In short
Notes on "Aaron Levie: The Restless Founder Plotting the Future of Cloud Storage and AI" - Pattern Breakers Podcast
Podcast Overview
- Host: Mike Maples Jr. (Floodgate)
- Guest: Aaron Levie, Co-founder & CEO of Box
- Focus: The early challenges of building Box, lessons learned in entrepreneurship, and the future of cloud storage and AI.
Key Themes and Insights
Founding Story of Box
- Initial Inspiration:
- Levie recognized the inefficiencies in data storage during his college internship.
- Noted that existing solutions were outdated and lacked innovation.
- Development Process:
- Launched Box in 2005 while still a student.
- Collaborated with co-founders and used early feedback from users to iterate on the product.
- Initially launched as a paid service, despite the trend toward freemium models.
Early Struggles and Growth
- Funding Journey:
- Faced numerous rejections from prominent investors (e.g., Bill Gates, Paul Allen).
- Eventually secured angel investment from Mark Cuban, which validated their business idea.
- Decision to Drop Out:
- Levie and his co-founder chose to prioritize Box over college, motivated by early traction and potential.
Business Model Evolution
- Transition to Enterprise:
- Initial focus on consumer products; pivoted to B2B as competition from larger tech companies increased.
- Recognized the need for a more robust enterprise offering, especially during the economic downturn.
- Freemium Model Success:
- Transitioned to a freemium model, resulting in an explosion of user signups and a clearer path to monetization.
Challenges and Near-Death Experiences
- Business Model Transition:
- Faced financial challenges during the pivot to enterprise, especially in a recession.
- Highlighted the importance of maintaining a sustainable cash flow and being judicious with burn rates.
Lessons on Sales and Product-Market Fit
- Sales Learning Curve:
- Emphasized the need for aggressive hiring of sales reps to gauge market interest and product fit.
- Established that the ability for new sales hires to cover their costs was a strong indicator of product-market fit.
Current Focus on AI
- AI Reinvention:
- Levie is leading Box’s reinvention to integrate AI capabilities, viewing it as a major opportunity rather than a threat.
- AI can unlock new potentials for managing and utilizing unstructured data, automating workflows that were previously labor-intensive.
Future Considerations for Startups
- Navigating AI and Incumbents:
- Acknowledges that while incumbents are adapting, there remains significant opportunity for startups, especially in areas with no established software solutions.
- Emerging Business Models:
- Encourages startups to explore new business models that leverage AI capabilities and fill gaps in existing markets.
Philosophical Takeaways
- Enduring Curiosity: Levie's continuous willingness to adapt and innovate keeps Box relevant.
- Embrace Change: Founders should be willing to pivot and embrace emerging technologies to remain competitive.
Conclusion
- Aaron Levie's journey with Box exemplifies the importance of resilience, adaptability, and a forward-thinking mindset in entrepreneurship. His insights on the interplay between product development, market dynamics, and emerging technologies such as AI provide valuable lessons for current and aspiring founders.
Additional Information
- Follow Mike Maples Jr.: [Twitter](https://x.com/M2JR)
- Pattern Breakers Blog: [patternbreakers.substack.com](https://patternbreakers.substack.com)
- Mike's Book: Available wherever books are sold.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00I would probably start with the premise that most incumbents are awake, they're alive, they're not going to miss some kind of window that's happening right now. Even though I said that incumbents are kind of awake, alive and going to move quickly, 30 % of the companies will not fully capture the potential opportunity. Startups will find a clever wedge. And then, boom, you have the new startup emerge that can kind of move fast enough that it hits escape velocity. That's the voice of Aaron Levy, co-founder and CEO of Box. What started in a college dorm room became a cornerstone of the cloud era, and Levy helped shape it.
0:37Nearly 20 years in, with Box crossing a billion in revenue, he's not coasting. He's charging forward, reinventing the company around AI, rethinking everything. While others might defend the past, Aaron stays in the future, curious, restless, and moving fast, so the rest of us can too with him. This is Mike Maples Jr. of Floodgate, and it's go time with Aaron Levy. This is Mike Maples Jr. and welcome to the Pattern Breakers podcast, where we explore why some founders radically change the future and how they stand apart. Together, we'll learn about the counterintuitive mindsets and actions behind their remarkable success.
1:18Brace yourself for a world where chaos is welcome, naysayers are often a positive signal, and movements galvanize misfits who transform the impossible to the inevitable.
