Aaron Levie: How the Business Model of SaaS Changes Forever & Startups vs Incumbents:Who Wins?|E1155

1. 0:00 – 0:57

   Intro

   1. ALAaron Levie0:00

      So we are in now one of these moments with AI, which is a period where we are going to see not only breakthrough technology, but the breakthrough application of those technologies. That is as much going to be an incumbent's game as a startup's game this time around. You're gonna be working nonstop if you're in one of these companies. Like, there is no chance that you should be focused on, on sort of anything other than just pure survival and execution.

   2. HSHarry Stebbings0:21

      Ready to go? Aaron, I am so excited for this. I'm like a big fanboy of your tweets. I go downstairs... People don't know this, it makes me sound really sad. I go downstairs for, like, my evening espresso, which is weird in its own self-

   3. ALAaron Levie0:46

      (laughs)

   4. HSHarry Stebbings0:46

      ... and I, like, read your tweets from the day on AI and I'm like, "Oh, this is, this is a good one." (laughs) So thank you-

   5. ALAaron Levie0:51

      I-

   6. HSHarry Stebbings0:51

      ... for tweeting me.

   7. ALAaron Levie0:52

      I, uh, happy to provide your evening, uh, entertainment, so...

   8. HSHarry Stebbings0:56

      (laughs)

2. 0:57 – 9:41

   The Transition to Cloud & The Next Wave of AI

   1. HSHarry Stebbings0:57

      Now I want to start with, one of your tweets mentioned actually you're living through the transition, you know, uh, 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?

   2. ALAaron Levie1:16

      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'll be, 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 '80s. You had it in the web boom in the '90s. You had it in the, the mobile and cloud booms in the kind of mid-2000s and 2010s. And in 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 of the market. So we are in now 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 pri- prior periods of, uh, of these windows. But you will have this moment of, of opportunity where startups will emerge that will be able to figure out a set of use cases or a way that, that they, they should deliver functionality on AI that an incumbent will not be paying attention to, will not may- maybe, maybe go after, and it's the, in these windows where you can build now very large companies. And so we're in one of these windows, and it's sort of, these are the only times when, when you really have that level of, of clear opportunity in front of you. And so now I, I... It was mostly just a call to, you're gonna be working nonstop if you're in one of these companies. Like, there is no chance that, that you should be, you know, focused on, on sort of anything other than just pure survi- survival and execution, uh, as a, uh, as an organization.

   3. HSHarry Stebbings3:18

      Do you think new juggernaut companies will be created both in the foundation model layer and in the application layer, or just in the application layer with incumbents gobbling up the foundation model layer?

   4. ALAaron Levie3:28

      I would say that, that there will be some foundation model companies, um, but not, not nearly the, uh, the magnitude of, of the application layer companies. And, um, and much of that is, is due to the trends we've already seen, which is, you know, the moment you have, you know, people like Zuckerberg that are, are literally willing to spend billions and billions of dollars commoditizing the, the, the model layer, it, it becomes very hard to sort of figure out, well, how do you, how do you differentiate in that space enough where, where you won't, you know, kind of be taken out by, by one large training run from an OpenAI or a Google or, or a Zuck? There will be, like, niche or, or maybe, you know, industry specific, you know, sort of approaches you could take or some very, you know, you know, kind of specific domains you could go after. Like, I think there could be categories where, you know, maybe the big incumbents are more nervous about going after audio, um, because, because there's obviously going to be lots of, of interesting conversations around copyright and whatnot. But I think for, like, the, the pure play horizontal LLMs, uh, we... I think tho- those will largely s- be subsumed by the, the, the big players, with maybe room for one, two, three independent companies at scale that are not in the, in the hyperscalers, but there will not be room for 50 companies. Um, that, that's just not gonna be possible.

   5. HSHarry Stebbings4:49

      When you think about, say, like, a Box today, uh, how do you think about leveraging LLMs? It is... Is it a case of actually using six at the same time and switching between them for different use cases and purposes and being able to transition seamlessly between them? How do you think about that and the choice that companies have there?

   6. ALAaron Levie5:06

      So we are building an architecture that lets our customers do what you just said, so effectively switch between models that they want to use for different purposes. Um, I think it's sort of less likely that we would be able to kind of switch on their behalf in some kind of completely abstracted way, because each model sort of, you know, is just a little bit different in, in how verbose it is, um, or how succinct it is, or what kind of style does it, does it sort of respond in. And so I don't think you're gonna have complete commoditization of sort of the personality of the models for the, the sort of style and the response, uh, to the point where then, where then, you know, if you're a user, you know, any given response could come from Gemini versus GPT-4 versus, you know, Claude. I, I think that's probably less practical. Um, you're gonna be more wired into a particular model for some, some use case as a user of software. What we did basically is as, as soon as sort of this wave started, you know, let's say 18 months ago, we basically started working on an AI platform layer that, that connects the data in Box securely with any AI model, starting with, with, uh, with OpenAI's models. Over time, we will be opening that up to other AI models as well, so if you're a customer and you say, "Okay, I really, you know, find GPT-4 is very good at legal, you know, answers, but Gemini is very good at meta, uh, at pulling up metadata from documents," um, those would be two different use cases you would have with AI within Box, and we would give you the ability to kind of interact with, uh, you know, multiple AI models to go do that on your, on your content.

   7. HSHarry Stebbings6:28

      When I speak to large enterprises, they all say the same thing. They say, "Hey, I want to get the incredible benefits from some of these providers, but fuck, it's really sensitive data. I'm not willing to..."... put that anywhere near any vulnerable openness, and they don't wanna put it in the cloud. It's like we're seeing this reversion back to on-prem in a fear of security issues.

   8. ALAaron Levie6:48

      You know, interestingly, I'm not necessarily seeing that. In fact- in fact, I'd probably say the opposite. For the first time ever, we're now talking to customers that have been cloud holdouts that are say ... that- that previous to AI, they- they said, "I- I just, you know, I'm fine with this data being on-prem. I feel like it's safer in- inside of an on-prem environment." AI is kind of the final, I would say, maybe death knell to- to that particular approach. Um, if your- if your data's not in the cloud or in a cloud-ready form, I think it's gonna be extremely hard for you to get the full value of AI on your information.

   9. HSHarry Stebbings7:17

      I had Sam on the show when he was in London, and he said that the- the biggest kind of rate-limiting factor was actually just the rate of model improvement.

