and content, we should have an agent layer that lets you build, build that exact thing. And so what's amazing for us, and this is where I get most excited about AI, is In our business, I'm going to make up all the stats. None of the numbers are exactly real, but I would argue that probably for 95% of our data, people have things that they would love to be able to do with that data that they just don't ever do because it's too expensive. It's too time consuming. They didn't think to do it. They don't have a person with that expertise to do it. And so, and so basically it kind of means that like 95% of your data is…

AI assessment note: “you've got access to data, you've got the user permissions, you have a set of tools”

Q Do you think Google smashed it last week?

A I do. Yeah. But last week, even to me could be kind of like condensed as just like another week of awesome AI updates. Um, I'm not sure that, that, that I, I'm not sure that I can sort of pull out like, like this is the one thing that will set off a new trajectory of AI. Like, like, You know, there were agents, there were better models, there was, you know, multimodal, like all great stuff, but what, but the, the thing that I think it underscores that I think honestly, uh, uh, cloud next did as well is like, you know, Sundar has said a message to the company that AI is the number one, most important priority of all things. It's like 10 times higher than every other level of everything else you're working on. It's gonna be like the new way to search. It's gonna be the new products in cloud. It's gonna, you know, It's going to be in workspace. And I think that message is, it was very important. It is now very clearly like the evidence of it working is now showing up. And, um, and I think, I think, you know, Google IO is merely the, the, you know, another moment of it manifesting that, that, that, that company has religion now, uh, on AI.

AI assessment note: “I do. Yeah. But last week, even to me could be kind of like condensed”

Q Fascinating. What do you recommend that people do in your conversations, given this litany of Things that need to happen and the space of innovation, all of it happen at the same time. You mentioned internal FDs. That's super interesting. We can talk about external FDs, which I think is a better understood thing. Where should people start or how do they accelerate?

A So the one part where I'm just like, I, you know, I'm a, I'm a hammer looking for nails is I see most things as a data problem, um, uh, and, and, and data with associated things like access controls and like how well defined is the workflow, et cetera. So most agentic challenges, I, I think are kind of inversions of, of, of basically like you have a data challenge, like the agent can't get access to the right information to do the work. Uh, maybe they have access to too much information, in which case then, then they're just going to like roam around and do the wrong thing, or they have access to too little information, in which case obviously they're not going to work, or they don't have enough context to be able to execute the task. And which means they need more information You know, surrounding the task. So, so we, we see data problems everywhere, um, that, that we look. And so I think one of the first steps is like your enterprise just needs to be prepared from a, from a data standpoint and from a, from a kind of a core architecture. And I think we, for 20 to 30 years in IT, it was sort of okay to, to sort of have all these systems, some redundant, some not well managed. You could kind of throw humans at the problem and just sort of say,

AI assessment note: “one of the first steps is like your enterprise just needs to be prepared”

Q Aaron, we were talking about the Meter paper, and it was, the paper suggested that their developers were actually less productive with AI, but that doesn't square with your experience talking to a lot of different startups, seeing a lot of different startups, and how they're so much more productive. So, why don't you talk about where, where you're seeing startups say they're more productive, and why is it happening?

A Yeah. So I'll, I'll first just represent our own case study and then, and then there's the really extreme version. So, uh, our own case study is we've adopted a few different kind of, um, AI coding tools. Um, uh, you know, cursor being a, a super, super popular one internally. And I, you know, as I talk to people, let's say in the hallway who have, you know, yeah, maybe they're trying to get me excited by AI, but like, I think they know I'm, I'm bought in. So, so the, the kind of Qualitative answers I get from, from people, and then I'll give you our, our internal metric. You know, some, some people say I'm getting, you know, a 20, 30% productivity gain. Other people will say 75%. Um, interestingly, I have not been able to pinpoint the demographic difference, uh, on the answers.

AI assessment note: “we've adopted a few different kind of, um, AI coding tools. Um, cursor”

Q It's all partisan, none of its first principles, right?

A I mean, for these people, for this group of people, which isn't everybody. That's going to be true of both sides. Like Michelle Obama, Michelle Obama was like, let's get kids healthy. And all of a sudden now it's in vogue to do that. So, so I, I think, I think we're just in an environment where, where any, anything will become partisan. What's interesting is, is that because of the, you know, some of the, the cross party elements of, of, of Trump and now his cabinet is it might pull in more, More of the Democrat party than, than would usually happen. And, and I think because of Elon and the people that are surrounding Trump, you probably have a bit more air cover for the Rocanas of the world to also step up because if it was like Steve Bannon and Trump doing Doge, it would be like, ah, okay, you know, maybe this is not the thing to, to, you know, lend credibility to for, for pure political reasons. If you have, you know, some of the best entrepreneurs that are, that are out there actually like literally in the cabinet driving this, At some point, you know, it is an IQ test if you're, if you're on board or not.

