The New Startup Playbook | Box CEO Aaron Levie

Can a 10-person startup outperform a company with hundreds of employees? Box CEO Aaron Levie argues AI agents are giving small teams a level of leverage that simply wasn't economically possible before, creating a window for startups to outrun incumbents. In this episode of Speedrun Office Hours, Aaron explains why founders are shifting from doing the work themselves to orchestrating agents, and why that puts a new premium on strategy, taste, and knowing exactly what to build. He makes the case that nearly every industry and job function could support specialized AI agents, potentially creating hundreds of new billion-dollar companies. They also discuss why enterprise AI may capture much of the next wave of model improvements, how dramatically cheaper AI labor could unlock demand that doesn't exist today, and one thing Aaron thinks AI won't change: distribution. If you build it, they still won't necessarily come.

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

• 0:00Aaron Levie?

  Startups can actually outrun these big companies in a way that was just never economically feasible before. You could actually go and compete in almost any category on the dimension of People are missing this whole thing. I really think that there will be hundreds of companies that are all 1 billion market cap, 5 billion market cap, 10 billion market cap and beyond, that basically are just, there's near infinite opportunity for new startups to emerge on the basis of

• 0:27Speaker 01

  AI is giving small startups something they've never had before. The ability to deploy resources at a scale that once belonged only to big companies. In this episode of Speed Run Office Hours, Box CEO Aaron Levie explains why a three, five or 10 person team can increasingly produce the output of a company many times its size. Aaron breaks down how founders are becoming managers of AI agents, why strategy and taste matter more as execution gets cheaper, and why he expects specialized agents to emerge across nearly every industry and job function. But one part of the startup playbook hasn't changed. Distribution. As Aaron puts it, if you build it, they will not necessarily come.

• 1:10Speaker 01

  Aaron, welcome. Thanks for joining us.

• 1:12Aaron Levie?

  Thanks for having me.

• 1:13Speaker 01

  It's kind of interesting that, you know, you're actually still a young guy, only a few years older than me and probably similar to Andrew, but you've been running Box since 2005, which is almost exactly half your life. If you could compare the world of startups now to the world as it was back then, what do you, what do you think about the startup experience has changed?

• 1:34Aaron Levie?

  My biggest takeaway actually is I feel really old, so I appreciate, I appreciate that you're using your age as the anchor for what young is, but, but, but I think unfortunately I tend to feel like very old now. And I mean, I am like so impressed and excited by so many of these young founders right now. And you know, what's interesting is that in 2005, so we dropped out of college, our middle of our junior year and in 2005, you know, it was, it was fairly rare to drop out and kind of be, you know, 20 doing a startup. There were, there were a few dozen of us in the, in the Silicon Valley at that time.

• 2:19Aaron Levie?

  You know, I think prompted probably mostly by like Facebook had made dropping out like a thing, but it was still a relatively rare event. And what is so fascinating now is the amount of now 20 year olds that are dropping out. It's, it's like, it is just like now a standard playbook for, for these kids. And, and so I think it's, you know, it's, I think it's super exciting how, just how many young people are, are getting started and, and jumping right into, into building startups. So I do tend to feel pretty old, but, but yeah, the playbook seems incredibly different. I mean, the way that startups are being run right now is, is the most different than any other period of technological change that I've ever seen.

• 3:05Aaron Levie?

  Where, where if you looked at like, if you looked at how we ran Box in 2005 and you compared us to a startup 10 years prior. So let's say you took the 1995 company and then the 2005 version of a startup. It actually wasn't that different. You know, we, at least in 2005, it was a little bit right before the cloud wave. We still went to data centers, we racked servers. You know, we, we coded morning and night, we, you know, we, we were, you know, a startup. But if you, if you kind of like looked at how we ran the company in 2005 compared to 95, it would almost look exactly the same. Like the way that every 95 startup got started looked exactly like how we got started and ran the business.

• 3:48Aaron Levie?

