20VC: Box's Aaron Levie on Predictions for the Next Wave of AI: Will Foundation Models Be Commoditised | How the Business Model of SaaS Changes Forever | Startups vs Incumbents: Who Wins | App vs Infrastructure Layer: Where is the Value?

Aaron Levie is one of the OG founders of the last two decades as the Co-Founder and CEO of Box. Today, Box does over $1BN in revenue with a market cap of $3.85BN, and has raised over $560 million from the likes of DFJ, Andreesen Horowitz, and Coatue. In Today’s Episode with Aaron Levie We Discuss: What You Need to Know Entering This AI Wave: Why does Aaron think we are currently in a transformative window in AI? What does Aaron think it takes to be successful in this next wave? Which areas does Aaron think founders should be focusing on today? Where should they not? AI Adoption: Business Model, Implementation, Regulation. How does Aaron think AI will change how we work & run a business? What does Aaron think is the single biggest obstacle to AI adoption in large organizations? Does Aaron agree with Sarah Tavel @ Benchmark AI companies will be selling work not tools? How does Aaron think AI will change the SaaS business model? Why is Aaron not as worried about AI regulation? What are his biggest concerns today? The Next AI Breakthrough: AI Agents Why does Aaron believe the next big breakthrough in AI will be agents? How does Aaron think AI agents will change org structures? How does Aaron think agents will differ from RPA? How will RPA companies benefit from AI? What does Aaron think AI agents will look like in five years? Startups vs Incumbents: Who Wins? What is Aaron’s advice to startups today building against OpenAI? Does Aaron think startups have more advantage in foundational models or the application layer? What advantages do incumbents have? What are their biggest weaknesses? Who does Aaron think are the biggest winners in AI today? Who is underperforming? Why does Aaron think Apple isn’t losing the AI race?

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

• 0:00Speaker 00

  OpenAI is kind of telling us what they are going to become. ChatGPT is going to be this universal assistant interaction interface. You probably don't want to do things that instantly could be subsumed by a horizontal chat interface. You have to do the workflows that eventually a human who wants to go and run a full business process has to implement. We are in at 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 going to be working nonstop if you're in one of these companies. Like, there is no chance that you should be focused on sort of anything other than just pure survival and execution.

• 0:40Harry Stebbings?

  This is 20VC with me, Harry Stebbings, and this show today is a special one. It all started on Twitter on the weekend with the one and only Aaron Levie sharing some wisdom on the AI landscape today. And I said, hey, let's make a show happen. And just three days later, here we are, recorded, released. For those that do not know, Aaron is one of the OG founders of the last two decades as the co-founder and CEO of Box. Today, Box does over $1 billion in annual recurring revenue with a market cap of $3.85 billion. Yes, that 3.8X is something we discuss in the show today. And Aaron has become somewhat of a luminary on Twitter on the evolution of the AI ecosystem. If you don't follow him there, it really is a must, @levy.

• 1:24Harry Stebbings?

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• 2:07Harry Stebbings?

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• 2:51Harry Stebbings?

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• 3:32Harry Stebbings?

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• 3:43Speaker 02

  You have now arrived at your destination.

• 3:45Harry Stebbings?

  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, and I like read your tweets from the day on AI and I'm like, oh, this is, this is a good one. So thank you for putting me.

• 4:02Speaker 00

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

• 4:05Harry Stebbings?

  Now, I want to start with one of your tweets mentioned, actually, you're living through the transition to cloud. And I just thought 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?

• 4:23Speaker 00

  We are clearly in this, this window that is going to be relatively temporary. 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 we, if it's already over. But basically you have these windows, more or less once a decade. We had it in the, the PC boom, basically the eighties. You had it in the web boom in the 90s. You had it in the mobile and cloud booms in the kind of mid 2000s and 2010s. 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 just naturally gobble up all over the market.

• 5:08Speaker 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 incumbents game as a startups game this time around because the incumbents have a lot of the data and a lot of the workflow. So it's even more competitive, I think, than the prior periods of these windows. But you will have this moment of opportunity where startups will emerge that will be able to figure out a set of use cases or a way that they should deliver functionality on AI that an incumbent will not be paying attention to, will not maybe go after 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

• 5:50Speaker 00

  you really have that level of clear opportunity in front of you. And so now I was most of this is a call to, you're going to be working nonstop if you're in one of these companies. Like there is no chance that you should be on sort of anything other than just pure survival and execution as an organization.

• 6:07Harry Stebbings?

  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?