AI assessment note: “I think we're just in an environment where, where any, anything will become partisan.”

Q So does this completely discard like Moore's law? Cause as you said, we've never seen that before and it's completely atypical compared to previous progressions.

A To be fair to maybe like a Moore's law, like religious, you know, you know, zealot, um, this is a sort of a different, uh, a different variable than, than what Moore's law is, uh, which is about the density of, of, of, uh, of your chip or the performance of your chip. So So this is more about model algorithms and, and how we're actually utilizing these models. There's actually a different law, which is sort of the GPU performance. Um, and I think there's a sort of a, you know, Jensen almost kind of created a law around this, but we have seen faster than Moore's law improvement on GPU performance. So, so the good news is we get a little bit of a reset on, you know, there's been a lot of talk on, hey, is Moore's law slowing down? Um, and GPUs kind of are, are giving us that That, you know, maybe next tailwind of, of compute performance improvement, um, which is this, you know, miracle that, that, uh, that we now get to, to, uh, to deal with. But, um, but I would say I, I'm seeing no signs of AI models, slow down, anything plateau in terms of the innovation curves, uh, that, uh, that we're seeing.

AI assessment note: “this is a sort of a different, uh, a different variable than, than what Moore's law is”

Q You know, when you look at their releases last week, you're looking at language learning cheaters and going, fuck, did you a lingo have a business anymore? And does language learning actually have an independent category of open AI is able to provide such quality.

A Open AI is kind of telling us what they are going to become, which is. ChatGPT is going to be this universal sort of assistant interaction, you know, interface, and all the, you know, subsequent tools to, to manage that and interact with, with different AIs that kind of come together there. And then they're going to have an API business that, that will be, you know, you can almost just, you know, very quickly, easily understand. It's going to be audio, video, text, like it'll, like, it's going to do all the formats of, of information with, you know, kind of complete intelligence on them. So then you're sitting around, you're like, well, what startup should I go build? You probably don't want to do things that, that instantly could be subsumed by a horizontal chat interface. And you probably don't want to do things in the model area that you might, might just be one training run away on their end of being subsumed by a, just a more superior model. So that means, I mean, I mean, this is sort of like, to me, it's the most exciting part of software to 80% of people. It sounds like the most boring part of software, but it's like, you have to do like the, the workflows That, that eventually a human who wants to go and run a full business process has to implement that doesn't want to just do back and forth chatting with a thing. So like to even to your tutor point, um, uh, or, or the,…

AI assessment note: “I don't think ChatGPT itself is going to become a language tutor.”

Q have to kick off with software, right? Um, you're, you're one of the thought leaders in the space, and certainly we know you well, and most people in Silicon Valley know you well. But maybe just, uh, level set, you know, quick reminder for everybody. What does Box do? What inspired you to get it started? And then, and then how it's evolving, you know, as you guys exit Zerp.

A Um, actually the Zerp thing, um, uh, I, I mean, I, you know, I know there's a lot of, uh, there's a lot of Zerp stuff going on, but we actually never really even had that much of a Zerp benefit. Um, I can certainly get into the different eras. There was, there was about a three-year period where we raised a ton of capital and we burned it. Um, and we did have a little bit of absurd benefit, but it was actually like on paper, exactly the right thing to do at that point. I got diluted a ton in the process as a result, but it was actually like strategically the most important thing to be doing, but, uh, history of the company super quickly, um, and kind of what we do. So we built a platform that helps companies manage their most important data, their financial documents, their marketing materials, their contracts, uh, their strategy, you know, content, anything that can turn into a piece of content we manage and store and secure. Uh, we have about a 115,000 customers, uh, 70% of the fortune, 500. And we started the company with a really simple premise. This was in 2004, 2005. When we got the idea, it was like right at the start where like you could put data in the cloud. It wasn't called the cloud then. And we did like crazy bridge rounds and all this stuff. I think we pitched bill like four times at that point, um, handily got rejected, you know, probably appropriate, probably ap…

AI assessment note: “we built a platform that helps companies manage their most important data”

Q 10 blue links that is just at its core seems somewhat at odds, um, with what perplexity is doing, with what ChatGPT is doing, the age of answers. Um, and so I, I would just love to, you know, kick it around for a second. How, if you're running Google today, right? And you're faced with this innovators dilemma around this, like, like what, what should they be doing here?