   10. ALAaron Levie7:23

       Hmm.

   11. HSHarry Stebbings7:23

       When- when you look at it, how do you analyze the rate of model improvement?

   12. ALAaron Levie7:27

       We have our own internal benchmarking that we do. So we compare models, um, using a set of business documents. The rate of improvement has been, uh, truly incredible, uh, just in the past 18 months. We, you know ... One- one critical metric for us is basically, uh, token window size, um, where we- we rely heavily on how much data can you give the model and can you get back from the model in a single sort of interaction or inference? When we started this whole exercise with just GPT, you know, 3.5, 18 months ago, so- so the thing that kind of started the ChatGPT wave, the token, uh, context window was more or less, I think, 4,000, uh, tokens. So you kind of give it like a blog post to analyze. Uh, just in the past, you know, week, um, at Google I-O, uh, Sundar announced a two million token window model or version of Gemini. So think about that. That's about a 500X improvement in 18 months of how much data you can give the model or get back from the model. Um, and- and there's just nothing in technology history that- that grows at 500X every 18 months. There's just never be- been happen ... You know, it's never been- been seen before. Um, and that is the kind of pace of innovation that we're able to see in, uh, in AI right now.

   13. HSHarry Stebbings8:37

       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.

   14. ALAaron Levie8:44

       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, uh, 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- 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.

3. 9:41 – 20:16

   AI Agents

   1. ALAaron Levie9:41

   2. HSHarry Stebbings9:41

      Uh, going through your- your tweets, there was another cool kind of chapter/segment I really wanted to dig in on, which is like AI agents. Uh, why do you believe the next big breakthrough in- in the world of AI is AI agents?

   3. ALAaron Levie9:52

      You know, what's interesting is last year, when, you know- you know, let's say six months or so after the emergence of- of ChatGPT, there was this mad rush for- for basically everybody sort of, uh, believing that the paradigm of software was you would just kind of chat with all of your applications. Uh, and so everybody launched these- these chat interfaces for, um, for software. And that was- that was good because you- you sort of had to have a, you know, some way to get started, um, in- in this, uh, in this movement and to see what the use cases were. But I think if you- if you, you know ... if we're really honest about- about sort of the chat, you know, use case, chat is more of like a UX paradigm shift. So it takes, you know, what used to be a graphic u- you know, graphic user interface and turns it more into a- a command line, I'm-gonna-talk-to-it. Um, uh, but like at the end of the day, you're kind of still accomplishing the same thing with- with software in a lot of cases. You can get to information faster, but if all we've done is move, you know, the- the user interface to a chat interface, that's- that's sort of not taking advantage of obviously the full potential of AI. So I think last year, we- we sort of saw the chat interface, you know, wave, um, where, uh ... where- where that was the initial, you know, kind of instinct of- of software providers. And then somewhere around, you know, middle of last year, tail end of last year, this- this idea or at least more established idea of- of AI agents, you know, has- has begun to emerge, which is instead of- of sort of talking to AI to get information back, um, what if we could talk to AI to have it do something for us and really kind of complete the- the underlying task that- that we're- we're actually trying to accomplish as opposed to just get information to do the task?

   4. HSHarry Stebbings11:31

      Can I ask a stupid question? Is that not what RPA is? Like, you know, we- we have large RPA providers. I always thought that was what RPA was.

   5. ALAaron Levie11:39

      Everything I just said is exactly how you would have pitched RPA for the past decade. Um, and- and everything I just said doesn't sort of negate the need for- for what RPA would be in the enterprise. The challenge with RPA is, you know, RPA is relatively frail. It's- it's often sort of this like looking at your computer screen and- and- and, you know, performing some kind of rote, you know, routine actions. Doesn't handle variability very well, um, because there's- there's again ... doesn't have the- the level of intelligence that you now have in AI models. So, um ... So I think RPA actually gives you a little bit of a- of a early preview of what becomes possible when you could apply more general intelligence, maybe not- not- not sort of full AGI but like a general intelligent model, to a large number of- of business tasks. So the big breakthrough is what if we could go from a world where software is something that you or I use to get our job- jobs done, you know, faster or- or it enables us to do our jobs, to where software is something that you or I use to basically farm out work to AI to go do. And- and it's kind of a ... it's a- it's a sort of real shift of how we think about software and- and the role of- of, you know, information and intelligence in our organization. So the best, you know, examples, uh, that are emerging now are I could have an AI that is my outbound sales rep, or I could have an AI that- that basically does full testing of my- of my product as a quality assurance, you know, engineer. Or I could have an AI that responds to all my customer support tickets. So when you think about now an organization that has, you know, effectively AI agents that augment the labor or the- the people in the organization, they're not co-pilots. They're literally autopilots, um, that are- are going out and doing work for you. That's a, you know, pretty significant revolution in- in sort of just like, you know, not only in the software space but literally how you run a business in the future.

   6. HSHarry Stebbings13:25

      How do you think we'll see org structures change as a result? We- I, you know, obviously I'm a content business and it changes content immensely. Um, how do you think we'll see org structures change as a result?

   7. ALAaron Levie13:35

      I think org structures somehow seem to stand the test of time on all forms of disruption. So, um, uh, so there's actually, um, uh, there's some good books in like, um, uh, uh... you know, that go back, I don't know, 80 years at this point, 70 years at this point, that basically, you know, really like codified today's org structure, you know, kind of, uh, format. And it has survived the, the test of the internet, of remote work, of, you know, sort of, you know, large scale industrial change. So I think org structure stays the same. Um, I think what happens is, is you now have the ability to sort of drop AI labor into any part of that org chart. And, um... And in fact, in many cases augment, you know, just whatever you would normally have had people go do, now you have AI go and, and swap in for people where you need more support.

   8. HSHarry Stebbings14:24

      But I, I heard you on, you know, the, the Bill Gurley show, uh, and the Brad show. Um, and, uh, you know, you kind of spoke about kind of doing the work and not selling the tool, kind of similar to Sarah Taber, who's kind of said exactly that.

   9. ALAaron Levie14:35

      Yes.

   10. HSHarry Stebbings14:35

       You sell the work and not the tool. Uh, and I thought, well, you wouldn't have outbound teams if you had an AI tool...

   11. ALAaron Levie14:42

       Yes.

   12. HSHarry Stebbings14:42

       ... that was very efficient and so your org structure would change immensely, right?