  If I compare the 2025 startup to us in 2005, or let's say the 2015 startup, so if you just use 10 year increments, it is the most different that I've ever seen in the history of, of, you know, my adult life and doing technology now for 27 years, let's say. And it's simply because of, of this AI first orientation, where you can be a three, five, 10 person team and have the output of a 50 or 100 or 200 person team. And that just, that just changes everything about how you run these businesses. So I'm, I'm wildly impressed by these startups. I also think some of them are just totally crazy and unhinged. But it's, it's fun to watch and fun to learn from, but it is the most different that I've ever seen.

• 4:32Aaron Levie?

  You know, how to, how to build a company today.

• 4:35Speaker 01

  I mean, on that point, it's kind of interesting, right? Like, like if, in, in the case of where you and your co-founder, you guys dropped out, right? If you had the ability to force multiply with like AI agents, for example. I'm curious what you're seeing, you know, I think, I think you wrote about this recently, how some of these startups are in particular, I think, like doing things in the background or they're using AI agents in sort of like interesting ways. What's, what's been the most craziest thing you've seen so far?

• 5:01Aaron Levie?

  Well, well, like, like if you just take the, the basic premise and then, and then draw it out, like,

• 5:06Speaker 01

  Yeah.

• 5:07Aaron Levie?

  When we started Box, our, our rate of, of progress as a startup was 100% correlated to how many hours we could be on a keyboard and type things. That was, that was the, that was the, the, the only, the only point of leverage we had was how fast we could type text into a keyboard. And we could be typing code, we could be typing marketing assets, we could be, we could be typing blog posts.

• 5:33Speaker 01

  Right, right.

• 5:34Aaron Levie?

  We would, we were managing servers, but, but the four of us, what we, we all kind of dropped out. We lived and worked in this, in this renovated garage kind of live, live works kind of thing. And, and that was the only speed at which we could execute was how fast we could work on computers. The startups that I'm talking to now, it's, this is not, you know, exclusively the case, but, but let's say it's, it's increasingly the case. It, it seems like there's now a new sense where the startup founders and the early employees, and I think this basically, you know, sort of scales to, to every industry over time. They're more managed, they're more managers of work. And the work is being done by agents. And so they're no longer rate limited by how quickly they can type

• 6:19Aaron Levie?

  and how quickly they can write code and how quickly they can come up with marketing assets. They are deploying agents to go and do a lot of that work. And I was talking to a startup founder recently that, you know, claims at least, and I, I mean, I basically believe it. He's just reviewing thousands of lines of code a day that the agent did. And the ability to be an editor or reviewer is like 10x the leverage of, of the person who actually has to create the thing. And so if you, if you kind of have that as your mental model, where this person now is the editor orchestrator reviewer of, of code, and they can go on and deploy multiple agents, so they're no longer rate limited by, again, like one terminal, one user interface that they can interact in.

• 7:00Aaron Levie?

  You can only type in one IDE at a time as a, as a, you know, individual kind of programmer, but I can review, I can, I can, you know, have lots of agents now running in the background. I can go review their work, you know, when they're all done. That's just a totally new form of leverage. And so now the bottleneck is just reviewing code, orchestrating it, integrating it, kicking off agents. The bottleneck is not just, you know, how much code have you written? So I'm mostly seeing it on the engineering side. So the big benefit is it's giving startups a new form of leverage that never existed in the startup world. Usually you're, you have this deficiency as a startup, which is you have two or three people and you're attacking some big incumbent that is 100 times more people.

• 7:41Aaron Levie?

  And you can basically move faster than that incumbent, but that incumbent can always deploy more resources. Well, we are increasingly neutralizing that delta because of agents. We're not fully there because agents make mistakes. There's no, it's not a panacea. You know, a lot of people describe it like a slot machine. You have to keep, you know, trying over and over again and seeing what the agent comes back with. But you can kind of squint and sort of see what this could turn into, which is, imagine a world where the agent could do a few thousand lines of code that was really high quality and adhered to your code base standards. And it, and it really worked and you reviewed the code and you only changed a few things. Well, that would mean that you do have now 10x the engineering capacity as a startup,

• 8:23Aaron Levie?

  which mean you could actually go and compete in almost any category on the dimension of scale and speed, which would, which would change everything about competitive dynamics. And then as an interesting disaster, the big companies find it very, very hard to actually go and equivalently do that because they have a lot of workflows, a lot of processes that are so wired into how they already operate, that they won't be able to make the, the change fast enough. So you have a window where startups can actually outrun these big companies in a way that was just never economically feasible before. And it's, it's effectively all due to AI agents. So again, starting in code, but I think, I think the most kind of wired in companies are figuring out how to do this in marketing. They're going to figure out how to do in legal work.