1:40In 2005, inside a college dorm room, Aaron Levy co-founded Box with a hunch that the way businesses stored and collaborated around information was about to change. At the time, cloud storage wasn't a given. It was a point of view about the future that few had yet embraced. Levy didn't just build for where the world was. He built for where it was going, and Box won big. But here's the twist. Founders often fall into patterns after they succeed. The urgency fades. But not with Levy. Now facing the AI frontier, he's not delegating Box's reinvention. He's leading it, personally, deep in the product details, like it's day one.
2:21What makes Aaron Levy fascinating isn't just what he saw back then. It's that he's still looking forward, still experimenting, still starting over, not because he needs to, but because that's how he's wired. It's not just ambition. It's a kind of enduring curiosity, a trait that has kept him in box forever young. Let's talk to him.
2:47Aaron, welcome to the podcast. Hey, Mike. Thanks for having me, man. You bet. I've been looking forward to this. Why don't we start from even before the beginning? I think it was 2005 when you started Box at USC. What was going on then and what got you to thinking you wanted to start this company? So before the beginning, so in 2004, I was a sophomore in college at USC and in high school had done a bunch of web internet startups, tried a bunch of different ideas. None really took off. Obviously, you're just kind of high school or building websites. And then in college, they kind of got a little bit more serious, a little bit more professional, but still nothing really worked.
3:30And I was doing an undergraduate business course where one of the projects was to essentially identify a market and do a SWOT analysis on some of the players in the market. And then simultaneously, I had an internship at Paramount Pictures, where my main job was basically like faxing documents and like, you know, scanning documents and just moving around data, you know. And so for some reason, you know, it's always hard to know, like, what was the very first spark that kind of comes together in one of these things. But for some reason, I kind of just latched on to this idea of internet storage would just make life a lot more efficient.
4:05And then in this class, I got to study the existing market of internet storage, which kind of was born out of the 90s. And most of the companies that had launched these online data storage products, they just stopped innovating also. And so kind of over a few weeks, maybe a month or two, you kind of build this sort of deep conviction and epiphany, which is, wait a second, like storage is getting cheaper. The Internet's getting faster and more people are going to be online. And yet everywhere I look, nobody has actually created a modern solution to this problem. Wait a second, like this could actually be a pretty cool startup opportunity.
4:37And so that was kind of the early ingredients that led to coming up with Box. Okay, but how did you act on that? Did you start writing the code yourself? Did you find co-conspirators pretty early? What was your minimum viable product to kind of test the idea? Yeah, so another kind of confluence of things, my background was in sort of front-end design. I was one of these script kiddies in high school. So you put together Perl scripts and you're automating things, but nothing that nothing that would have really been able to scale out as a file system that we were trying to build. So so I had a couple of friends, ultimately the co-founders, but they joined more officially about a year later that were helping on some of the technology and the ideation on the technology side.
5:24And then we ended up having some contract engineers go and build the first version of the product. I did all the kind of front end design and experience. And then we got that built out. We launched that as an initial, you know, now I would look at it like a prototype. It was fully functioning. It worked, you know, it wasn't like leaking your data. And we launched that. And we launched that in maybe January, February of 05. And basically, you know, relative to other startup ideas that I'd had, this is the first one where just like regular people on the internet were like happily using the product.
5:59and giving us feedback. And I was like, oh, wow, this is actually what people talk about when they talk about like doing a startup. Like all the other ones have been a website, like the traffic kind of comes and then they leave and no one ever sticks around to do anything on your product. It kind of sucks. But this was the first one where like somebody signed up, they like uploaded their files, their shared files. They would email us saying, hey, I wish you had this feature. We had some early success with some of like the very primitive bloggers you had like Engadget and Gizmodo. And, you know, these were like kind of the first internet blogs, they'd review technology.
6:32So we had we had some reviews on those sites, we did some giveaway promotions, we had, you know, different kind of referral things. And, you know, each day, you know, maybe it started with with three signups, and then five signups and 10 signups. But each day, it was kind of growing, nothing that felt like an overnight success. And there's an important asterisk, we launched as a paid only service, mostly because we just didn't, you know, think there was another way you did software, like, okay, you have a software application, you're going to charge for it. And basically, you know, just to just to show the kind of, you know, complexity or tension here, I had applied for a couple internships that spring for the summer and I got rejected from the internships.
7:09If I had gotten them, we could have been on a very different timeline because what happened was by getting rejected, you know, it meant that my co-founder and I, we could spend the entire summer working on the on Box the entire summer. So we built basically Box out of first our kind of dorm college, you know, apartments, and then out of my co-founder's house in Seattle, you know, 15 hours a day, you know, growth hacking, building more features, launching new things. That's when it really started to feel like a startup. And then ultimately, you know, actually like going out and pitching investors that kind of made it even more real.