   13. ALAaron Levie14:45

       Yeah, yeah, sorry, sorry, sorry. I mean to be very... I mean, yes, at that level of specificity, you might have certain roles that have now turned into AI roles. Like, you know, the classic example would be, let's say customer support. I, I, I, you know my, my general view is that you'd have an A- a layer of AI labor that handles the first, you know, it's like the first line of defense on your, your inbound customer support. That will still eventually escalate to, to the human side, which, okay, I've got to take on the more complicated processes. Maybe I'm doing things that are a bit more proactive with customers that have, you know, that, that have signs of issues. You know, workday might look somewhat similar. There's just now an extra layer of AI that has been added to parts of the org chart. And then similarly, you know, if I have an outbound sales rep, um, they, they will generate leads for then the inbound sales rep that, that has to go and basically pursue these. So what we've done is, is really kind of just shift the type of work that that team was probably doing previously in, in most cases.

   14. HSHarry Stebbings15:41

       But we can have two customer support reps, not ten, because we've taken away all the kind of annoying frontline stuff, the low-hanging fruit that was handled by AI. And then you've just got the complex for a fewer number, and we've lost the outbound team.

   15. ALAaron Levie15:55

       Sure.

   16. HSHarry Stebbings15:55

       So we've gone from like 20 to two.

   17. ALAaron Levie15:57

       This is a question on then, then sort of total number of people in the organization. I think you have an... a couple of interesting questions. So, so if you take a mature company, uh, let's just say, let's say Box, you know, in this case. Basically anywhere within Box, if we can make that particular function more productive... So if I can take, uh, a sales rep and have them sell 20% more, or if I could take a customer support rep and have them, you know, handle five times more tickets because, because AI is helping, at least so far empirically, every time that we've done that, we will actually reinvest in that area of the business because, because there's simply just more work to be done than we've ever had people to be able to go and do. Um, there... If I can, if I can ensure that an engineer at Box could develop 30 or 50% more code, we're, we would actually reinvest that productivity gain back into engineering to build even more software. So, so you have sort of... You know, some companies I think will choose to just reinvest those dollars and that efficiency. And even in the customer support case, if we can get rid of some percentage of those frontline customer support tickets, we're going to take that, that, that, the time of those people and have them turn into customer success where we're going to actually go and, you know, reach out to our customers more proactively when, when they have issues or when we think there's an opportunity to use the product more. So that's, that's sort of one side of the equation. Then I think you have an interesting example, which is, which is... Okay, take a company that starts from scratch. They've got one employee, it's the founder. What does that company sort of look like in the future? That actually might look like a different company. Now, I, I would actually argue that they, they will actually... if, if AI is sort of doing what it's supposed to do, I believe that company will actually hire more people over time on a like-for-like basis. Because what they would be doing is that one or two person company would hire the AI outbound sales rep, you know, software company. They'll actually get more leads faster than they would have as an alternative, you know, kind of way they would run the business. They're going to have to now hire sales reps to handle those leads and, and they will literally be scaling more effectively a- and, and probably faster as an organization. So there's a lot of belief that like, oh, well, well, you might have these solo companies that, you know, become multi-billion dollar companies with just one person or, you know, three people and, and a bunch of AI. I think that will be done, you know, uh, just by virtue of like everything happens in the world multiple times, but like I think that'll be a relatively novel way to run their company. Um, I think most companies would take the AI efficiency gains and then you'll end up hiring the functions that eventually need to be serving all the new growth that you've just developed because of AI.

   18. HSHarry Stebbings18:25

       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?

   19. ALAaron Levie18:41

       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 kinda 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.

   20. HSHarry Stebbings19:53

       That, that's really interesting. Is it an AI line item or is it actually a fintech line item, a HR line item? Is it segregated by the functional tool that it's in or in an AI tool?

   21. ALAaron Levie20:03

       I mean, we're, we're literally seeing both just simply because the, the m- the, the way that these products get priced are so, are so varied. Um, you know, ha- sometimes it's included in your SaaS spend, and sometimes it's like, "No, here's your consumption of your AI usage."

4. 20:16 – 25:36

   The Evolution of Business Models in the AI Era

   1. ALAaron Levie20:16

   2. HSHarry Stebbings20:16

      You mentioned there about kind of selling the work and not the tools, and actually how it changes in terms of providing that output. What does that do to business models? 'Cause we're so predicated on seats. I'm a SaaS investor, how, what happens now, Aaron?

   3. ALAaron Levie20:29

      Your guess is as good as mine. So, um, I think we're, we've seen ev- uh, th- the good news is that everybody's experimenting with every version right now. So we will eventually see where we, where it lands in 6 or 12 months. I've certainly had conversations both with customers and then startups also selling to customers on every variety. So, uh, do you price to what value are you delivering? You know, how much would that workflow have cost you, you know, prior to AI? "Oh, it was $100,000? Well, well, we'll charge you $50,000 for it." That one's tough to scale because everything's bespoke, so let's kinda throw away the value, the, the kind of bespoke value-oriented approach, because that, that's never, you can, y- you know, th- e- except for maybe like a Palantir or something, it's very, very hard to kinda make that model work. So, um, so eventually you're gonna have some unit that, that we all agree with, um, uh, that, that you can go off of. So is it sort of a consumption, you know, model of, of what, what is your unit of volume? Is it customer support tickets? Is it leads that I generate? Is it, um, is it, um, you know, emails that I write? You know, we'll have to figure that out.

   4. HSHarry Stebbings21:31

      On the AI agents, basically then, when we look forward, what do you think it looks like in five years time?