A Uh, well above my pay grade. Fortunately, I am just a lowly enterprise software. But, um, but you know, I, so, so as a reminder, obviously for everybody, um, like innovators dilemma is about business model, you know, difficulties. And we always, we always think it's a technology problem. It's always about your business model, um, doesn't make The, the new thing attractive to you. Um, and so you avoid doing it until you get disrupted. You know, I, I, I might take, uh, after, you know, uh, thinking about this a little bit, not, maybe not enough, is I don't think there's a totally, 100% classic innovator dilemma issue with, with, um, the move to AI with Google. Um, I think on the other end of this, uh, the business model could be as good, if not better. And Brad, you think about this a lot of like, Of like, if you, if you actually had Google literally tell you the thing to buy, um, and, and they got a transaction on that, it would actually be a similar business model. Um, they would just get you to that answer even faster and you'd still transact and you'd still do commerce and, and they are still the distribution engine.

AI assessment note: “I don't think there's a totally, 100% classic innovator dilemma issue”

Q I mean, you sat in the middle of the team, as I remember, like really in the pit with all the developers or wherever you are, right?

A I still do, but it's just, I'm in the office now, unfortunately less, less frequently. So, so, um, but for the first seven years, um, and, and this was, I mean, part of this was just consistent with our sales model. It was an inside sales model, Um, and, uh, and the people we were talking with really didn't demand a, an in-person meeting. Um, so, so we could kind of accomplish that, but, but actually I, I was, uh, rarely even on the phone with customers. Um, the, our, our real customer interaction was driven by our, our first set of, uh, head of sales, our first kind of set of sales individuals and, and sales team, and so I was super product focused. And then we had a sales operation. And, and, you know, we would meet, you know, almost daily on just like, hey, what are you hearing? What's going on in the field? What, what are customers asking for? And then we would, we would, you know, through, through, um, uh, you know, any means necessary, try and try and build the kind of things that, uh, that, that we thought were going to be important for these customers. And, uh, and, and that really worked up to a certain stage of, of, of, of customer, of customer sort of, Um, uh, kind of credibility.

AI assessment note: “I still do, but it's just, I'm in the office now, unfortunately less”

Q Uh, exceptional man, but I wanted to start, and we were just chatting, I was running around the park listening to the Dworkesh and Jensen episode, and I was like, I don't think Jensen came out very well. Do you agree with me that Jensen didn't come out very well from that episode?

A Um, I, I think this is like the greatest Rorschach test of all time of, of where, uh, where, where somebody is mentally on AI. Um, I, If I, so I happened to see a bunch of the tweets before I watched it. And so I was a little bit obviously biased in advance, but if I hadn't seen any of the commentary and I had just watched it, um, I would have been very confused by the, by the commentary post, uh, you know, post, uh, interview. And, and, um, to be clear, I kind of jumped to the more, uh, salacious part of, of, you know, China and that topic, but I'm, I'm almost probably 80% with Jensen. Um, and, um, and I, I, my, my sort of, uh, kind of way of thinking through the logic actually works much closer to, uh, to Jensen. Um, you know, the, the idea that we're in some kind of, you know, kind of race, existential race where a month or two of advantage is gonna, you know, change the total outcome of, of AI progress and, and what everybody does between us and China. I, I just don't agree with, I think what we are in is a commercial and economic race. Obviously with safety, you know, built into that, there's no question. Um, and I think we actually have a lot more power globally, uh, if it's our technology stack that's powering AI. And so I, I, I kind of am more in the camp of, of Jensen on, on his, on his lines of logic. And, you know, Dwarkech kind of oversimplified a few, a few compone…

AI assessment note: “I'm almost probably 80% with Jensen”

Q also picked Sachs, so I think it's undeniable that Peter Thiel is just a great picker, hands down, one of the greatest investors, whether it's in people politics, Uh, or businesses, so I give it to Peter Thiel. Uh, let's do our best new product, best new product of twenty-twenty-four. Aaron, I'm gonna start with you this time. Do you have a best new product that you launched at Box?