• 9:07Aaron Levie?

  They're going to figure out how to do in outbound sales. So that, that will be a pretty interesting application of the, of the

• 9:14Speaker 01

  I guess the thing I'm wondering about Aaron is then like, you know, we've always talked about before that like sometimes everyone wants to work at, at the work at the speed of strategy, right? And they want to be able to work at the speed of, you know, creativity and thought, right? And like, nobody wants to spend all their time writing marketing copy unless you're, you're the, you know, start your Silicon Valley's favorite internet comedian like Aaron Levy. But I, I mean, I, I do think that there is this question though, that if you are now can be more strategic though, the decisions you make actually matter quite a bit.

• 9:40Aaron Levie?

  Yes.

• 9:41Speaker 01

  Like you could really, like, you might really like mess up. And then luckily it doesn't cost that much, but you're still going to mess up. And in fact, like really the speed of creativity and, and sort of the chessboard actually matters more.

• 9:52Aaron Levie?

  Yeah, I think, you know, one thing that, that is interesting is, is so that the tendency appears to be that the way you're building software now, at least in these startups, is you get really, really clear prompts or specs.

• 10:07Speaker 01

  Right.

• 10:07Aaron Levie?

  You get very, very clear ways of working with agents to understand your code base, to, you know, build sub-agents at the right, you know, parts of your code base. And there's an increasing, you know, view of this sort of spec driven development, which is you write, you write very, very in-depth specifications about what

• 10:24Speaker 01

  Sure, the idea of the product engineer, right? Like the product person, actually, you know, the, the pointy haired Dilbert product, product manager now truly actually has the power to, to do their own stuff.

• 10:35Aaron Levie?

  You wait long enough and they become, yeah, very, very powerful, but, but yeah. So it turns out if you're really good at writing a spec and you're really good at knowing and having clarity about what you want to build, that's actually extreme leverage now. So, so there's a huge premium on knowing, on, on actually being very good at, at strategy, being very good at, at like, what is the market opportunity for what you're building? And, and not just, you know, previously there used to be probably a premium on just like, how quickly can I hack something together? Well, now actually, because the hacking something together is, is fairly commoditized, the premium is, is have you thought through what, what you're actually trying to build? Is there a real market opportunity for it? Is it a good idea? Does it look good? Does it have taste? Like those are now the new, the new, you know, forms of value creation.

• 11:19Aaron Levie?

  And so I, I do think that the companies that are really religious about getting that right will be the ones that, that get ahead in the future.

• 11:27Speaker 01

  I guess the question behind this is, okay, so let's assume that if you're a startup, you effectively have all these tools at your disposal. You could obviously adopt one of the bigger folks, right? And then the issue is that you've argued around this idea of like sort of AI context rot, which basically like the way to solve that is to actually have these sort of like point solutions potentially, or like great sort of well designated agents, as opposed to having the the single sort of ultimate, the ultimate fighter, you actually have like a team of the ventures to go and help you in the world of AI. I guess like, if you're that startup, right? And you're trying to figure out like, what's the agent architecture that you kind of ship with first? What's the fast way to get off the rails? It's one of these things where, you know, it's at what point do you just give up everything?

• 12:10Speaker 01

  And at what point do you start filling out, you know, do you just start with like a basic toolkit, for example?

• 12:15Aaron Levie?

  Well, the point I was making in that context is not so much about the number of tools you use as much as as the need for specialization in some in some virtual or or very tangible way. And so like, for instance, Claude Code has created a way to have that virtual specialization by just letting you go and create subagents that that own a particular part of your codebase, or a particular part of your workflow. And that's sort of how you resolve the context rot issue within within the Claude Code kind of paradigm. So, so it's not so much that you want a tool for everything. It's that it's that we have a very real issue, which is this, you know, like, super powerful, super agent doesn't exist, it doesn't work.