• 6:18Speaker 00

  I would say that there will be some foundation model companies, but not nearly the magnitude of the application layer companies. And much of that is due to the trends we've already seen, which is, you know, the moment you have people like Zuckerberg that are literally willing to spend billions and billions of dollars commoditizing the model layer, it becomes very hard to sort of figure out, well, how do you differentiate in that space enough where you won't, you know, kind of be taken out by one large training run from an OpenAI or a Google or a Zuck. There will be like niche or industry specific. You know, sort of approaches you could take or some very, you know, kind of specific domains you could go after. Like, I think there could be categories where, you know, maybe the big incumbents

• 7:03Speaker 00

  are more nervous about going after audio 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 L L Ms, I think those are largely be subsumed by the the the big players with maybe room for one, two, three independent companies at scale that that are not in the in the hyperscalers, but there will not be room for 50 companies. That that's just not going to be possible.

• 7:27Harry Stebbings?

  When you think about, say, like a box today, how do you think about leveraging L L Ms? 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?

• 7:43Speaker 00

  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. I don't think you're going to have complete commoditization of sort of the personality of the models for the the sort of style and the response to the point where then, you know, if you're a user, any given response could come from Gemini versus G P T four versus, you know, Claude. I think that's probably less practical. You're going to be more wired into a particular model for some some use case as a user of software. What what we did basically is, as as soon as sort of this wave started 18 months ago, we basically started working on an A I platform layer that that connects the data inbox securely with any A I model, starting with with Open A I's models.

• 8:26Speaker 00

  And then over time, we will be opening that up to other A I models as well. So if you're a customer and you say, OK, I really, you know, find G P T four is very good at legal, you know, answers, but Gemini is very good at pulling up metadata from documents. Those would be two different use cases you would have with A I within box. And we would give you the ability to kind of interact with multiple A I models to go do that on your on your content.

• 8:45Harry Stebbings?

  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. They don't want to put it in the cloud. It's like we're seeing this reversion back to on-prem in a fear of security issues. How do we solve for that?

• 9:05Speaker 00

  You know, interestingly, I'm not necessarily seeing that. 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 saying that that previous to AI, they they said, I'm fine with this data being on-prem. I feel like it's safer inside of an on-prem environment. AI is kind of the final death knell to to that particular approach. If your data is not in the cloud or in a cloud-ready form, I think it's going to be extremely hard for you to get the full value of AI on your information.

• 9:31Harry Stebbings?

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

• 9:42Speaker 00

  We have our own internal benchmarking that we do, so we compare models using a set of business documents. But the rate of improvement has been truly incredible just in the past eighteen months. What one critical metric for us is basically token window size. 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? And when we started this whole exercise with just GPT, you know, three point five eighteen months ago, so so the thing that kind of started the chat GPT wave. The token context window was more or less, I think, four thousand tokens. So you kind of give it like a blog post to analyze in the past, you know, week. At Google I/O, Sundar announced a two million token window model or a version of Gemini.

• 10:26Speaker 00

  So think about that. That's about a five hundred X improvement in eighteen months of how much data you can give the model or get back from the model. And there's just nothing in technology history that grows at five hundred X every eighteen months. It's just never been happened, you know, it's never been been seen before. And that is the kind of pace of innovation that we're able to see in AI right now.

• 10:44Harry Stebbings?

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

• 10:52Speaker 00

  To be fair to maybe like a Moore's Law, like religious zealot, this is a sort of a different, a different variable than what Moore's Law is, which is about the density of your chip or the performance of your chip. So, so this is more about model algorithms and how we're actually utilizing these models. There's actually a different law, which is sort of the GPU performance. 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 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? And GPUs kind of are giving us that, you know, maybe next tailwind of compute performance improvement, which is this, you know, miracle that, that, that we now get to deal with.

• 11:34Speaker 00

  But I would say I'm seeing no signs of AI models slow down, anything plateau in terms of the innovation curves that we're seeing.

• 11:41Harry Stebbings?

  Going through your tweets, there was another cool kind of chapter slash segment I really wanted to dig in on, which is AI agents.

• 11:48Speaker 00

  Yes.

• 11:48Harry Stebbings?

  Why do you believe the next big breakthrough in the world of AI is AI agents?

• 11:53Speaker 00

  You know, what was interesting is last year, when six months or so after the emergence of ChatGPT, there was this mad rush for basically everybody sort of believing that the paradigm of software was you would just kind of chat with all of your applications. And so everybody launched these, these chat interfaces for, for software. And that was, that was good because you sort of had to have, you know, some way to get started in this movement and to see what the use cases were. If we're really honest about, about sort of the chat, you know, use case, chat is more of like a UX paradigm shift. It takes, you know, what used to be a graphic, you know, graphic user interface and turns it more into a, a command line. I'm going to talk to it.

• 12:34Speaker 00

  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. The user interface to a chat interface, that's sort of not taking advantage of it, obviously, the full potential of AI. So I think last year, we sort of saw the chat interface wave where that was the initial kind of instinct of of software providers. And then somewhere around, you know, middle of last year, tail end of last year, this idea, or at least more established idea of AI agents, you know, has begun to emerge, which is instead of of sort of talking to AI to get information back, 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 actually trying to accomplish as opposed to just get information to do the task?