7:44When did you decide to drop out of USC and pursue it full time? Like, when did you decide, yeah, this is a thing for sure. So in the summer, we pitched every VC we could find in Seattle. I found Bill Gates's fax number. We faxed him a prospectus. I think we got the equivalent of a 404 from a fax machine. So that was automatically rejected. We dropped off a printed prospectus at Paul Allen's house, mostly rejected by everybody except for a couple. We found this group of angel investors in Seattle that were willing to take a shot on us. So we raised about$80 ,000 and we sold a quarter of the company for$80 ,000 that summer.
8:25And then later in the summer, because I guess we were just like drunk on needing dilution, we also pitched Mark Cuban and he then decided to invest in us later that fall. So then we took on a few hundred thousand dollars, which again was another kind of 20, 25 % of dilution. That gave us increased conviction that, wow, like if Mark Cuban is saying this is a real business. That's pretty serious. We should take that more seriously. And then what was happening is throughout the fall, it was very distinctly obvious that it was almost impossible to keep doing classwork and run the business. I'd be in the middle of classes that I just knew I was going to fail out of and just answering customer support email inquiries on a BlackBerry.
9:08So that kind of ramped up through the fall and that made us realize that we had to make a decision at some point. And how did you get Mark Cuban's attention? Mark's incredible because to this day, he's just like the most online person probably on the planet. If you found Mark Cuban's email address in 2005 and you emailed him, I actually think there's like a high degree of likelihood that he would have responded. I am utterly amazed at his email responsiveness. Especially because I think now it's like a known thing that he does it. And you'd think that at some point, if everybody knew that you were so good at email, you would have to be so inundated by email 20 years into that.
9:46And yet to this day, he's just still incredible at triaging it all. So we sent him an email and we were just like, hi, we're two kids that are building this online storage product. Any interest in blogging about it or partnering with us on anything you're doing? And then that kind of snowballed into an investment case on his end. But all of that kind of reached this crescendo in, I believe it was Thanksgiving break of 05, my co-founder and I, we were just like, you know, I think this is reaching a point where we have to kind of, we have maybe a once in a lifetime opportunity to jump on this. And we got lucky because the zeitgeist was starting to emerge.
10:24Zuck and team had dropped out, moved to Palo Alto. YouTube was these ex-PayPal younger people building this thing. You know, this is probably our shot. Like We have a website. It's working. It's scaling. So we dropped out that winter break and moved to the Bay Area. In the early innings, did you ever have any near-death experiences where it just wasn't going your way at all? Or was it sort of gradual up into the right for the most part? I think everything was gradual up into the right so far in the story. The near-death starts to happen over the next couple of years where we had kind of more multiple near-death experiences.
11:04So maybe just to accelerate, you know, we drop out. We had two other friends, the ones I mentioned earlier, also drop out a few months later. And this freemium thing is this, you know, real opportunity, which is if we had a free version of the product, more people would sign up. We could then upsell a percentage of them. So we launched, you know, Box as a freemium product. And that starts to take off where now we're seeing like thousands of signups a day. We raised a Series A. We'd probably be raising like$300 million if it was back then. And our Series A was 5 million posts. So I'm very jealous of all founders right now.
11:36So we raised this$5 million post from DFJ, Josh Stein, and Emily Milton. And we kind of, at this point, were a little bit in wandering mode because what was happening was we were kind of a consumer slash prosumer product. So we saw the writing on the wall that Google had to enter the game, Apple had to enter the game, Microsoft, Yahoo, Apple, I mean, sorry, Facebook, et cetera. So that kind of scared the living shit out of us because we were like, okay, you've got these massive incumbents. All are going to pick up on this idea that you could store files in the cloud and make them available for people.
12:11And all we're getting is we're collecting$2.99 at a time. It's kind of hard to make math work. And then at the same time, we had another kind of part of the customer cohort, which was these businesses or teams or professionals where we were still charging them$2.99. And maybe we had a pro version like$7.99. sense. But you could see that there was a lot more functionality they needed, and they'd be willing to pay a lot more if they had that functionality. And so we were in this kind of wilderness period in 06 to early 07, which was we might have to kind of decide one path. Are we going to do this consumer thing head on with the big tech companies?