   5. ALAaron Levie21:36

      I can sort of sufficiently say, "Hey, you know, AI, generate leads for my business," or, "Answer my support tickets," or, "Review my contracts," or, "Process my invoices." If I can do that, then, you know, realistically you will have sort of, I think you'll have kinda category w- you know, winners in, in a large portion of sort of job functions that today exist, and there'll be AI versions of those functions, um, and, and this is a m- this is a, again, one of these windows where 10, 20, 30, 50 companies will get started that, that were like the window in two- in the mid-2000s where like all of today's SaaS companies basically emerged in like a five-year period, essentially. And we'll have that for, for basically AI jobs where you'll have the AI security engineer, the AI, you know, customer support agent, the AI, you know, m- marketer, and, um, you know, lots of companies won't work just be- for, for the, the, the, the kinda typical reasons, but we will have a landscape of, of f- basically labor that you can get from AI. Then there'll be like really interesting kinda second derivative effects which is, okay, you know, how do you manage all those different, that like, AI labor? Like right now, you know, when you wanna manage lots of software, you, you have, you know, you implement Okta or you implement a security tool. Well, this is kind of a crazy world where all of a sudden I have, I have digital labor, uh, that is, you know, from a variety of providers. Do I need some way to kind of organize them, make sure that they can interact well, have guardrails around what they can do? Uh, you know, there's, there's a, like, you can almost imagine like a workday for AI. Like, like, how do I actually organize what all this, what all this work is? How do I actually make sure that it's organized well, you know, versus the, what the humans are doing also? Lots of in- incredibly interesting kinda downstream questions in this world that, uh, that we're only, only scratching the surface of.

   6. HSHarry Stebbings23:23

      You said we'll see this whole generation of like AI versions of each function. To what extent do you think we have that with new players in each of those functions, versus Gong, Salesloft, Outreach add AI and have it as another product which is integrated into existing workflows and is an extension?

   7. ALAaron Levie23:42

      The cool thing is this. Um, this will be an epic battle of existing incumbents with, with existing data workflow and, and customers that will add AI into their platform to deliver a set of services. That will work some percentage of the time, uh, and it's almost like hard to know in advance which categories that works better or worse in. But, but just by vir- by, by default, that will work a meaningful portion of time. Like when Facebook needed to get into mobile, other than Instagram, they basically could g- could get into every mobile category that they needed to, um, when they chose to do that. Um, uh, and so only the categories that they didn't pay attention to did you sort of see these emerging, you know, new players in the, in the mobile space. Similarly in AI, I think, I think there will be some categories where incumbents have the natural advantage, but then there will be either blind spots that those incumbents don't kinda go after, or there will be things so different from their existing business model, in kind of classic innovator's dilemma fashion, that they, that they just don't understand that they have to go after that, that particular problem and it looks like it's not like a- an actual threat, or it doesn't seem to be solving the same problem, and then all of a sudden overnight, you're like, "Oh, the business is now over because we were disrupted by the AI version of what we do." And, you know, if you're a customer support company, you, you might sort of think like, "Okay, my, my, my classic customer buys, you know, seats for every, every single sale e- every customer's, you know, rep that, that's in the business," and that's the business model they have. This AI agent thing looks too different from that business model, and all of a sudden... And then even what you build to manage the AI agents to do customer support will be different from, from what the, the kind of, you know, typical customer support software company will be building, that all of a sudden you get disrupted three years later and nobody needs customer support software. You know, that, that's, uh, that, that is sort of not gonna happen exactly like that, but that would be the one disruptive angle that we could see with some of these, uh, incumbent categories.

5. 25:36 – 28:59

   The Current State of Enterprise Adoption of AI

   1. ALAaron Levie25:36

   2. HSHarry Stebbings25:36

      It's funny when you said about the incumbent categories adding on those features and kind of having it n- as an extension with the distribution benefits that they have already. Uh, the, the one that everyone's shitting themselves about in startup world is, "Well, OpenAI'll just do it."

   3. ALAaron Levie25:48

      Hopefully. (laughs)

   4. HSHarry Stebbings25:48

      And, you know, (laughs) yeah, fair enough, like it's, it's a warranted worry.

   5. ALAaron Levie25:53

      Well-

   6. HSHarry Stebbings25:53

      How do you-

   7. ALAaron Levie25:54

      Yeah, sorry.

   8. HSHarry Stebbings25:55

      Well, and just how do you think about what, you know, Sam said on, (laughs) on this show?

   9. ALAaron Levie26:00

      Yeah, yeah. Yeah.

   10. HSHarry Stebbings26:00

       We will steamroll you.

   11. ALAaron Levie26:02

       So there were some great memes from, from that interview. I mean, honestly, uh, everybody should thank, thank Sam for the clarity and transparency of their, of their model. Um, uh, and, um, and I think it's actually, it's actually very good when, when in- when basically, you know, the lead platform player tells you the types of things they're gonna go after versus the ecosystem. Like, people should be paying close attention to that, um, and, and, and, you know, really understanding what that advice means.

   12. HSHarry Stebbings26:28

       You know, when you look at their releases last week, you're looking at language learning tutors and going, "Fuck, did Duolingo have a business anymore? And does language learning actually have an independent category if OpenAI is able to provide such quality?"

   13. ALAaron Levie26:42

       OpenAI is kinda telling us what they are going to become, which is ChatGPT is gonna be this universal sort of assistant interaction, you know, interface, and, and the, all the, you know, subsequent tools to, to manage that and interact with, with different AIs, um, that kinda come together there. And then they're gonna have an API business that, that will be... You know, you can almost just, you know, very quickly, easily understand it. It's gonna be audio, video, text. Like, it'll, like, it's gonna do all the formats of, of information with, you know, kinda complete intelligence on them. So then you're sitting around, you're like, "Well, what startup should I go build?" You probably don't wanna do things that, that instantly could be subsumed by a horizontal chat interface, and you probably don't wanna do things in the model area that you might, might just be one training run away on their end of being subsumed by, uh, just a, a more superior model. So that means, I mean, ki- 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 wanna just do back and forth chatting with a thing. So, like, to even to your tutor point, um, uh, or, or the, the, uh, you know, um, you know, language learning, I don't think ChatGPT itself is going to become a language tutor. I think it'll have the full capability to be a language tutor at the model level, and could you, like, you know, prompt it to being a language tutor seems, seems plausible, but, but, like, hard to imagine it follows a multi-year journey with you, you know, exactly in the way that, that, that Duolingo would maybe do. But what should Duolingo do is probably as quickly as possible adopt whatever OpenAI is building from a model standpoint and make sure that they are incorporating that into their product. Because what, what I, I, I, what I do tend to see happen way too often is that incumbents will hold onto their own technology way longer than they should because there's some perceived kind of, you know, "I have to own something," that in practice, the moment that, that, that whatever you thought you had to own is, is inferior to what the rest of the market has access to, you need to drop the inferior thing as quickly as possible and adopt whatever is superior, even if it means, you know, potentially supporting what, what you think, you know, emotionally is sort of your long-term competitor.