• 13:19Harry Stebbings?

  Can I ask a stupid question? Is that not what RPA is? We have large RPA providers. I always thought that was what RPA was.

• 13:27Speaker 00

  Everything I just said is exactly how you would have pitched RPA for the past decade. 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 often sort of just like looking at your computer screen and, you know, performing some kind of rote, you know, routine actions, doesn't handle variability very well, doesn't have the the level of intelligence that you now have in AI models. So I think RPA actually gives you a little bit of a of an 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

• 14:09Speaker 00

  that you or I use to get our job jobs done faster 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. It's a it's a sort of real shift of how we think about software and and the role of information and intelligence in our organization. So the best, you know, examples 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.

• 14:53Speaker 00

  They're literally autopilots that are are going out and doing work for you. That's a pretty significant revolution in not only the software space, but literally how you'll run a business in the future.

• 15:02Harry Stebbings?

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

• 15:11Speaker 00

  I think org structures somehow seem to stand the test of time on all forms of disruption. So there's some good books and like, go back, I don't know, 80 years at this point, 70 years at this point, that basically like codified today's org structure, you know, kind of format. And it has survived the test of the internet of remote work. So, so I think org structure stays the same. 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 in fact, in many cases augment whatever you would normally have had people go do. Now you have AI go and swap in for people where you need more support.

• 15:47Harry Stebbings?

  But I heard you on, you know, the Bill Gurley show, you know, you kind of spoke about kind of doing the work and not selling the tool. Kind of similar to Sarah Tavel, who's kind of said exactly that, you sell the work and the tool. And I thought, well, you wouldn't have outbound teams if you had an AI tool that was very efficient. And so your org structure would change immensely.

• 16:05Speaker 00

  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. But, you know, the classic example would be, let's say, customer support. My general view is that you'd have a layer of AI labor that handles the first, first line of defense on your inbound customer support. That will still eventually escalate 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 have signs of issues. 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, they will generate leads for then the inbound sales rep that has to go and basically pursue these.

• 16:49Speaker 00

  So, so what we've done is really kind of just shift the type of work that that team was probably doing previously in most cases.

• 16:56Harry Stebbings?

  But we can have two customer support reps, not 10, 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. So we've gone from like 20 to two.

• 17:11Speaker 00

  Yeah, so if this is a question on then total number of people in the organization, I think you have a couple of interesting questions. So if you take a mature company, let's just say, let's say Box, basically anywhere within Box, if we can make that particular function more productive. So if I can take a sales rep and have them sell 20% more, or if I could take a customer support rep and have them handle five times more tickets 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 there's simply just more work to be done than we've ever had people to be able to go and do. If I can ensure that an engineer at Box could develop 30 or 50% more code,

• 17:52Speaker 00

  we would actually reinvest that productivity gain back into engineering to build even more software. 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, 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 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 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 would actually argue that they will actually, if AI is sort of doing what it's supposed to do,

• 18:37Speaker 00

  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 they will literally be scaling more effectively and probably faster as an organization. So there's a lot of belief that like, 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 a bunch of AI. I think that will be done 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. I think most companies would take the AI efficiency gains

• 19:22Speaker 00

  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.

• 19:28Harry Stebbings?

  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 all the best and the worst enterprises engage and adopt with AI?

• 19:44Speaker 00

  I think there's two types of spend happening. There's probably the bulk of the dollars that you see in the headlines, I would argue, are likely experiments where you'll have some kind of hit rate, success rate that happens. And then those experiments graduate into production spend. We just don't have an accurate pie graph yet of what's in the production category versus what's in the experiment category. It would be probably too generic to say it's all experimental, and it's certainly not accurate that it's all production. The exact split of those two things is hard to diagnose at this point. I've just been on the road. We've done maybe about a dozen or so AI events throughout the US in the past quarter. The vast majority of companies have a meaningful number of

• 20:27Speaker 00

  AI experiments happening with lots of different areas of their business, lots of different applications. But the vast majority also have areas that are in production already. So unfortunately, it all would get lumped into the same category of AI spend by the time the CFO gets the AI bill. But we are seeing real production and lots of experimentation.

• 20:46Harry Stebbings?

  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?

• 20:56Speaker 00

  We're literally seeing both, just simply because of the way that these products get priced are so varied. Sometimes it's included in your SaaS spend, and sometimes it's like, no, here's your consumption of your AI usage.

• 21:06Harry Stebbings?

  We mentioned there about 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? Because we're so predicated on seats. I'm a SaaS investor. What happens now, Aaron?