• 12:58Aaron Levie?

  And so you do have to have some degree of specialization. And that specialization can come, you know, in a variety of of packages. I think there's like, there's a YouTube video on every every way to solve this. If you ask, you know, three startups or five startups, you're going to get three or five different answers. And it's totally fine, because this is sort of, this is the stage where everybody's kind of figuring out the best practices, and it's all emerging right now. But I don't have a, I don't, I can't give any kind of general principle on that, because it's just different by team, by company, by what tool you choose.

• 13:30Speaker 01

  But it would seem that at the very least, your perspective is there is definitely not like, this is not just going to be able to go and benefit incumbents. There's this unique opportunity. If you could be one of those specialized tools as a startup,

• 13:40Aaron Levie?

  Yes.

• 13:41Speaker 01

  that's, you're in a really, really good spot. Like, you can basically remake the whole, whole area of the stack.

• 13:44Aaron Levie?

  Yeah, okay. So now, now, if I flip it, if I flip it a little bit, because I was mostly answering the question through the lens of, generically speaking, the fact that AI startups can can move 10 times faster than an incumbent, that's fantastic. Now, if you think about it, okay, what does that mean in terms of what you should build? How should you compete in this market? You know, what, like, I think there's infinite, you know, that's obviously, you know, a little hyperbolic, but but there's near infinite opportunity for new startups to emerge on the basis of, we are going to see a complete shift in the in the software landscape, because so many, so many industries and parts of business

• 14:25Aaron Levie?

  that previously didn't have software, now will have software in the form of AI agents for the first time ever. And if I, if I look at like, most domains of knowledge work, will have a, some kind of agent that is associated with that type of knowledge work. Incumbents will take some categories, but there'll be startup opportunities in every single category for basically building agents that do knowledge work. And the first ones that that have reached some degree of critical mass are coding agents. And there's been, you know, very clear startup opportunities in the form of Replit, Cursor, Windsurf, Lovable, Cognition, like, like, holy crap, if we had said 10 years ago, that there'd

• 15:08Aaron Levie?

  be 20, 30, 40 billion dollars of market cap in the coding space, and we would have been like, well, kind of GitHub is the only thing that's ever really even exited in the coding space. How could there be 30, 40, 50 billion dollars within just a three year period? That wouldn't sound plausible. And so, and yet, that, that, that's, that's not only happening, but it's actually just scratching the surface. I'm, I'm perfectly comfortable underwriting a couple hundred billion dollars of market cap in the AI coding space that don't go to incumbents, purely because there's just so much surface area, so much TAM that needs to exist. Okay, now do that for every single field. Do that for, for life sciences, do that for healthcare, do that for legal work, do that for consulting. There is going

• 15:53Aaron Levie?

  to be new AI agent companies in every single one of those spaces. And not only will they outrun the traditional software incumbent companies, they'll actually, they're going to outrun the traditional services companies in those spaces as well. And, and it's just a completely new environment for startups to emerge.

• 16:14Speaker 01

  You said something at the beginning, the beginning of this conversation that I thought was interesting, which was, when you talk to founders, you feel like you're, you're doing the learning about 70% of the time. I was curious if there's anything that comes to mind, like, what are you learning from kind of the new generation of founders when you do speak with them?

• 16:32Aaron Levie?

  Yeah, I think it's mostly, I mostly just have to rethink the leverage that you get from from agents in every, in every conversation. So, so if I, if I took an example conversation I would have had with a founder a year ago, and you say, hey, how are you using AI? And again, the standard at that point would have been GitHub Copilot, maybe a few uses on Cursor. They would say, yeah, I'm getting 10 or 20% productivity gains. It's really helping me with, you know, type ahead, autocomplete functionality. It's, it's like, replace me needing to Google, you know, when I have a, when I have a search, when I have a coding question. Now, if you ask the most advanced startup founders, you know, how are they using AI? It's back to this point. It's, it's not a, it's not a, it's

• 17:16Aaron Levie?