A Uh, we, we do, um, but I'll exclude ourselves from this, but the, um, uh, but I, I think that the wave of voice AI, um, I'm most compelled by right now as, as sort of the twenty-twenty-four kind of, you can see the, the semblance of, Actually, you know, a new paradigm for, for mobile. Um, we've kind of had the same thing on mobile for 20 years, and, um, uh, and so the ability to actually, uh, you know, in a high quality way, talk to your phone, have it do something, uh, I think is, uh, you're starting to see signs. The latest version of Gemini, um, is just incredibly, uh, powerful. Perplexity has very good, uh, work here. ChatGPT, advanced voice mode. So I think you're gonna start to see this, uh, shape kind of computing in, in the next couple years.

AI assessment note: “I'll exclude ourselves from this, but the, um, uh, but I, I think”

Q Does anything about this potential like deregulatory moment shape your view? So like, there are a lot of people who were kind of skeptics on the sideline, but who now are saying, okay, with the Trump administration and change of administration, the rules are likely to change. And obviously that's fueled a huge run up, but what, what do you make of that?

A Oh, I mean, the Trump administration is very bullish for, for anybody doing crypto. There's no question. I, I was, I was, Treating it from a very purely like, you know, sort of OCD sense of like, like, will this be a good way to build a network on the internet that is not financial? And, and so I was just laying out the case why that probably wouldn't work because of these sort of incentive dynamics that you have for what it's worth, despite I, I unfortunately have to agree with you. I'm actually fine for people to do whatever they want. If they're educated on, on, you know, the risks and the rewards and all that. And like, I, I, I laugh at meme, you know, coins all the time, like to each their own. My point was, was sort of, and again, we all kind of collectively saw web two arrive. I, I was getting a little bit, you know, anxious and nervous about this idea that web three was being described as sort of like somehow hearkening back to the origins of web two when everything was sort of mashups and interoperable and, and then looking at an architecture that I didn't, I didn't think could build You know, deliver that kind of outcome, uh, based on what I was seeing. Like, it's not, it's not an argument against just general decentralization, but, but the architectures that I was seeing get kind of created, I didn't think could lead to that for, again, non-financial use cases. Finan…

AI assessment note: “Trump administration is very bullish for, for anybody doing crypto. There's no question.”

Q Now, I want to start with one of your tweets mentioned actually you're living through the transition, you know, to cloud. And I just thought, you know, you really had such a front row seat to that. Having the experience that you have in terms of living through that transition, how do you think about what it takes to be successful with this transition in this next wave of AI?

A We are clearly in this, this window that is, um, going to be relatively temporary. Um, uh, you know, I don't know if it'll be two years. I don't know if it'll be five years. I don't know if it's already over. But basically you have these windows every, you know, more or less once a decade. There's nothing, you know, kind of particularly specific about the decade part, but we had it in the, the PC boom. So that was basically the eighties. You had it in the web boom in the nineties. You had it in the, the mobile and cloud booms in the kind of mid 2002 1010. And each one of these moments, there's an architecture shift that happens in tech that creates Really the only window of opportunity you have for new kind of platform scale, you know, large franchise kind of companies to emerge, because you need a change in the technology industry for new insurgents to be able to enter, or else basically the incumbents will, will just naturally gobble up all over the market. So we are in at one of these moments with AI, which is a, a, a period where we are going to see not only breakthrough technology, but the breakthrough application of those technologies. That is, um, as much going to be an incumbent's game as a startup's game this time around, because the incumbents have a lot of the data and a lot of the workflows, so it's even, it's even sort of more, uh, competitive, I think, than the pr…

AI assessment note: “startups will emerge that will be able to figure out a set of use cases”

Q So does this completely discard like Moore's law? Cause as you said, we've never seen that before and it's completely atypical compared to previous progressions.

A To be fair to maybe like a Moore's law, like religious, you know, you know, zealot, um, this is a sort of a different, uh, a different variable than, than what Moore's law is, uh, which is about the density of, of, of, uh, of your chip or the performance of your chip. So So this is more about model algorithms and, and how we're actually utilizing these models. There's actually a different law, which is sort of the GPU performance. Um, and I think there's a sort of a, you know, Jensen almost kind of created a law around this, but we have seen faster than Moore's law improvement on GPU performance. So, so the good news is we get a little bit of a reset on, you know, there's been a lot of talk on, hey, is Moore's law slowing down? Um, and GPUs kind of are, are giving us that That, you know, maybe next tailwind of, of compute performance improvement, um, which is this, you know, miracle that, that, uh, that we now get to, to, uh, to deal with. But, um, but I would say I, I'm seeing no signs of AI models, slow down, anything plateau in terms of the innovation curves, uh, that, uh, that we're seeing.