6. 28:59 – 34:03

   Embracing AI for Competition & Survival

   1. ALAaron Levie28:59

   2. HSHarry Stebbings28:59

      What do you think the street's response to that would be if some of the largest public companies today drop the inferiority problem and said, "Oh, fuck it, we're gonna adopt OpenAI's instead because their models are better"?

   3. ALAaron Levie29:10

      I mean, this is actually, th- there's, like, multiple answers embedded in this. I think some of this actually is more of just, like, the, the, the market sort of lack of understanding, if anything. What I was, what I'm about to say is probably people would like it if Duolingo announced tomorrow that GPT-4o is powering their, you know, translation engine. That would actually be a positive because, because it would just be like, "Oh, this is this very powerful AI that now your user base has access to," and we understand that, like, you're selling a different sort of flavor value proposition than what OpenAI horizontally is going to sell, so we think that could be, you know, better for your, your business. But I, I have no idea. I mean, this is, like, it's impossible to give Duolingo advice on this, uh, on this podcast.

   4. HSHarry Stebbings29:49

      (laughs)

   5. ALAaron Levie29:50

      So... (laughs)

   6. HSHarry Stebbings29:51

      Uh, the-

   7. ALAaron Levie29:51

      But, but all, all I would say is I've seen some people bury their head in the sand being like, "No, my, my custom-trained model is so good at this one thing, and we don't wanna give OpenAI, you know, this particular data, or we're gonna compete over the, over time with them." It's like, it's like, you can, you can wish all of that to be true. But if what they have is better for the product that you're trying to deliver to customers, that is the only way that you're going to survive this. So that, that's, that's I think what a lot of incumbents, you know, tend to, tend to run into, which is the classic innovator's dilemma challenge that, that you, you see.

   8. HSHarry Stebbings30:21

      You've spoken before about kind of the need for just unwavering commitment and speed and working-

   9. ALAaron Levie30:26

      Yeah.

   10. HSHarry Stebbings30:26

       ... harder than ever 'cause there's a short period of time where winners will be made. That's kind of easy if you're a startup and there's three people in, you know, the proverbial garage.

   11. ALAaron Levie30:34

       Yeah.

   12. HSHarry Stebbings30:34

       It's quite hard when you're a large company like Box, and it's like, "Oh, no, no, no, no, hundreds of people, thousands of people." Like, this is the time again, like, who, like, back, back to work, like proper-

   13. ALAaron Levie30:45

       Yeah.

   14. HSHarry Stebbings30:45

       ... proper work, not 9:00 to 5:00. Um, it's, how do you galvanize a team to know-

   15. ALAaron Levie30:51

       Yeah.

   16. HSHarry Stebbings30:51

       ... this is a sprint? Go.

   17. ALAaron Levie30:54

       The tweet I sent was not for anybody else other than Box employees. So for us, we're 2,700 or so employees. Um, we're still enough, th- though, that we can literally get on a Zoom call, and our all hands is, like, everybody in the company on one call, and then we talk through the strategy of what we have to do. I think we're in a moment where, uh, anybody reading the news in tech understands, you know, I, I, the kind of period that we're in. Um, I don't nece- necessarily know that everybody understands what's on the line about if y- if your company doesn't make it to the other end of this bridge, um, you know, before, before everything kind of breaks off, uh, then, then, you know, you're out of business, um, in, uh, in this, in this new world. So that's probably the only alarm that needs to be, you know, kinda set.

   18. HSHarry Stebbings31:36

       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?

   19. ALAaron Levie31:50

       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 gonna press a button and we're gonna go execute. And you're gonna iterate and you're gonna 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 wanna follow up a week or two weeks later and be like, "Ah, just kidding, like, we gotta do this thing." Um, and, and so, you know, maybe, um, and 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 l- 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 p- and you just, like, quickly pivot. And, like, everybody was on the same page that, "No, no, we were just, this was just 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 exactly the thing, and, and we're gonna go off and, and, and kind of race." And so you have to, you have to kind of find exactly the right moment where you're ready to now expose the working thing to everybody else. If it's too late, then everybody is gonna be like, "Well, bozos, what were you doing?" And if it's too early, then, then you're gonna have thousands of people kind of go through the, the sort of like, "Oh, that didn't work," or like, "Hey, that didn't land." And, and, and, and, and finding that balance is kind of an interesting thing for anybody on the more product development, you know, sort of side of, of, of these kind of companies. You know, I think of Gemini actually as, as, um, the first round of Gemini, all the, all the kind of, you know, you know, massive mistakes that it made is probably some version of this, um, manifestation, which is, like, if it was a, if it was a 20-person startup, they, they would've put it out there. Everybody would've known, "Okay, this didn't, this, this kind of sucks at these things. Let's go improve it." But at, at a company of the scale of Google, like, there's some team working on it. They kind of throw it over the fence, and then everybody's like, "Oh my God, what is this thing?" And, and it's just like, like, it's, it's just because you had a separation of the, the people working on the whole thing from then the ultimate people that needed to like, like, you know, flag the alarm, and by then it was too late and,

7. 34:03 – 41:13

   Democratizing Business Creation with AI

   1. ALAaron Levie34:03

      and just chaos.

   2. HSHarry Stebbings34:04

      Do you think Google smashed it last week?

   3. ALAaron Levie34:06

      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, there, 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 sent a message to the company that AI is the number one most important priority of all things. It, 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 gonna 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.

   4. HSHarry Stebbings35:11

      Would you be a buyer or a seller of Google?

   5. ALAaron Levie35:13

      I don't buy or sell anything, so, um, but, um, but it, like, I'm, I'm, I'm generally along Google, uh, in, in an AI era.

   6. HSHarry Stebbings35:21

      Okay. Are you worried about AI regulation? I sit in Europe. We, uh, we favor a very regulated environment. We've made our business, uh, kind of constraining our residents and then taxing the shit out of anyone who wants access to them, and that's been called a business model in this continent, as you know. Um-

   7. ALAaron Levie35:38

      It's cool that they haven't kicked you out for, uh, for, for your views on this.

   8. HSHarry Stebbings35:41

      I mean, also just for, you know, it's, uh, 10:30 here and I'm working, so, I mean-

   9. ALAaron Levie35:46

      (laughs)

   10. HSHarry Stebbings35:46

       ... it's like, I literally had a reference call before this and they were like, "Dude are you, are you European?" I'm like-

   11. ALAaron Levie35:51

       (laughs)

   12. HSHarry Stebbings35:51

       ... "Yeah, I know, I know."