  not a 20, 30%, you know, form of leverage. It's a possibly a three to five to 10x form of leverage because of this ability to have background agents. But the problem is, is again, in your existing teams, and your existing organizations, your existing way of doing engineering is not wired up for kicking off lots of background agents to go and execute on your codebase. Your codebase isn't designed in that way. You don't have the documentation in the codebase, in a lot of times, to support agents to go and operate on the codebase. You don't probably have the tool stack to be able to do that. You haven't done the engineering methodology change to enable, you know, dozens or hundreds of people to go do all this at once. It actually is something that that benefits a small team, where, where

• 18:01Aaron Levie?

  they're not going to have all these conflicts happening at all time across all these agents. And so, and so this is something that naturally is advantaged for the smaller startup to be able to move quickly on. And so when I'm talking to startups, I'm mostly just learning, how are you doing that? Like, and then trying to figure out, like, what's my way of bridging our company to do that as quickly as possible? So we can, we can take, you know, a lot of the benefit of these learnings and port them into how we run bots.

• 18:29Speaker 01

  That makes so much sense. All right. So, um, let's, let's, you know, circling back to the, to the first, our very first question. I'm curious how you're thinking about, if any, like, important things you think folks, you know, obviously, we've talked about leverage, agents, the ability to basically be, you're a two person startup. So actually, choosing your founder really matters a lot more. Because effectively, that's equal to like, 2,000 people.

• 18:52Aaron Levie?

  Yeah, exactly. Yes.

• 18:53Speaker 01

  But, but I mean, like, thinking through that, that paradigm now, like, if you were, you know, picture Aaron from dropping out now, right? What would you, what would you, you tell Aaron now?

• 19:07Aaron Levie?

  Yeah.

• 19:08Speaker 01

  We've already talked a lot about it, but what are the sort of like, more basic building block things? Maybe, does anything change there?

• 19:13Aaron Levie?

  I think a lot of the core principles of company building are relatively, you know, timeless, and they transcend any particular technology wave. To your exact point, you know, team probably matters more than ever before because of the leverage on your, on your co-founders or co-founding team. So, so that, I mean, that's a great insight. So that was yours. So, like, I just would underscore that, that point.

• 19:36Speaker 01

  What about market, for example? Like, some folks have said, you know, try to find the most highly specialized, really boring market on the planet to find regulatory capture, maybe. Or you like, forget about that, that's not going to work for you, man.

• 19:48Aaron Levie?

  No, no, no. So, so, okay. So, so there's, well, there's some things that are downstream from you have the idea. But if you want to go all the way up to, you don't have the idea yet, then then I'll be able to start there. I think, I really think that there will be hundreds of companies that are all 1 billion market cap, 5 billion market cap, 10 billion market cap, and beyond, that basically are just, they're taking a job function in the economy, and they're building an agent for that job function, and they're selling that agent to corporations, to services firms, to system integrators, to everybody. And, and I think you could literally do, maybe Andreessen has one of these, you could

• 20:27Aaron Levie?

  literally do a, a matrix, that is, every industry and every line of every job function in, you know, per industry. And it would be like, it would be literally 5,000 cells. And it would be like, there's sales reps in life sciences, there's lawyers in financial services, and some of the markets, you know, probably will be TAM constrained, but some will be much bigger. Some need to be kind of like, okay, we have to get the whole horizontal, some will have to be, we'll have to get the whole vertical. But I think you could very easily go through the entire economy and underwrite AI agents for any one of those slots in the economy. And, you know, if I had to literally start from scratch, I'd probably be looking at that matrix and saying, okay, is this, is there an industry I know

• 21:12Aaron Levie?

  extremely well? And that I can go and, and kind of really reverse engineer, like, what does the work look like in that industry and build an agent for that? Jared Friedman had this great tweet. He's a Y Combinator, and he basically said, like, go do the job of what you want the agent to go and automate and be like, the, like, the expert in how to do that job. And then you're going to be very potent at being able to go and create an agent to do that job. Right? And so, you know, probably like, the best case scenario is you've already done that job in the past, and you just go and build an agent for the work you already know how to do. Second best scenario, have a co-founder that has done that. Third best scenario, go literally find a way to like, do that, you know, shadow somebody, do it all day long.