12:47Or do you go after this enterprise market? Are you trying to split the baby? The team was like, I think we have to do enterprise. We have to be a B2B product. And I was actually the first to resist it because there was nothing cool about doing enterprise software in 07 or 06. And so I resisted it, but eventually the conviction built that, okay, we probably can't survive as a consumer company. So we did a relatively hard pivot. We said, we're going to go enterprise. And where it gets a little bit more near death through that pivot, unfortunately, the economic recession kicked in. So that was a really complicated exercise.
13:18But we were lucky that we got Mamoun from now Kleiner back then, USVP led our Series B. And he kind of went head to head in some respects with the partnership and said, I want to bet on this team. And we looked nothing like what they were used to, a freemium viral disruption in the enterprise led by 20-year-olds. So that was a near-death experience because we could have gone out of business simply because we were in a business model transition, bleeding a lot of cash because of our subsidization on the freemium side. And then we had a couple of similar experiences later on as we scaled. Even the Series C, we were not yet fully crushing it on the enterprise front.
13:59And Royo Driscoll kind of really bailed us out on that one from scale. So we've had a few of these near-death experiences, usually related to the business model still needing a little bit more time to bake, running low on capital because we're grinding out the growth, which is why at this point I always instruct founders to be very thoughtful about burn, cash flow. But it's still getting the engine going was certainly hard back then. And what is it that caused enterprises to buy? Was there one key reason or one key use case where you were just 10x better than anybody else and that gave you the momentum?
14:38The killer app for us was secure file sharing collaboration in an enterprise context, which is Sally, Bob, Timmy, whatever. You can just sign up on Box. It was Box.net and then became Box.com. You can just sign up for an account, start using it, have a secure way to share and collaborate. And then we'd be able to go and talk to the IT department about, hey, there is a better way than using these on-prem legacy systems. Can we introduce you to Box? But we had this viral engine that was going and kind of getting us in the conversation. And then there were a couple moments that sort of added more inflection to that.
15:12So the iPhone, while it was launched when we were kind of more on the consumer side, it started taking hold in the enterprise. So all of a sudden you had mobile devices that couldn't tap into the on-prem systems. And then iPad was just one more version of that, which is you would have like an executive in a boardroom pull up an iPad and they'd be like, how do I get the board deck? And the company was like, oh, yeah, that's not going to work with our on-premises, you know, document management software. So they needed Box to go in and actually enable that experience. So we kind of had, you know, a bunch of these big technological shift tailwinds that we could ride where we were only a piece of that tailwind, but that tailwind was causing an architecture change in the enterprise that we could ride alongside, which you could easily extrapolate that as an important lesson for any startup and especially an AI as an example of like making sure you're on the right side of those tailwinds.
16:01And then maybe the only other final point was we were just simply cheaper, faster, easier than the incumbent. And so we could come in as this disruptive, you know, kind of easy land and expand product where it's all upside for us, all downside for the incumbent. And that let us sort of have this, you know, nice business model, you know, asymmetric advantage. Were some subset of the IT folks just hostile to you? Were they just like, get out of here? I don't even want your stuff in my company. I view you as the problem, not the answer. And where some just, where have you been all my life? This is amazing.
16:36I'm just curious, the spectrum of those early people, how many of them were early believers? How many of them were neutral to hostile even? One of the reasons why I have so much conviction on any kind of freemium or commercial open source type model in an enterprise context is it lets customers kind of select in to your funnel as opposed to you. You know, if you just imagine two completely different parallel universes in one universe, all you have is a bunch of, you know, account names and you have to go call each one and figure out where they are in their, you know, in their journey and, you know, how much do they like the cloud or whatever.
17:15And now alternative universe number two, you have a freemium product and all of a sudden you just see a heat map of like, oh, this company is taking off, this company is taking off that company is. Obviously, the signal to noise ratio is 100 times better in that latter scenario. We, by default, had the benefit of we could target and go talk to companies that were already using the product. That meant they were already a little bit bought in. Now, some said, okay, I don't want my users doing this. And so we actually are uncomfortable about you guys. But we tried to be very serious and professional and cognizant of the natural organ rejection that would happen in an enterprise context.
17:52So we were not a, you know, it's our way or the highway type company. It was very much like, hey, we'd love to hear what features would you want? You know, what enterprise products and capabilities can we build? You know, you're almost in this flow state between sales and product and go to market when it's working because you're not just like handing a sheet of paper to the salesperson and saying, just sell this is all you can sell. You're giving that salesperson the ability to kind of bring us feedback and we're going to go and build that. And so and that that became this really nice flywheel.