• 21:20Speaker 00

  The good news is that everybody's experimenting with every version right now. So we will eventually see where it lands in six or 12 months. I've certainly had conversations both with customers and then startups also selling to customers on every variety. So... Do you price to what value are you delivering? How much would that workflow have cost you prior to AI? Oh, it's $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 kind of throw away the value, the kind of bespoke value oriented approach. Except for maybe like a Palantir or something, it's very, very hard to kind of make that model work. So eventually you're going to have some unit that we all agree with that you can go off of. So is it sort of a consumption, you know, model of what is your unit of volume? Is it customer support tickets?

• 22:05Speaker 00

  Is it leads that I generate? Is it emails that I write? You know, we'll have to figure that out.

• 22:09Harry Stebbings?

  On the AI agent space, when we look forward, what do you think it looks like in five years' time?

• 22:14Speaker 00

  I would imagine I can sort of sufficiently say, hey, 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, you'll have kind of category, you know, winners in a large portion of sort of job functions that today exist. And there'll be AI versions of those functions. This is again, one of these windows where 10, 20, 30, 50 companies will get started that were like the window 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 customer support agent, the AI marketer.

• 22:59Speaker 00

  You know, lots of companies won't work just for the kind of typical reasons, but we will have a landscape of basically labor that you can get from AI. Then there'll be like really interesting kind of second derivative effects, which is, okay, you know, how do you manage AI labor? Like right now, you know, when you want to manage lots of software, you know, you implement Okta or you implement a security tool. Well, it's kind of a crazy world where all of a sudden I have digital labor, 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. You can almost imagine like a workday for AI. Like, how do I actually organize 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 incredibly interesting kind of downstream questions.

• 23:43Speaker 00

  In this world that we're only scratching the surface of.

• 23:46Harry Stebbings?

  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, Sales Loft, Outreach, add AI and have it as another product which is integrated into existing workflows and is an extension?

• 24:04Speaker 00

  The cool thing is this, this will be an epic battle of existing incumbents with existing data workflow and customers that will add AI into their platform to deliver a set of services. That will work some percentage of the time and it's almost like hard to know in advance which categories that works better or worse in. By default, that will work a meaningful portion of time. Like when Facebook needed to get into mobile, other than Instagram, they basically could get into every mobile category that they needed to when they chose to do that. 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'll be some categories where incumbents have the natural advantage,

• 24:46Speaker 00

  but then there will be either blind spots that those incumbents don't kind of go after, or there will be things so different from their existing business model in kind of classic innovator's dilemma fashion that they just don't understand that they have to go after that that particular problem. It looks like it's not like 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. You know, if you're a customer support company, you might sort of think like, okay, my classic customer buys, you know, seats for every every customer's, you know, rep that's in the business and that's the business model they have. This AI agent thing looks too different from that business model all of a sudden. And then even what you build to manage the AI agents to do customer support will be different

• 25:31Speaker 00

  from what the the kind of, you know, typical customer support software company would be building, that all of a sudden you get disrupted three years later and nobody needs customer support software. That that is sort of not going to happen exactly like that, but that would be the one disruptive angle that we could see with some of these incumbent categories.

• 25:45Harry Stebbings?

  It's funny when you said about the incumbent categories adding on those features and kind of having it as an extension with the distribution benefits that they have already. The one that everyone's shitting themselves about in startup world is well, OpenAI will just do it. And yeah, fair enough. Like, it's a warranted worry. And just how do you think about, you know, Sam said on the show, we will steamroll you.

• 26:07Speaker 00

  So there were some great memes from that interview. Well, everybody should thank Sam for the clarity and transparency of their of their model. It's actually very good when when basically, you know, the lead platform player tells you the types of things they're going to go after versus the ecosystem. People should be paying close attention to that and, you know, really understanding what that advice means.

• 26:28Harry Stebbings?

  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?

• 26:41Speaker 00

  I think there's a heuristic here that that probably works, which is no matter what, I think we agree that OpenAI is kind of telling us what they are going to become, which is ChatGPT is going to be this universal assistant interaction interface. All the, you know, subsequent tools 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 will be, you know, you can almost just very quickly, easily understand. It's going to be audio, video, text, like it's going to do all the formats of information with, you know, kind of complete intelligence on them. So then you're sitting around, you're like, what startup should I go build? You probably don't want to do things that instantly could be subsumed by a horizontal chat interface.

• 27:23Speaker 00

  And you probably don't want to do things in the model area that might just be one training run away on their end of being subsumed by a more superior model. 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 the workflows 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. To even to your tutor point. 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 plausible, but but like hard to imagine it follows

• 28:06Speaker 00

  a multi-year journey with you, you know, exactly in the way 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 I do tend to see happen way too often is that incumbents will hold on to their own technology way longer than they should, because there's some perceived, I have to own something. That in practice, the moment that that whatever you thought you had to own 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.

• 28:46Harry Stebbings?