AI assessment note: “this is a sort of a different variable than what Moore's law is”

Q What about today? Um, customers versus prospects. How, how, what is, how much do they trick the CO into spending his time with each other? How do you balance the two?

A It's actually more that, uh, yeah, I, I, I trick myself into it. So I am, uh, I, I am willing to talk to anybody interested, remotely interested in moving their content to the cloud. So, uh, so I, I, uh, I, like, you know, 90% of the time I'll leave some Zoom call with a prospect and be like, that deal's gonna close next week. We got this. And it's like a year and a half later. Um, it's like, okay, finally we're closing it. So there's a sort of optimism that, uh, that refreshes on a daily basis, um, uh, as a, uh, as a founder, but, um, so a lot of time spent, uh, with, uh, with customers, but you know, we, we've definitely shifted. So we have a 100,000 companies on the platform. So that means, you know, almost by definition, the vast majority of our bookings and revenue are going to be from our existing install.

AI assessment note: “So a lot of time spent, uh, with, uh, with customers, but you know, we, we've definitely shifted.”

Q But then more to bigger customers, outsized growth, right? So, what's changed at Box as you go more enterprise at eight hundred million?

A Yeah, so, you know, it's interesting. Um, I'm, I've, I've decided that, like, I don't need to get any points, um, for the, the thing I'm about to say, um, but I do want to be remembered, um, As, as, as still having this as a core part of the strategy, but I, I just don't care to talk about it that much. Um, a lot of, like, like, a lot of founders will come to me and they'll be like, how did you do enterprise sales at the beginning? And I'm like, I was like, I didn't, we didn't, like, we have always been a freemium product-led growth company. We just stopped talking about it because it's just like, like, it's just not that much to talk about at some point. So, so these numbers are super important, but they don't come Just because we do these, you know, super big enterprise deals all the time. They come because we have instrumented every element of our product to be self-serve freemium and viral. And then we have an enterprise sales team that goes and works with customers to turn those deployments into much more strategic relationships. And that was the, that was the balance that, that we lucked into early that we made the bet on. And it just, that's a flywheel that if you can get humming, almost just, you know, takes care of itself. Uh, so, so our model is, most of our upsells of, of customers are, the customer has already deployed the software, they're already using it, and it'…

AI assessment note: “we have always been a freemium product-led growth company. We just stopped talking about it”

Q lucky and you work incredibly hard, right? Does box, what percent of Salesforce customers does box have, right? I mean, after all these years, it's not like 10%. Maybe it is accidentally, right? But not, not through Salesforce as a lead source, for example, right? So maybe, so I think The interesting question is, can people make millions of dollars off of Box now, uh, as a lead source, right?

A Yeah, this is a great question. So, so this, this, um, what we realized was we had to begin to dimensionalize our customer base a little bit differently if we were going to go accomplish that. So, so the, and, and I think, I mean, actually, maybe just show of hands, who is building an application that has an industry focus or industry orientation to it? Ok, so, so just, that was just, ah, and then who's building something that is more function based, job function based? Ok, interesting. Then who, who's everybody else? Just products for a hundred percent of the user base, the customer base. Ok, who's doing something that, that is universal, every employee in the whole company could use it? Okay, cool. Alright, so, um, so what we realized was, was depending on which category you're in, there are different economic, ah, values that we can- Absolutely. That we can drive, right? So if you're building a deep industry workflow, you actually could make more money from that customer than we can. Um, if you're building a job function app, then we have to find a way to, to get that job function app to the right, to the right part of our customer base. And if you build something universal, then, then we, we have to figure out how do we kind of go to market together, you know, across the entire customer base. So we built this thing called Box for Industries, um, last year, which is what we,…

AI assessment note: “depending on which category you're in, there are different economic, ah, values”

Q I'm just following that lead. Jason Lemkin, my dear friend says, Why has no public company created any good agent product? Everyone creates 60% shit agents, but he's like, the one person who's done is Palantir, and no other public company has created a sufficiently good agent product. Why is that?