18:20And so it's funny, though, because, you know, I have to I have to kind of, you know, call this out as a blind spot. Like, you know, I think a lot of founders have to do that all themselves. And this is where you have a lot of these founder led sales kind of dynamics. I actually didn't. But but but only by virtue of the freemium model was generating leads. And I kind of saw my saw my role as as being the kind of, you know, arbiter of, you know, what are what are what's the sales team hearing from the customer? What are we building on the product? How do we get that flywheel going? So I certainly talked to customers, but really the sales was really all happening from a classic sales team.
18:53Yeah, to me, the sales learning curve is really interesting as a notion. One of the reasons I find it so interesting is I think it's easy for startups to get fooled about whether they really have product market fit. And so I've got, you know, everybody's conspiring to tell the founder that he or she has it. because the seed investors want to raise an A round, so they want to pretend that you have it. The entrepreneur wants to believe that they're making progress, and so you're looking for any positive signs of life that you can find. One of the things that I came to realize was that progress down the sales learning curve is a very good heuristic for product market fit, because you can ask yourself, when I add an incremental salesperson, can they pay for their entire burden cost across the entire company and how soon can they do that, right?
19:42If you can do that, you can hire salespeople at will, which I'm going to assert means you have product market fit and there's no debate. If you can't do that, then the question becomes, okay, where can you and where can't you? That's the friction between you and strong product market fit. But it's a way of saying, hey, look, I'm not being a distant critic here. It's just there's a set of salespeople and they're at a certain level of progress down the learning curve. And we can assess, right, if we're a one out of 10 or 10 out of 10 based on that. Yeah, that's super interesting. That brings to mind kind of an adjacent thing that Rory, when he joined the board, he had this mantra of just like hire a sales rep every month, like clockwork.
20:24That'll show you what's breaking in the business and or what's working. By the time you have six sales reps, if you have leads for four of them, it's going to cause the marketing team to kind of have to step up. Obviously, you get to a point where like, if none of them are performing, then you don't have product market fit. But it's kind of causing this ability in the business to test what's the upper bound versus I've seen a lot of startups with product market fit hire too slowly, because they're trying to kind of like hyper optimize, you know, each reps productivity rate or whatever. And it's just like, no, no, just like keep hiring sales reps, let the business, you know, kind of grow into, the amount of capacity you have by forcing these other parts of the business to step up.
21:04I am convinced there's been no important company that's gone out of business because they hired too much go-to-market capacity. But there's been lots of companies that could have won their market by having more go-to-market capacity. So I think it's more fatal to have a window of opportunity and you sort of didn't build that rhythm fast enough than, okay, I built it up, the market It wasn't there, you know, because that means you wouldn't have worked anyway. So, like, who cares? You know, what was it like as the company started doing better and, you know, you started to become a real company? You're not a startup anymore.
21:36It's no longer zero to one MacGyver juking and jiving, going from a jazz band to sheet music, you know, where you're trying to hire execution-oriented people and trying to manage that. What was it like from your perspective? Because it probably felt pretty different than the early days. Yeah, although that's a great analogy. But to be totally fair, I think we've probably only done the sheet music thing for like a year in any stable way. So that's about as long as it lasts in this industry. But there was a period where from 2010 to let's say 14, maybe it's a nice period, which was we were doubling or tripling each year.
22:17that was causing us to put more fuel on the fire, relatively capital inefficient. But what we had conviction of is that we were acquiring these long-term value kind of assets in the form of customer cohorts that would pay off within two years, let's say, of the acquisition. And so you just want as many of those as possible. And so we did that about until maybe 200 million in revenue. And then obviously just large numbers kind of kick in. You're scaling a little bit more slowly. But I'd say that was the sheet music period. And then we sort of had to figure out that, okay, we can't just be a one-act company.
22:52We're going to have to sell more into the customer base. We have to build out more platform capabilities. We have to have a whole sort of series of security and governance and data protection solutions. So that was a journey where we had to then go from a single product to a multi-product act. That's kind of like back to, let's say, jazz band again. And then you kind of get your sheet music for a couple of years. but then boom, COVID happens. Now you're back to kind of figuring out what's changed, what's new. So I'd say, you know, there's, at best, I've been able to have a calm demeanor for like six to 12 months in this business.