  Would you think the street's response to that would be if some of the largest public companies today dropped the inferiority problem and said, ah, fuck it, we're going to adopt OpenAI instead because their models are better?

• 28:57Speaker 00

  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 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 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 have no idea. I mean, this is like, it's impossible to give Duolingo advice on this, on this podcast. But 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 want to give OpenAI, you know, this particular data, or we're going to compete over time with them.

• 29:38Speaker 00

  It's like, 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. That's I think what a lot of incumbents tend to run into, which is the classic innovator's dilemma challenge that you see.

• 29:52Harry Stebbings?

  You've spoken before about the need for just unwavering commitment and speed and working harder than ever because 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 the proverbial garage. It's quite hard when you're a large company like Box and it's like, oh, no, no, no. Hundreds of people, thousands of people, this is the time again, like back to work, like proper, proper work, not nine to five. It's how do you galvanize a team to know this is a sprint, go?

• 30:23Speaker 00

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

• 30:57Harry Stebbings?

  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?

• 31:10Speaker 00

  There is a premium when you're a bigger company, 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 because of the work it takes to drive that alignment. But it means when you do that, you don't want to follow up a week or two weeks later being like, ah, just kidding, like we got to do this thing. 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 like the whole company is sort of like fully lined up to go do that thing. You find out that it sucks. 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 have, we don't really know for a fact what's gonna happen. We can just pivot through this.

• 31:51Speaker 00

  In a big company, 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 we're gonna go off and, and, and kind of race. 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's gonna be like, well, bozos, what were you doing? And if it's too early, 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. Finding that balance is kind of an interesting thing for anybody on the more product development, you know, sort of side of, of these kind of companies. You know, I think of Gemini actually as the first round of Gemini, all the, all the kind of massive mistakes that it made.

• 32:32Speaker 00

  It's probably some version of this manifestation, which is like, if it was a 20 person startup, they would have put it out there. Everybody would have known, okay, this didn't, this kind of sucks at these things. Let's go and prove it. But at a company 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? It's just because you had a separation of the people working on the whole thing from then the ultimate people that needed to like, you know, flag the alarm. And by then it was too late and, and just chaos.

• 32:58Harry Stebbings?

  Do you think Google smashed it last week?

• 33:00Speaker 00

  I do. I think last week, to me, the, the thing that I think it underscores, that I think honestly, 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 be in workspace. And I think that message, it was very important. It is now very clearly, the evidence of it working is now showing up. And I think Google I O is merely the, another moment of it manifesting that that, that company has religion now on AI.

• 33:36Harry Stebbings?

  Would you be a buyer or a seller of Google?

• 33:38Speaker 00

  I don't buy or sell anything, so I'm generally long Google in an AI era.

• 33:42Harry Stebbings?

  Are you worried about AI regulation? I sit in Europe. 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.

• 33:57Speaker 00

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

• 34:00Harry Stebbings?

  I mean, also just for, you know, it's, uh, 10:30 here and I'm working. So I mean, it's like, I literally had a reference call before this and they were like, dude, are you, are you European? I'm like, yeah, I'm like, I know. Are you nervous about regulation preventing progression in AI?

• 34:15Speaker 00

  I'm increasingly less nervous only because of what we've actually seen these bills sort of come up with. They don't, they don't seem to sort of progress halting as maybe what would have been rumored about a year ago. The, the scariest moment to me was the pause AI kind of moment, which was, okay, we need to, we need to stop the development of advanced AI for six months until we kind of, you know, figure something out. It was like, guys, like, it's been, let's say, a decade of, of us all as a community talking about AI. If you think that in an extra six months is all it takes for us to have some kind of alignment on what is the doomsday AI, AI going to look like? What is, what is sort of dangerous AI? What is less dangerous AI? Six months is not going to solve this.

• 34:55Speaker 00

  There are very fundamentally different philosophies in the land of AI that are irreconcilable. They will never fit together. It's just, it's okay. 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 gum up the advancements. If, you know, governments started looking at pause AI and they're like, oh, even the tech community wants us to, to stop this thing. And that, that was what I was kind of most nervous about in that period. Since then, if I look at what, what has legs, what, where progress has been made, it's often more surgical AI regs. So, okay, we have to deal with, with copyrights and, and data training. We have to deal with IP protection. I think those are important conversations, actually. I think that, that our IP law did not anticipate a world of AI in the way that we have today.

• 35:40Speaker 00

  And I think it's, I think it's a good conversation that, that is, is important to solve. There's another conversation of what is the national security issues with super intelligent AI at some, at some point in the future? How do we want to make sure to protect against that and regulate that? And I sort of like that this is an open conversation that we should be advancing.

• 35:58Harry Stebbings?

  I, you know, the show's been successful because 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 kind of rote learning? But what happens?