A Um, you know, I don't know that I can fully endorse the point, but I'll, I'll, I'll, I can give you the, because I, I would argue our agent is sort of the best agent for working with content. You know, this is a very fast moving, uh, space, And you have to be kind of wired in at a level that, that I don't think you've ever had to be wired in in tech. Um, uh, like I am, uh, you know, and, and the information sources aren't the classic ones. It's not the, it's not the roll up review two weeks later from your traditional news publication that is going to give you any kind of alpha. It's, it's, it's the practitioner who's the, you know, literally the engineer at the, you know, agent sandbox company. And their, their long form article on how they are handling, you know, memory and the harness and, you know, like, like, like if you're not wired into that ecosystem, it's very hard to then have your team, you know, be at the kind of forefront of all of what is happening. And so it just is a, it's a different pattern than what we've ever had to do. Like, like, you know, COVID was, was pretty crazy. Like we all had to Kind of like hunker down and be paying attention to daily news cycles on, on COVIDy stuff. Um, but it wasn't like a tech problem, like it wasn't hard technologically. Um, so there's like, there's, but there's not been a moment before where the speed of change and responsive…

AI assessment note: “if you're not wired into that ecosystem, it's very hard”

Q What's the biggest thing that you've lost with scale? Some people lose speed, some people lose creativity, some people lose innovation. If you were to say, no, we probably lost that. What was something that you lost at scale that you most want to get back?

A There is a premium when you're a bigger company, which is, which is when you make a decision, it needs to be a well thought out decision that you're just going to press a button and we're going to go execute and you're going to iterate and you're going to learn lots of things. But like you, because of the, because of the work it takes to drive that alignment, but it means when you do that, like you don't want to follow up a week or two weeks later and be like, ah, just kidding. Like we got to do this thing. Um, and, and so, you know, maybe, um, this is the only, you know, in the 30 seconds I had to think about your, your question, you know, when, when you're a 20 person company, you just get in a room and you're like, okay, here's what I think we should do. It looks like this. It should be priced like this. Let's go build it. Let's test it or whatever. And then, and then like the whole company is, is sort of like fully lined up to go do that thing. You find out that it sucks and you, and you just like quickly pivot. And like everybody was on the same page that no, no, we were just, this was just It's clearly a hypothesis. We, we don't really know for a fact what's gonna happen. We can just pivot through this. In a big company, you're like, that, that team still exists, but the problem is you have everybody else watching that team saying, please tell us when, like, the thing is …

AI assessment note: “when you're a 20 person company... You find out that it sucks and you just quickly pivot”

Q Is it actually, does it feel like real autonomous driving, or were you still, is there still fear for people's life when they're in there?

A Uh, well, those could be the same thing. So, um, so it, it might be that real autonomous driving, you still fear for everybody's life, because you're just like, I do not know how this works. Like, this is kind of alchemy. This is crazy, but, uh, it was, it was definitely, you know, very crazy. It was a very, you know, kind of relatively boring suburban, um, kind of trip, but, um, uh, but it was, uh, like there was just zero need to ever, ever interject. I mean, you have to, to kind of show that you're, you're still paying attention. Um, but, uh, but I mean, it just, it shows again, we're like the past, Year and certainly for the next couple of years, you get the sense that we're going to see hundreds of these, these like, like early previews about the future, um, which is just pretty exciting. Like, uh, I, I mean, I, I've just never seen a period where, you know, in any given week you could see two to three things, which are just like, obviously that's going to be the future. Maybe it doesn't work perfectly right now, but, but it's like, there's nothing that is, is stopping it from working perfectly in a world of more compute, And, and just more breakthroughs on, on, on the, uh, on the models themselves, and that is kind of where we're at right now.

AI assessment note: “there was just zero need to ever, ever interject”

Q ignored Zerp a bit, didn't get caught up in this, but when you looked around, right, Frank Slootman said to me, probably in 20, 21, most software companies in Silicon Valley are walking dead and they don't even know it. Right. When you looked around in 20 and 21 and look around today, How do you think, um, your fellow CEOs and founders are balancing that profitability versus growth tradeoff?

A A lot to unpack here. Um, so, so first of all, I mean, empirically the data is showing that, that most public company CEOs have dealt with this relatively well. Um, they have sort of responded to the crisis. Um, and you know, Brad, especially, obviously you've put out great, great, you know, content that I think has, has catalyzed that across, um, a number of CEOs as well. And I think there, there's been a clear wake up call to, you know, let's just say, you know, My contemporary group of, of, you know, 2010 onward SaaS companies where, you know, we, we benefited from relatively cheap capital, you know, relatively high valuations. We could use that capital to, to again, grow at all costs. Uh, I would, you know, if I, if I represent, you know, probably many of the names on this group, I think that was the exactly right economic decision at the time. There was sort of a market share war. Um, you were, you were acquiring customers that maybe had a, a sort of a five or 10 year You know, kind of lifetime value curve, uh, associated with them, maybe even more. Um, and so of course you want to gobble up as much market share as humanly possible. There's a lot of stickiness to the platform. There's, there's some kind of network effects in some of these enterprise software.