23:26And speaking of, you know, now we've got AI. So, you know, we're back in, we're back in, we're back in jazz band. Yeah. And you've talked about AI's potential for years, but more recently, you know, I've seen you talk about it even more. I'm just, you know, could you walk us through how you're thinking about AI's impact on content management collaboration and how's it evolved from Box's early days? Yeah. So for us, this is almost a complete, you know, sort of reinvention of the company. And if Box feels more today, like it did 17 years ago than any other point in the history, in the sense of the just sheer amount of change that's happening in the business and outside the business and the kind of clear feeling that you have to jump on it with actually the added stress slash excitement of the speed of innovation happening from the AI model providers is insane.
24:25The change of behaviors is happening faster than I've ever seen. The wired in and connectedness of everybody participating in it is just incredible because we're all in the same platform talking to each other. But it very much feels like, to me, we are in hardcore startup mode, reinventing the business because of AI. And the reason why it's elevated to that is in our business and industry, we store unstructured data, financial documents, contracts, invoices, marketing assets, resumes, project plans. All of that data is exactly the data that was relatively opaque to your computer before AI. You created a file, you stored it somewhere, maybe you'd remember to go back to it, maybe you'd find it at like, you could find the file name and search for it or some words in the document.
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25:15But that was the only real reuse of that data. That was the only real value you could pull from that information. And now AI lets us basically talk to all of our data, understand what's in it, you know, sort of transform it in really interesting ways, like go look at these hundred research documents and find the trends that I need to pay attention to. It lets us pull out data from the unstructured data so we can automate the workflows around it. So you could say, hey, I want to automate all my contracts or all my invoices in a way that before that required a lot of manual labor or really, really expensive technology.
25:49So for us, it's basically a reinvention of the entire category that we're in where we can now go and solve these very previously unsolved problems around how you work with your data. And so the big question we're asking ourselves is, if we were to have started the company today in 2025, what would we be doing as opposed to building on and kind of being path dependent on the things that just because we've been in the business now for nearly 20 years that we'd be doing when AI happens? So how do you make sure you're kind of running the business and operating as if you just started fresh today? And I'm curious, as is true in any zero to one or dynamic phase of life in startups, you get surprised, positive and negative surprises.
26:39What has surprised you so far about how your customers want to embrace AI? Yeah, so probably the biggest positive is that if I were to compare and contrast it to the cloud, when the cloud was emerging in the enterprise, and we would meet with customers, and I'd go to the banks and the pharmas and the big manufacturing companies in 2010, 11, 12, 13, etc. cloud was sort of seen as begrudgingly we might adopt the cloud. And probably if we do, it's only going to be in one part of the organization where it's more limited in its impact. And now if I contrast that to today, everybody is sort of saying, holy crap, like, I probably need to really get on this AI thing and figure out what parts of my business am I going to be running entirely differently because of AI.
27:26And then that cascades down into the IT organization. That causes the IT organization to say, oh, crap, what's our AI strategy? How are we going to run the business differently? HR is asking similar questions. What does this mean for which parts of labor do we have to make sure really understands AI? And so I would say that this is a positive surprise in that there's been almost no convincing that this is maybe the most important thing that will have happened in business in the 21st century or 20th century even because you're basically bringing automation to knowledge work. And so now it's much more of, okay, how do you do the change management?
28:04How do I work through the policy committees? Which vendors do I work with? What's the reference architecture that I need to land on? But it's not being held up by major philosophical or technical impediments that cloud, let's say, had. So I'm curious, you probably have thought about this question some. You know, a lot of people talk about AI and does it give the incumbents the advantage? Does it give where does it give startups the advantage? You know, I tend to come at these questions from a perspective of under what conditions. Right. And so but I'm curious about your thoughts about that. You know, if you were if you were a zero to one startup founder now and a bunch of people listening are.
28:45How would you be thinking about this and how would you be making sense of what opportunities are worth pursuing and which ones are probably not such a good idea? I would probably start with the premise that most incumbents are like awake, they're alive. Probably most are either being run by founders or like deep product people enough that they're not gonna miss some kind of window that's happening right now. So I'd start first by just saying like the incumbents are gonna execute. Most of AI is sort of aligned with the incumbents business model. And so it's not inherently disruptive. Plenty of asterisks to what I just said.
29:19Google is gonna have to figure out how does AdWords work in an AI world? The call center software companies will have to figure out how AI works when you might have a shift in the number of agents, lots of asterisks. Where the opportunity probably is, is in domains or, you know, I'm mostly just thinking about AI agents at this point. So I'm going to kind of, most of my examples will lead to that. But in domains where there's not a classic kind of incumbent piece of software for that domain, because it was so manual. It was maybe only able to be done by people. And now for the first time, you actually have software opportunity in areas that were just previously kind of manual knowledge work, let's say.