• 36:14Speaker 00

  Yeah, I mean, actually, I think, I think being an incumbent RPA vendor is, is actually a great spot. 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. And there's nothing in conflict with their business model. In fact, if anything, actually, they probably were the first to have more of a consumption oriented model for automation. So I think I think you could be very bullish on RPA vendors right now. I do think it means that more players kind of get in and around the space. The thing that will 100% guaranteed happen, like in five years from now, this will be the most obvious thing of all time. But when you look at like RPA, you had to be, you know, a relatively deep expert in in RPA.

• 36:54Speaker 00

  You had to be like a midsize or large enterprise or kind of developer oriented, you know, kind of individual. The total size of the market was basically arbitrarily or artificially held back by just the complexity of the legacy approach. So if AI makes it 10 times cheaper, faster and easier to automate workflows, then it stands to reason that the market will be substantially larger. Could be 100 times larger at the end of this whole journey. So what will happen is the market will get much larger. Traditional RPA vendors, if they execute, should take a good portion of that market. And there's going to be a new set of entrants that will bring automation and intelligence to their platforms that take out parts of the new market that emerges.

• 37:35Speaker 00

  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 going to be like, okay, it's in all these folders, you know, inside of my hard drive. And well, what if you could just like go in 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. 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 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.

• 38:16Harry Stebbings?

  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?

• 38:23Speaker 00

  I mean, probably the long pole of all of AI right now is not going to be the technical breakthroughs. It's going to be the implementation and change management on the human side.

• 38:31Harry Stebbings?

  So I actually tweeted that AI services companies are going to make more revenue than any foundation model providers. And then Accenture posted 2.4 billion in revenue and OpenAI posted 2 billion in revenue. So how do you think about that? Do you agree with me?

• 38:47Speaker 00

  Do you literally mean the Accenture-type services?

• 38:50Harry Stebbings?

  I do, actually. I mean, implementation and education.

• 38:53Speaker 00

  Services are almost the leading indicator to compute because you need services to implement the thing that then eventually is sort of on autopilot. So I think I would take the bet on AI services for the next five years unquestionably. The amount of dollars that will go into the change management of systems, the implementation of the technology is going to continue to be massive. On the other hand, the other thing that goes along with that, though, is a bunch of the AI stack. So the actual GPUs, the data center build-out, that as well. At some point, though, the curve, if AI is as meaningful as I believe it is, and I think so much of tech believes it is, at some point, the actual AI, the software services of AI, the infrastructure services of AI, will eventually exceed the

• 39:37Speaker 00

  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, five years ago, when we were first moving more into the cloud, our services were higher than our infrastructure spend.

• 39:58Harry Stebbings?

  Is that anything that you think we don't spend enough time talking about, or there's not enough light shone on in the AI discussion and that we haven't discussed today?

• 40:07Speaker 00

  To me, there's just interesting downstream kind of consequences if everything plays out as it should on paper. So I'm fascinated by the idea of, you know, what SAS did was it made it so, I have a friend who has, he sells balloons online. It's actually like not a bad business. It's like, it makes real money. And he sells balloons online, and I don't think he would have started the business if Shopify didn't exist. The existence of Shopify made it so he could be like, oh, well, I have this random idea, let's just see if it works. It lowered the barrier to then going out and basically starting a business. And I know that Toby has thousands or tens of thousands of these types of stories. So if Shopify caused businesses to get started, Because it lowered the barrier to being able to sell online.

• 40:52Speaker 00

  If AWS caused applications to get started, because I was like, oh, I could just build an app and run it in the cloud. I don't have to think about servers anymore. If Stripe caused businesses to get started, so I don't think about payments anymore. Then 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 startup idea or whatever. And I think there's an interesting 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 a business being started.

• 41:34Speaker 00

  I'm, I don't know which country I should pick on it as a made up, you know, kind of country as this problem. But like, if you're two or three people in, in name your random country, does that country have like the SDR sort of infrastructure that, that got built out in parts of Europe or, or, or the US 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 going to mean in terms of where companies get created? How much you can scale up? I think we'll just see a boom in all new ideas begin to emerge.

• 42:06Harry Stebbings?

  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 a podcast logo cover art or podcasts themselves. Fuck, people don't know this, but for our intros, it's not my voice, Aaron, because we have thousands and thousands of hours of my And so my point being though, is that value appreciation going to go to zero? When suddenly you get a thousand emails a day from outbound sales reps that are all AI.

• 42:37Speaker 00

  Yeah, I think you will always see this, a standard power log dynamic. I think if we were having this conversation, imagine having this conversation 20 years ago exactly and being like, wait a second. If the iPhone lets you have any software and Amazon lets you build any software, aren't we just going to see like tens of millions of apps? How will anybody even, you know, know what to find or discover? And I don't know, the world. The world magically just kind of figures out this stuff like the things that don't work die off, people don't pay for the outbound emails anymore, the things that do work take off. Creative destruction is is an incredible thing that's alive well in the world.