   13. ALAaron Levie35:52

       (laughs)

   14. HSHarry Stebbings35:53

       "It's, I'm weird." Uh, but, uh, so are you nervous about regulation preventing progression in AI?

   15. ALAaron Levie36:00

       I'm increasingly less nervous only because of what we've actually seen these bills sort of, um, come up with. They don't seem as, um, they don't, they don't seem as sort of progress-halting as maybe what would have been rumored about a year ago. You know, the, the, the scariest moment to me was the Pause AI, uh, kind of moment, which was, which was, okay, we need to, we need to stop the, the development of advanced AI for six months until we kind of, you know, figure something out. And, and it was like, it's been, let's say, a decade of, of us all as a community talking about AI. If you think that an, an extra six months is all it takes for us to have some kind of alignment on, on, like, what, what is the doomsday AI, AI gonna look like, what is, what is sort of dangerous AI, what is less dangerous AI, six months is not gonna solve this. There are very fundamentally different philosophies in, in the land of AI that, that, that are irreconcilable. They will not... They will never fit together. It's just, it's okay. It, it's great to have actually a dynamic set of perspectives. They will not be able to ever be fully unified. And so I thought that that was going to really kind of, you know, gum up the, the pro- the, the, the advancements if, you know, government started looking at Pause AI and they're like, "Oh, even the tech community wants us to, to stop this thing." Um, and that, that was what I was kind of most nervous about in that period. Since then, if I look at, at what actually has kind of, you know, what, what has legs, what, where progress has been made, um, I think it's, it's, it's often more surgical, uh, AI regs. So okay, we have to deal with, with copyrights and, and data training.

   16. HSHarry Stebbings37:33

       Mm-hmm.

   17. ALAaron Levie37:33

       Um, we have to deal with IP protection. I think those are important conversations actually. I think that, that our IP law did not anticipate, you know, an, a, a world of AI, uh, in the way that we have today. And I think it's, I think it's a good conversation that, that would, you know, is, is important to solve.... um, there's another conversation of- of just like what is the national security, you know, sort of, you know, issues with- with just, you know, super intelligent AI at some dist- at some point in the future. How do we want to make sure to, uh, protect against that and- and, um, and regulate that? It's not an area that- that I'm as, um, as sort of, uh, you know, kinda focused on or- or- or, uh, or- or, you know, as believe in. But some- some people that I deeply respect fully believe in it, and, um, and I sort of, uh, like that this is an open conversation that we should be advancing.

   18. HSHarry Stebbings38:21

       I, you know, the show's been successful 'cause I specialize in dumb questions. From the way that you described agents, it was like the next generation of RPA. What happens to prior RPA providers? Does- does UiPath just adopt an agent-based model and actually move away from kinda rote learning, uh, or d- d- what happens?

   19. ALAaron Levie38:39

       Yeah, I mean, actually I think, I think being an incumbent RPA, uh, vendor is- is actually a great spot because- because if you already are talking to customers about literally automating business processes and workflows and there's just a better way to do that, um, and- and there's nothing in conflict with their business model... In fact, if anything, actually, they- they probably were the first to have more of a consumption-oriented, you know, kind of model for- for, uh, automation. Um, so I- I think, I think you could be very bullish on RPA vendors right now. Um, but I do think it means that more players kinda get in and around the space. So the- the, um, I think the- the- the thing that will, uh, 100% guaranteed happen, like- like in five years from now this'll be the most obvious thing of all time, but when you, when you look at, like, RPA, you had to be l- you know, a relatively deep expert in- in RPA. You had to be like a mid-size or large enterprise or- or kinda developer oriented, you know, kinda individual. And so the- the total, uh, size of the market was basically arbitrarily or artificially held back by- by just the- the- the complexity of the legacy approach. So if AI makes it 10 times cheaper, faster, and easier to automate workflows, then- then it stands to reason that the market will be substantially larger. It could be 100 ti- 100 times larger at- at the end of this whole journey. So- so what will happen is the market will get much larger. Traditional RPA vendors, if they execute, should- should take a good, you know, portion of that market, and then there's gonna be a new set of entrants that will bring automation and intelligence to their platforms that- that, you know, take out parts of- of the new market that emerges. That's obviously what we're focused on, which is, hey, what about all the parts of the business that you never automated before? You know, if you go to most companies and you say, "Show me where your digital assets are, all your marketing materials," they're gonna be like, "Okay, it's in all these folders, you know, inside of- of my hard drive." And, well, what if you could just, like, go in and- and ask a question of, like, "Show me all of the, you know- you know, red dresses" and it just, like, instantly came up? Well, that is what you'll now be able to do with AI. Uh, what if you go to your contract repository and instead of it being just a bunch of folders with contracts in them, you just say, "Hey, what contracts are up for renewal next month with this cl- with this, you know, particular clause in it?" And instantly you now know, you know, what areas of ... risk does your business have? So, these are things that you just could not have done before that AI now lets us do on top of all of our data.

   20. HSHarry Stebbings40:57

       Do you think there's a hard, like, enterprise consumer behavior shift that they have to go through in order to fundamentally change how they work?

   21. ALAaron Levie41:04

       Yeah, so this is the, I mean, probably the long pole of- of all of AI right now is not gonna be the technical breakthroughs. It's going to be the implementation and change management

8. 41:13 – 47:57

   The Significance of Cash Flow Management

   1. ALAaron Levie41:13

      on the human side.

   2. HSHarry Stebbings41:14

      So I actually tweeted that, uh, AI services companies are gonna make more revenue than, um, uh, any foundation model providers, and then Accenture posted 2.4 billion in revenue and OpenAI posted two billion in revenue. So, absolutely right. (laughs) Um, how do you think about that? Uh, do you agree with me?

   3. ALAaron Levie41:35

      Uh, services are almost the leading indicator to compute, um, because you need services to implement the thing that then eventually is sort of on autopilot. You know, not- not- not fully, but- but more or less. So- so I think, uh, I would take the bet on- on AI services for the next five years, n- unquestionably. Um, the amount of dollars that will go into the change management of systems, the implementa- the- the implementation of the technology is- is gonna continue to be massive. On the other hand, the other thing that goes along with that, though, is- is, you know, a bunch of the AI stack, so the actual GPUs, the- the data center build out, that as well. So I think the only, the- the- the, at some point, though, the curve, if- if AI is- is as, you know, meaningful as- as I believe it is and I think, you know, so much of- of tech believes it is, at- at some point, the- the actual AI sort of, the software services of AI, the s- the infrastructure services of AI will eventually exceed the human services on the implementation simply because now once it's in production, you don't need that same change management 10 years later. Like, it's just literally running. Like, the amount of money we spend today on our cloud infrastructure vastly exceeds the amount of money we spend maintaining our cloud infrastructure, versus, you know, five years ago when we were first moving more into the cloud, our services were higher than our infrastructure spent.