AI assessment note: “empirically the data is showing that, that most public company CEOs have dealt with this relatively well”

Q lose by not increasing that is this future founder thing that you're talking about. And on one hand, it's kind of impossible to numerate, like why that could be so huge. But when you look at the legacy of immigrant founded companies in the Bay area and the headcount that's now under those companies, it's almost impossible not to believe. And, and you, why wouldn't you want that aperture bigger?

A Well, the only thing like, like there, you know, there's also, you know, the argument of, okay, well, this is just a Silicon Valley thing. And I mean, clearly it's not like, so we all know it's not, but like, even if you wanted to prove that it's not Silicon Valley, well, we're going to literally run out of real estate. Okay. So like, and room, um, we know that. So guess what, if I'm a freaking town in anywhere in the country and I could just be like, well, I can create like, 10,000 tech jobs. If I just become, if I, if I'm able to get this amazing talent and they're all going to move here, like, This is totally a countrywide opportunity for us, and we are just, we're just sitting on this and not doing anything about it, and I think it's insane. So, yeah.

AI assessment note: “This is totally a countrywide opportunity for us, and we are just sitting on this”

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 company.”

Q vision, it, it's, it's still evolving now for this platform, right? Are there one or two things, and we'll, we'll actually look at the platform on the next slide, and maybe I'll flip to it, except I can't go back, so I'm, I'm cautious, but are there one or two things you wish you'd done earlier on your platform, looking back, that you would have pulled, pulled them down earlier?

A Yeah, I think there was, um, I, I think, uh, yeah, I mean, Every, I, I just say as a general statement, every feature that today is, or, or product that today is performing well, I wish I had done earlier. So, so I, there's like unlimited given, right? Yeah. So like, like I wish I could do a lot of that faster. Um, you know, sometimes you have to find your way of which products are, are working and, you know, I'd say every maybe year we have two or three bets going on in the business of, of new areas of innovation and some years, All of them work. Some years you look back and you say, okay, only one of those worked, or, or maybe we even skipped a year of, of, of actually kind of that, that type of value that we want to drive. But in general, you know, you're always sort of planting a few seeds, um, and then, and then while you're working and incubating the, the, the ones that you planted the prior year. And so today, you know, data security is a big area. Workflow automation is a big area. Uh, we're now, um, uh, thanks to your inventions, uh, we're now doing a lot more in e-signature. Um, so we appreciate, uh, all, all the, uh, the, the wars that you had to fight before us on, on that front, but, um, so we're gonna have multiple pillars of, of, of, you know, new capabilities, all on one platform, and then integrated together, and then offered as APIs to, to anybody else that wa…

AI assessment note: “every feature that today is, or, or product that today is performing well, I wish”

Q Is that late? I mean, obviously Box is doing great, but thinking about it and learnings is.

A It's hard because you're always, you're, you're, you're, I mean, this is like the age old sales, like, Segmentation challenge. Do you do territories? Do you do size of company? Do you do verticals? And it's just, you're always kind of the matrix of, of complexity. So, so you have to be able to get enough value from your customers to be able to, to in, in any given territory to be able to start to even specialize on verticals within those territories. Um, so, so we actually were, were, I don't think we were late or early. We were sort of appropriately timed relative to the impact it would have on our business. So, so, and, and the, the, the key distinction is so, Um, in crossing the chasm.

AI assessment note: “I don't think we were late or early. We were sort of appropriately timed”

Q Do you really think so? With the greatest of respect, we are seeing the eradication of kind of lower ranking legal positions.