• 43:14Harry Stebbings?

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

• 43:23Speaker 00

  I I think we have ways of defending against this, but like you can, it doesn't take like that much imagination to be like, ah, you know, one of those like robot dogs with like a gun and a multimodal AI like, wow, wouldn't want that thing running around. So so I I think there are real reasons we should sort of pay attention to some some of the more dangerous use cases of AI. I just think we have in many cases sufficient legal frameworks for addressing those things. And then for any net new one that we come up with, let's actually 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, jumps over outside the data center to another data center and then

• 44:05Speaker 00

  self propagates. And I'm less nervous that that is is sort of on the on the docket of events.

• 44:10Harry Stebbings?

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

• 44:17Speaker 00

  We'll see.

• 44:17Harry Stebbings?

  Which stage of the business did you suck in as a leader most? And what did you learn?

• 44:23Speaker 00

  Definitely delegation. I like to get my hands dirty with all aspects of the business. And so it was it was very hard to kind of let go of parts of it to to other leaders.

• 44:33Harry Stebbings?

  Can you not micromanage at scale? Jensen Huang has told us with 60 direct reports.

• 44:38Speaker 00

  I 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. I'm in a brief period where I have to delegate to keep people happy. But eventually we will we'll be back to that land. I think the the real lesson is now is you choose the areas that you you need to exert that level of involvement. So in places like, let's say, critical areas like AI or end user experience and some product, you know, strategy, 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, or just the fact that like, you want to be able to bring on great people that that are motivated to go execute, delegation is actually extremely important.

• 45:18Harry Stebbings?

  Why do you think Zuck's crushed it so much?

• 45:21Speaker 00

  In life or in AI?

• 45:24Harry Stebbings?

  I mean, in AI specifically.

• 45:27Speaker 00

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

• 46:12Speaker 00

  be that kind of counterbalance in this space right now. So I just think it's like all of the stars aligning for his particular both philosophy and resources.

• 46:23Harry Stebbings?

  You can add anyone to your board, but obviously you don't have them already. Who would you add and why them?

• 46:28Speaker 00

  We had Jensen speak at Box six years ago, and Gen AI was not a thing, but AI was a thing. So I'd say Jensen, having access to, you know, basically the start of the supply chain of AI is such an important perspective on where things are going. I mean, if you could just look at his invoices to and from TSMC, if we could just see that data, you would kind of know what to go build next. His window into, you know, five or 10 years out in tech is unparalleled right now.

• 46:56Harry Stebbings?

  What did you not do with Box that you wish you'd done? 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?

• 47:08Speaker 00

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

• 47:39Harry Stebbings?

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

• 47:49Speaker 00

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

• 48:06Harry Stebbings?

  Why are you bullish on Apple?

• 48:08Speaker 00

  I'm bullish on Apple for a variety of reasons, you know, institutionally, how how the the company operates. But there's some meme probably of like, why is Apple not fully in AI yet? First of all, if you look at the most immediate threat that AI poses for for companies, I don't think Apple is is immediately threatened threatened by AI. Most of my AI usage is on an Apple product that I have often paid money to Apple to be able to use. So like if I so like, just like on the most immediate basis, all of my usage of AI is not threatening to anything that Apple does and is purely contributing even more to 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 assess, you know, does this new technology hurt a business that I'm in?

• 48:52Speaker 00

  And I think the answer is largely no for Apple. 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, I just say something to AI and it does a thing in the world, gets me an answer to a search query. You know, hey, you know, what what's a good, you know, way to make dinner tonight, whatever, whenever 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,

• 49:35Speaker 00

  that they are not currently monetizing 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 task, you know, automation engine, this intelligent, you know, sort of device. And so 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, it's all through your interfaces, your APIs or your software. I think that puts them in a very powerful position. So then the only question is like, oh, well, so why is it taking kind of 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. 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

• 50:18Speaker 00

  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.

• 50:32Harry Stebbings?

  Or they just partner with OpenAI as they're supposed to be doing.

• 50:35Speaker 00

  But that's that's my thing. It's like, that's not even an or. Why is that an or? Like, what does it matter to you? What is the underlying engine in Siri? I don't care. I want to 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 because it's all rumors. I don't see that as as any weakness on Apple's front. I see that as a consumer. I just want the best AI to be on my device.

• 51:03Harry Stebbings?

  Final one. If I said to you, it's 20, what is it, 2029? Where would you be thrilled for Box to be then?

• 51:10Speaker 00

  There's there's really metrics like, you know, we just passed a billion in revenue. We'd like to get to 2 billion as quickly as possible. That's an important milestone for us at.

• 51:19Harry Stebbings?

  Can I be blunt? I'm so sorry for being so rude. You parked a billion in revenue. Your market cap is 3.89. I'm I'm like, I'm depressed.