   4. HSHarry Stebbings42:51

      Mm-hmm. No, I get you totally. Is there 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?

   5. ALAaron Levie43:01

      To me, there's, uh, just interesting downstream, um, kinda consequences if everything plays out as- as it- it- it should on, like, on paper. So- so I, you know, I- I'm fascinated by, like, I'm fascinated by the idea of, you know, what SaaS did was it made it so... I have a friend who has, uh, he sells balloons online, um, and it- it's actually, like, not a bad business. It's like a, like it makes real money. Um-

   6. HSHarry Stebbings43:27

      (laughs)

   7. ALAaron Levie43:27

      ... and he sells balloons online, and, um, and I don't think he would've started the business if Shopify didn't exist. Um, li- 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, caused businesses to get started 'cause they don't have to 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 just be like, "Well, maybe I should, like, start this idea because I've lowered the barrier to, again, getting customers or supporting customers or, you know, testing the software." Like, like, "I now have AI labor that can let me now scale my, my, my startup idea," or whatever. And I think there's an interesting sort of global democratization that could happen where you could be a company based in a place that, like, did not have this type of talent for your, for a, a, a business being started. I'm, I don't know which country I should pick on a- as a made-up, you know, kinda country as this problem, but, like if you're two or three people and, and name your random country, like do, does that country have, like the SDR sort of infrastructure that, that got built out in, you know, the, you know, sort of parts of Europe or, or, or the US like, because of the SaaS boom? Probably not. But like now, I go and I can just, like literally, like hire an outbound sales rep, you know, with AI. So think about, what is that gonna mean in terms of where, where companies get created, how much you can scale up? I think we'll just see a, a boom in, um, uh, in, in all new ideas begin to emerge.

   8. HSHarry Stebbings45:22

      The one thing I really worry about, and it's slightly on a tangent, but like when you have anything kind of generative AI, essentially supply just becomes unlimited. It could be that outbound sales rep and they can send a million messages a day, or we could have, um, a podcast logo cover art or podcasts themselves. Fuck, uh, we don't, people don't know this but for our intros, it's not my voice, Aaron. Like that, not at all.

   9. ALAaron Levie45:45

      Well ... (laughs)

   10. HSHarry Stebbings45:45

       Like just, just-

   11. ALAaron Levie45:46

       (laughs)

   12. HSHarry Stebbings45:46

       ... and because we have thousands and thousands of hours of my int-

   13. ALAaron Levie45:49

       Yeah.

   14. HSHarry Stebbings45:49

       (laughs) And so my point being though, shit, is like value appreciation gonna go to zero when suddenly, fuck, you get a thousand emails a day from outbound sales reps that are all AI?

   15. ALAaron Levie46:00

       This one can't solve. Uh, the, um, I, I think the, I, I think you will always see this, a standard kind of, um, uh, power law dynamic. Uh, you know, I think, I think if we were having this conversation, imagine having this conversation 20 years ago exactly, and being like, "Wait a second. If, if the iPhone lets you, you know, have any software and Amazon lets you build any software, aren't we just gonna see like tens of millions of apps? How will anybody even, you know, know what to find or discover?" And, and it's like, it's like, I don't know, the world, the world magically just kind of figures out this stuff. Like the, the things that don't work die off, the, you know, nobody, people don't pay for the outbound emails anymore. The things that do work take off. It's, it's, uh, you know, we, we, creative destruction is, is an incredible, you know, uh, you know, thing that's alive and well in the world.

   16. HSHarry Stebbings46:48

       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?

   17. ALAaron Levie46:59

       I think we have ways of defending against this. But like, you know, you can, you can n- it doesn't take like that much imagination to be like, "Oh, 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." (laughs) 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, uh, you know, uh, dangerous use cases of AI. I just think we have, in many cases, sufficient 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

9. 47:57 – 59:46

   Quick-Fire Round

   1. ALAaron Levie47:57

      ...

   2. HSHarry Stebbings47:57

      So I wanna do a quick fire with you. I, I love this. Um, I essentially, I say a statement and you give me your immediate thoughts. Does that sound okay?

   3. ALAaron Levie48:05

      We'll see. (laughs)

   4. HSHarry Stebbings48:06

      (laughs) Which stage of the business did you suck in as a leader most and what did you learn?

   5. ALAaron Levie48:11

      Definitely delegation. I like to, um, get my hands dirty with, uh, with all aspects of the business, and so it was, it was very hard to kinda let go of, of parts of it to, uh, to other leaders.

   6. HSHarry Stebbings48:23

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

   7. ALAaron Levie48:30

      I l- I cannot wait until we're a $2 trillion 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 the, the real lesson is now, uh, is, is you choose the areas that you, you need to exert that level of involvement. So um, in, 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 a- 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 wanna be able to bring on great people that, that are motivated to go execute, uh, delegation is actually extremely important.

   8. HSHarry Stebbings49:19

      I totally agree. Why do you think Zuck's crushed it so much?

   9. ALAaron Levie49:23

      In life or in AI?

   10. HSHarry Stebbings49:25

       (laughs) I mean in, in AI specifically.

   11. ALAaron Levie49:29

       Okay. Um, I think my read on this is you have, um, you know, one of the best entrepreneurs of our time that has, uh, basically all of the right underlying resources for AI. So lots of compute, incredible engineers, you know, billions of users, i.e. lots of data. He is extremely motivated to have a platform that the internet ...... you know, builds on and participates in. Um, and, and I think AI is sort of his moment to, to really kind of reestablish the dominance, uh, that, that I think we remember Facebook having in the maybe late 2000s, which was like, we were all gonna build on the social fabric of the web. Some of that happened, some, some didn't exactly happen as planned, and I think AI is now this moment when, when actually he can provide a real alternative to more of the, you know, relatively closed approaches to AI, and, um, and he's sort of set up extremely well to, to be that kinda counterbalance, um, in this, uh, in this space right now. So, so I just think it's like all of the stars aligning for his particular both, you know, probably philosophy and, and resources.