A And that, that is a different issue, which is how do you do the next generation of mentorship and apprenticeship when AI does automate the maybe, ah, traditional tasks that those workers are doing? Big question. A big question facing every bank in the world, every law firm in the world, anybody who had a sort of an apprenticeship model, I don't doubt that that's a real issue. But that's different from the constraints that, that all of this work ends up resulting in that you still have not been able to automate. We had a customer conversation two weeks ago, and, and, and this is just going to sit with me forever. I mean, I always have this example. They've automated or they're working on automating patient referrals when, you know, when you want to go and see the radiologist or the, the high end doctor for whatever issue you have, they're automating that, which is awesome. So now you don't have to be on the phone for, you know, a week or whatever. Well, guess what? You can automate anything. But if it still is 18 months out before an appointment is available, what, what your ultimate constraint is still the healthcare institution and the amount of doctors we have, and actually the amount of, of, of real labor we have across those organizations. So yes, maybe, maybe you, you don't want to, you know, stake your career on being a frontline, you know, customer service service rep in…

AI assessment note: “I don't doubt that that's a real issue. But that's different from the constraints”

Q Aaron, we were talking about the Meter paper, and it was, the paper suggested that their developers were actually less productive with AI, but that doesn't square with your experience talking to a lot of different startups, seeing a lot of different startups, and how they're so much more productive. So, why don't you talk about where, where you're seeing startups say they're more productive, and why is it happening?

A Yeah. So I'll, I'll first just represent our own case study and then, and then there's the really extreme version. So, uh, our own case study is we've adopted a few different kind of, um, AI coding tools. Um, uh, you know, cursor being a, a super, super popular one internally. And I, you know, as I talk to people, let's say in the hallway who have, you know, yeah, maybe they're trying to get me excited by AI, but like, I think they know I'm, I'm bought in. So, so the, the kind of Qualitative answers I get from, from people, and then I'll give you our, our internal metric. You know, some, some people say I'm getting, you know, a 20, 30% productivity gain. Other people will say 75%. Um, interestingly, I have not been able to pinpoint the demographic difference, uh, on the answers.

AI assessment note: “some people say I'm getting, you know, a 20, 30% productivity gain.”

Q I had cuts Clothing on This Week in Startups last week, and he said there's gonna be, like, if this doesn't get revolve resolved in, like, let's say two to four weeks in his group chats, people are gonna start layoffs, and they, they can't physically restart the supply chain in Vietnam or wherever to make t-shirts. So, Aaron, what's your thought on this as well? Just bringing you in.

A Sure. Well, first of all, I mean, Ryan has supplied me with a high degree of doom scrolling. And, uh, I, it's just like a horror show reading his tweets. First of all, I, like, I would feel better if the messages out of the administration were either more kind of consistent or that there was a logical connection between, do we either want to raise the kind of, you know, tariff revenue stream, or do we want free trade? Like, like those things are, are working against each other because Like depending on who you talk to, they say this is a mechanism to bring down income tax, which obviously then by definition means that they expect the tariffs to sort of persist, um, which is totally different from let's go negotiate deals that just allow for the, you know, free trade to actually increase. Uh, and so are we worried about the reciprocity or are we worried about kind of revenue stream? So that's a whole, whole issue. You also have this issue, which is the messaging from the government. And this is the meta point I'll make in a second is about is about how we could have actually accelerated into the transformation of the economy. But, you know, you have folks like Lutnik, et cetera, you know, going on on TV talking about the end state of our economy, which are actually probably, you know, fine messages, but, but we haven't seen what that vision looks like. You know, so everybody is …

AI assessment note: “I would feel better if the messages out of the administration were either more”

Q You know, when you look at their releases last week, you're looking at language learning cheaters and going, fuck, did you a lingo have a business anymore? And does language learning actually have an independent category of open AI is able to provide such quality.

A Open AI is kind of telling us what they are going to become, which is. ChatGPT is going to be this universal sort of assistant interaction, you know, interface, and all the, you know, subsequent tools to, to manage that and interact with, with different AIs that kind of come together there. And then they're going to have an API business that, that will be, you know, you can almost just, you know, very quickly, easily understand. It's going to be audio, video, text, like it'll, like, it's going to do all the formats of, of information with, you know, kind of complete intelligence on them. So then you're sitting around, you're like, well, what startup should I go build? You probably don't want to do things that, that instantly could be subsumed by a horizontal chat interface. And you probably don't want to do things in the model area that you might, might just be one training run away on their end of being subsumed by a, just a more superior model. So that means, I mean, I mean, this is sort of like, to me, it's the most exciting part of software to 80% of people. It sounds like the most boring part of software, but it's like, you have to do like the, the workflows That, that eventually a human who wants to go and run a full business process has to implement that doesn't want to just do back and forth chatting with a thing. So like to even to your tutor point, um, uh, or, or the,…

AI assessment note: “I don't think ChatGPT itself is going to become a language tutor.”