• 51:31Speaker 00

  Don't be too depressed.

• 51:32Harry Stebbings?

  No, but like, I was taught like at least like 8x.

• 51:35Speaker 00

  Yeah. This is sort of why I am the the lesson for everybody's future is eventually at some future point, you will be measured on on a set of metrics that are much more boring than ARR multiples, and they will be free cash flow multiples or whatnot. So. You know, we are, we are at the later stage of that journey now. Forex is clearly way, way too undervalued. You should be in the kind of, you know, six or eight X range. We had a period, probably the last couple of years where the kind of core business slowed down. And we've been launching a, you know, sort of second act, as it were, or third act within, you know, both AI workflow automation, more business process. That takes time to get to scale before obviously the, the top line growth, you know, can slow down.

• 52:20Speaker 00

  So, so we're kind of in the midst of that transition right now, but these are the things you deal with as a, as a public company.

• 52:26Harry Stebbings?

  So where would you be five years then? Sorry, I interrupted you with.

• 52:29Speaker 00

  No, no, it's fine. So our next set of goals, get to 2 billion as quickly as possible. Market cap, kind of, you know, whatever is associated with that. You know, I don't have a specific, one specific thing as much as, kind of back to what we were talking about earlier on AI. You know, if you think about the information that goes into, into your content, your contracts, your marketing assets, your, your financial records, your invoices, this is basically, you know, the closest thing that a company has to its digital memory. Let's just say, and AI now has the ability to actually tap into your digital memory as a company. The thing that, that over the next couple of years, and so let's say five as an arbitrary point, is really enabling just the world to reimagine what they can do with their data.

• 53:10Speaker 00

  And what if every company had infinite digital memory to make better decisions, to automate more processes? You know, think about the new employee that has to be on boarded, that doesn't know anything about what the hell, you know, the organization's doing, instantly that's now what they can tap into. So, so we think it's just a profound moment for, for how you work with your information in the cloud.

• 53:28Harry Stebbings?

  Listen, Aaron, thank you so much for putting up with me pressing in many, many different areas, which was also like, there was no schedule sent ahead of time. It's like arranged on Twitter without the usual process.

• 53:40Speaker 00

  No, that's great. Who wants process?

• 53:42Harry Stebbings?

  Exactly. But thank you so much.

• 53:44Speaker 00

  Thank you.

• 53:46Harry Stebbings?

  I mean, what can I say? I absolutely love doing that show. If you want to watch the full episode, you can watch it on YouTube by searching for 20VC. That's 20VC on YouTube. But before we leave you today, I want to talk about Cooley, the global law firm built around startups and venture capital. Since forming the first venture fund in Silicon Valley, Cooley has formed more venture capital funds than any other law firm in the world, with 60-plus years working with VCs. They help VCs form and manage funds, make investments, and handle the myriad issues that arise through a fund's lifetime. We use them at 20VC and have loved working with their teams in the US, London, and Asia over the last few years. So to learn more about the number-one most-active law firm representing VC-backed companies going public,

• 54:30Harry Stebbings?

  head over to Cooley.com and also CooleyGo.com, Cooley's award-winning free legal resource for entrepreneurs. And speaking of providing incredible value to your customers, travel and expense are never associated with cost savings, but now you can reduce costs up to 30% and actually reward your employees. How? Well, Navan rewards your employees with personal travel credit every time they save their company money when booking business travel under company policy. Does that sound too good to be true? Well, Navan is so confident you'll move to their game-changing All-in-One Travel Corporate Card and Expense Super App that they'll give you $250 in personal travel credit just for taking a quick demo.

• 55:12Harry Stebbings?

  Check them out now at Navan.com/20VC. And finally, let's talk about Squarespace. Squarespace is the all-in-one website platform for entrepreneurs to stand out and succeed online. Whether you're just starting out or managing a growing brand, Squarespace makes it easy to create a beautiful website, engage with your audience, and sell anything from products to content all in one place, all on your terms. What's blown me away is the Squarespace Blueprint AI and SEO tools. It's like crafting your site with a guided system, ensuring it not only reflects your unique style, but also ranks well on search engines. Plus, their flexible payment options cater to every customer's needs, making transactions smooth and hassle-free. And the Squarespace AI?

• 55:55Harry Stebbings?

  Content wizard, helping you whip up text that truly resonates with your brand voice. So if you're ready to get started, head to Squarespace.com for a free trial. And when you're ready to launch, go to Squarespace.com/20vc and use the code 20vc to save 10% off your first purchase of a website or domain. As always, I so appreciate all your support and stay tuned for an incredible episode this coming Friday. A compilation where we bring together the best minds in AI to understand where they think true value lies, whether it's in the infrastructure layer with foundation models or in the application layer with startups.