   12. HSHarry Stebbings50:37

       You have a very strong personal brand now. I always use you as actually, like, a very powerful example of how great personal brands can be and why more founders should build them.

   13. ALAaron Levie50:47

       (laughs)

   14. HSHarry Stebbings50:47

       W- what do you think that most people don't know about you because of your personal brand that you would like them to?

   15. ALAaron Levie50:53

       (laughs) W- I'm b- I, I'm, I'm totally fine with people not knowing anything additional about me. Um ...

   16. HSHarry Stebbings50:59

       (laughs)

   17. ALAaron Levie51:00

       Uh, I, I, uh, I just really like enterprise software and that's how people should think about me.

   18. HSHarry Stebbings51:03

       (laughs) Love that. Um, you can add anyone to your board. Obviously, you don't have them already. Who would you add, and why them?

   19. ALAaron Levie51:10

       We had Jensen speak at Box, our, our kinda conference. Uh, Box Works must have been six years ago. You know, gen AI was not a thing, but, but AI was a thing, so, um, so, so we wanted to talk about kind of the future of where things were going. So, anyway, so I'd say Jensen having access to, you know, basically the start of the supply chain of AI, um, is such an important perspective on where things are going. If you could just look at his invoices, you know, uh, to, to and from TSMC, if we could just see that data, you would kinda know what to go build next. Um, it's, uh, yeah, I mean, the, his, his window into, you know, five or 10 years out in, in tech is, is unparalleled right now.

   20. HSHarry Stebbings51:49

       Why are you bullish on Apple?

   21. ALAaron Levie51:51

       I'm bullish on Apple for a variety of reasons. Uh, just that, you know, institutionally how, how the, the company operates. But, you know, I think there's, there's, uh, you know, some, some meme probably of like, "Why is Apple not fully in AI yet?" And, um, and actually, if you look at the most immediate threat that, that AI poses for, for companies, um, I don't think Apple is, um, is immediately threated- threatened by AI. Um, it literally, uh, most of my AI usage is on an Apple product that I have often paid money to Apple to be able to use. So, so like, if I, so like, just like on the most immediate basis, all of my usage of AI is, is, is not threatening to anything that Apple does and is purely contributing even more to, to their, their sort of, their platform dominance. But now let's go on the offensive side. So, that, that's sort of on the defensive side. Like, like, you have to first as- assess, you know, does this new technology hurt a busi- uh, a business that I'm in? And I, I think the answer's largely no for Apple because they're not selling something that AI is, is sort of directly threatening. Then you, you flip to the offensive side which is, does AI help the business that, that Apple is in? And I think it's unquestionable that if you could turn this thing into basically a command center for, I just, I just say something to AI and it does a thing in the world, you know, get, yeah, fine, gets me an answer to, to a search query. You know, "Hey, uh, you know, what, what's a, a good, you know, way to m- make dinner tonight?" Whatever, whatever, you know, you, you, you do as a, on personal side, you know, instantly they'll just do that. And then if it really turns into a thing of like, "Hey, book me this flight or call this Uber for me," or whatever, that's just an infinite amount of, of new types of transactions that they can facilitate that they are not currently monetizing in, in any kind of meaningful way. Now, who knows how they actually monetize those things? But I think it turns your phone basically into, into your, your, your task, you know, automation engine, um, uh, and, and this intelligent, you know, sort of device. And so, so if, if you have a billion plus people that are using this device for now a new set of things, that they never used it before, and it's, it's all through your interfaces, your APIs or your software, uh, I think that puts them in a very powerful position. So, then the only question is like, "Oh, well, so why is it taking kinda quote unquote so long?" I would actually argue that any of the, any of the kind of quote unquote either delays or slowdown doesn't amount to anything. Like, like, we, we, we, we, like, like, you know, the AI that I was using a year ago is totally different than the AI I'm using today. This, this space is changing so rapidly, that it is way better for Apple to enter the moment when they, you know, believe that they've built the right user experience, when the technology is sort of stable, and when it's high enough quality, we will all use with the thing that they launch whenever that point is.

   22. HSHarry Stebbings54:39

       Or they just partner with OpenAI, as they're supposedly supposed to be doing in the next

   23. ALAaron Levie54:42

       But that, that's my thing is like, there's not- that's not even an or. Why, why is that an or? Like, what does it matter to you what is the underlying engine in Siri? Like, I do- I don't care. I, I just wanna, I wanna be able to click my phone, ask a question, get something done. So, so I don't even see that as an or, I see that as just a, a natural sort of technology partner supply chain thing. And who even knows what they're even doing 'cause it's all rumors. But like, but like, I don't, I don't see that as, as any weakness on Apple's front. I see that as a, as a consumer, I just want the best AI to be on my device.

   24. HSHarry Stebbings55:12

       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 focus here. What decision did you decide not to do that you wish you had done?

   25. ALAaron Levie55:25

       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 ev- 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, w-... 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, uh, uh, apply constraints that force better decisions, better strategy, better execution. Um, so I would have done that ear- you know, years earlier than, uh, when we ultimately, uh, focused on cash flow.

   26. HSHarry Stebbings56:06

       You've been married now for a few years. What, what is the secret to success as like a fucking on it public market CEO and a happy marriage? Pretty tough to do.

   27. ALAaron Levie56:17

       It helps that my wife is equally busy. So, um, so I, I don't get yelled at as much, uh, as probably as possible for, uh, for, for my own, uh, busyness. But, um, uh, I mean, you, you just, uh, uh, probably all the standard things. You, you just, you carve out the date nights, uh, you, uh, you, you have weekends for family time, and then you just ask for forgiveness a lot, so...

   28. HSHarry Stebbings56:40

       (laughs) I love that. Uh, final one. If I said to you, it's 20... God, what is it? 2029? Shit. Where would you be thrilled for Box to be then?

   29. ALAaron Levie56:51

       There's, there's certainly metrics like, you know, could be... you know, we, we just passed a billion in revenue. Um, we'd like to get to two billion as quickly as possible. Um, uh, so, so, so that, that's an important milestone, uh, for, for us at, at Box.

   30. HSHarry Stebbings57:03

       Can I, can I be blunt? W- I'm so sorry for being so rude.

Episode duration: 59:47