29:59And that you just have, we can already see tons of examples. I need to take this marketing advertisement and translate it into five different languages. Like there's no software incumbent that is sort of like the obvious player in that space. Now, maybe Adobe enters that space or whatever, but you're not inherently going after an existing software incumbent. There's going to be tons of white space in every single field and every single domain that looks like that. There's going to be a lot of white space in sort of AI that requires kind of pan system, multi-system, you know, kind of AI experiences.
30:34These are, let's say, the gleans of the world, or maybe there's new cybersecurity AI products that kind of have to work across multiple platforms. Then there's another set of use cases, which is just like in an AI enterprise, what new problems emerge in the infrastructure management that didn't exist, you know, pre-AI. So there'll be new governance products because, you know, your AI is now producing a lot of information that has to be retained and governed. So you can kind of like go through a list and see definitely lots of incumbent opportunity, but lots of white space because there might either not be existing software or there might be new horizontal opportunities.
31:09And then I just maybe throw out one more asterisk, which is even though I said that incumbents are kind of awake, alive, and going to move quickly, 30 % of the companies will not fully capture the potential opportunity. Startups will find a clever wedge that the incumbent missed. And it was just a little bit too weird or a little bit too different from their core business model to go after. And then boom, you have the new startup emerge that can kind of move fast enough that it hits you know, escape velocity. So one thing I've wondered about, I don't think we've ever talked about this, but one of the things I've noticed is when you have these sea changes, like let's talk about, say, the microprocessor.
31:50I have a list of 13 different business models, and I haven't found a new business model in the last 200 years. So like, you know, marketplaces existed in Mesopotamia, and the most recent one I'm aware of is the subscription business, which came out about 200 years ago in England for magazines. And so one thing I noticed after looking at this, and the GPTs can be really helpful for this, but like when the microprocessor came out, there was a shift in value creation to licensed software. So companies like Microsoft and Oracle and SAP emerged. That had never happened before. Software was the thing you gave away to make the mainframe run because the mainframe was expensive.
32:33But now all of a sudden, microprocessor makes computation asymptotically free, then the internet comes out. And to the best of my ability, I can't think of a software license model company that mattered, that was created like much after 1990. And the new software paradigm became SaaS and subscriptions or advertising. And so one thing that I've kind of noticed is that when there's a technology sea change, the technology shift is so profound that there is a migration of attractive business models. And so if I was a startup, I would be trying to pick a business model that is not ad-based or not subscription-based.
33:16I would try to understand where the empowering conditions of AI give me the ability to exercise business models that would have seemed previously unattractive that are all of a sudden attractive. And like the internet empowered people to get global distribution, right? You can't have SaaS without an internet because you've got to be able to get distribution to everybody and you've got to be able to charge a subscription and stuff like that. So I'm curious about if you've thought about it that way some, about, you know, kind of about like just counter-positioned business models, if you will. Yeah.
33:48I mean, I think you layered in a much more sophisticated, thoughtful approach. I think by analogy, I would say the AI platform shift enables a work unit business model that we never had digitally before. Answer this number of customer support tickets, read this number of documents and give me back a review of them, find this much research in my library of data, write this much code or entire applications. So we will probably need to move to some unit of output where the customer is kind of paying for an outcome or as close to an outcome as possible. AI lets you do that for the first time. But to your exact point, it's not a new business model relative to the past century, or sorry, five centuries, because it's what we used to pay people to do.
34:37And now you're going to pay software to do some of those things as well, which is a brand new business model dynamic for software. Yeah. And in some ways, I find it inspiring. If you buy the premise that there is is pretty much a not that changing list of business models. It's kind of inspiring to think that, well, if AI is that big of a deal, you had mass computation with the microprocessor, you had mass connectivity with the internet. Now maybe you have mass cognition. And if cognition becomes asymptotically free in certain domains, what are domains where it hasn't been up until now, where that was a bottleneck and now all of a sudden it becomes abundant?
35:20Yes. It just seemed all my instincts tell me that huge companies are going to get created on that. Yeah. Yeah. And this is I mean, maybe I'll be proven wrong at some point, but but I tend to be a pretty staunch AI optimist because because to your point about let's say let's say cognition gets, you know, asymptotically cheap, asymptotically cheap. And then you have this AI layer that sort of packages up that cognition for applied use cases. There's always this debate of like, that doesn't that only or just go after people dollars, let's say. I tend to have more of the take, at least somewhat biased by how we deploy AI internally at Box, how some of our customer conversations go.
36:00So I would say the bigger opportunity is actually, you know, where is there the widest amount of gap between that cognition scarcity and the customer demand, you know, for that, you know, cognitive capability. And that's actually where you're going to see really big businesses get made, which is not the world pays$20 billion a year for human labor, you know, for this particular function. Now AI can do it. So now that'll become$5 billion of software revenue. And that's the end of the market. Like it's going to be areas which is like human labor, you know, was five billion of spend globally on this thing, you know, but it was artificially capped because nobody like could hire a full time person to do that one thing.
36:41And so now AI comes in and you take a traditionally human, you know, oriented space at five billion. But now software has actually made it a$25 billion market because now everybody on the planet can access that thing. And that's really the more exciting opportunity. And actually, I think you'll see a lot of jobs flow because those things actually have many adjacent things that then the human still has to go do. Yeah. And, you know, whenever you make something that was once scarce, abundant, you you create entire new usage context. Right. So, like, for example, I'm a big fan of Clay Christensen and I have a database of every startup where you would have made 100 extra money if you'd invest in the seed round.
37:18And so now I can just say, hey, chat GPT, what was the primary job to be done for each of these hundred bagger startups that got them to product market fit? You would have been on a hike thinking about it, but you never would have been able to act on it. Now you can just, it's trivially easy to get that stuff. And so if you're a system level thinker, you can solve problems and kind of have the power of amplified cognition in areas you just, it would have just been infeasible. Infeasible. It's not a substitute. It's a compliment, right? 100%. Yeah. You've had quite an entrepreneurial journey so far, and it's still going.
37:55There's a lot of ambitious founders out there. What do you think they can learn from your journey to become the best founders possible? Wow. Okay. That's another hour-long podcast. So many lessons learned. I mean, maybe the quick highlight reel of just things that I, to this day, try and pay attention to. You always have to be on the right end of the technology tsunami that's happening. I've seen a lot of startups over the years just be on the wrong side of that. And then you just get wiped out. That can mean a bunch of different things at this particular moment, but always being able to ride tailwinds as opposed to having these overly fancy or overly sophisticated business models or strategies that required nine things to go your way, just ride tailwinds.
38:46You just always want to be on something that's going to lift you from an overall architectural shift. There's definitely a dozen exceptions to this point, but business strategy is kind of like the law of physics of startups. You should have a good strategy. You should know why the incumbent can't do what you're doing. You should know why you have some asymmetric advantages in the business model and why there's an actual innovator's dilemma moment. I think there's a little bit too much hope as a strategy sometimes. Again, you might be the lucky one, but I'd want all of the odds in my favor if I were a startup.
39:23The classics, the team really matters. You're going to be in the trenches with people 20 hours a day. So having an incredible team that you want to work with, that you're pumped to work with, never losing sight of just the product. There can be a lot of sort of fancy distractions when building a startup, but it ultimately always comes down to just, do you have the best product? And you can't really fight that. These are kind of the things I pressure test, you know, box on, you know, to this day of just making sure that we have all those variables in place as we're kind of transforming the business.
39:57Well, kudos to you. I mean, you've really stuck with it and built an actual real company. Thanks, Mike. Appreciate it, man. All right. Talk soon. All right. Peace. it. Thanks for listening to the Pattern Breakers podcast. You can follow me on X at M2JR, and I encourage you to check out our newsletter at patternbreakers.substack.com. I'd love to have you subscribe wherever you get your podcasts so you don't miss an episode. And if you like the show, I'd be grateful if you could leave us a review. Until our paths cross again, I hope you embrace the power of thinking and acting beyond the conventional boundaries.
40:37It's the people who dare to be different who truly make a difference.
From the publisher
When the team behind Box first went looking for funding back in 2005, they tried just about every trick in the book. They sent Bill Gates a fax. They dropped a prospectus off at Paul Allen’s house in Seattle. And they took a shot at convincing Mark Cuban to join two ambitious college kids with a hunch the way businesses stored and collaborated around information was about to change. Two decades later Box is a cornerstone of the cloud era with $1 Billion in revenue, but co-founder and CEO Aaron Levie is as restless as ever.
In this episode, Mike Maples, Jr. of Floodgate speaks with Levie about how he started Box when he was still in college at USC, why it’s fatal for startups to hire sales reps too slowly, and how he’s personally leading the way as the company looks to reinvent itself in the era of AI.
Check out the Pattern Breakers Blog at patternbreakers.substack.com for
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