• 21:56Aaron Levie?

  And then, and then the opportunity is, can you, can you make an agent that is like, the, the life sciences FDA regulatory review agent? Can you go do the, I am the, you know, legal review case agent?

• 22:08Speaker 01

  Right.

• 22:09Aaron Levie?

  And, and there's gonna be, again, there's gonna be a lot of flameouts, you know, in this space that are, again, like, they just didn't nail the scale, it wasn't the right market fit, you know, the TAM wasn't big enough, there'll be lots of that. But then there's gonna be a lot of surprises where it'll turn out that there's more categories than we think, where right now, the supply-demand equilibrium in the economy is actually not sort of, as, as sort of, kind of perfect as we would have imagined, where if somebody could have introduced labor at a tenth of the cost that it, that it previously, you know, was, was priced at, that there would be actually, you know, 50x the demand for that particular form of labor.

• 22:48Speaker 01

  That's right.

• 22:49Aaron Levie?

  And so, like, you'll all of a sudden be like, okay, I'm a legal review agent, and it turns out that, like, traditionally, legal review costs, you know, $2,000 per hour, or $1,000 per hour for high-end work, now the agent can do that for $5 or $10 an hour, and it just turns out that, like, we didn't actually have as many lawyers as the world needed, it was just that they were so expensive, so nobody could actually afford them, and then boom, there's an explosion of, of this new category of-

• 23:15Speaker 01

  Everybody's filing patents now. Everybody is gonna be an inventor of some sort, yeah.

• 23:18Aaron Levie?

  Like, I, I can name, I can name, I can name a bunch of use cases even internally. I'm not gonna, you know, kind of, you know, give too many startup ideas out there, but, but, um, I can name a bunch, I can name a bunch of ideas internally where if, if the cost of the particular function was a tenth of the price, we would, we would spend, we would, we would have many more kind of full-time people equivalent of that function. It's just, it's too inefficient right now, and so it is always at the bottom of our, our stack-ranking budget planning list, so we never get to it. But if it was an AI agent that could be compressed at a tenth of the price, then we actually would be spending on that agent, and it, and amazing-

• 23:58Speaker 01

  There's no ceiling. There's no ceiling to the ROI potentially, right?

• 24:01Aaron Levie?

  There's no ceiling to ROI, and there's no minimum floor price to get started. And that's the, like, people are missing this whole thing. Like, like, to hire a, a person costs $100, $200, $300,000, or whatever, depending on the function, to bring in an agent might cost $1,000. And so you will start using them in use cases that you never hired the person for. And that will then, all of a sudden, it'll, it'll kind of reduce the bottlenecks in your business in ways that you didn't anticipate, which then will cause you to actually go and fund those areas even more. So I think there's a lot of opportunity that will kind of look like that, but again, for an industry, for a job function, and I think there's endless opportunity, you know, in, in that general space.

• 24:42Speaker 01

  Yeah. I, I look forward to, um, after this, um, there's a, there all of a sudden, there's this giant surplus of young 20-somethings who end up as like admins in FDA-regulated back offices. Where did all these people come from? They're like, oh, Aaron sent me. Okay, I'm just, they're just here, they're really excited to go and work here. Really love our industry.

• 25:00Aaron Levie?

  I mean, I mean, what, what we probably need is like, we need this like pairing mechanism between, maybe you guys start it, it's like, you're, you're a strong, you're like, very clearly central casting CTO, you know, founder, you dropped that at MIT, and then you pair them with somebody who just like, you pluck them out of Pfizer, and you're like, you know how to do regulatory review processes.

• 25:22Speaker 01

  Right, right, right.

• 25:23Aaron Levie?

  We're just gonna match, and then, there's just, it's just a matchmaking service between the person that knows how to build agents and the experts in the workflow, and we just go create 100 of these.

• 25:31Speaker 01

  Well, so I, I'm curious to hear about this, right? Like, because Box started out as a, in the consumer world, then you guys went to enterprise, and in the past, even Mark, Mark himself over at, you know, at recent Horowitz once said, he's like, you know, really great founders actually start out in consumer, just because it's so hard to do consumer, you have to build products, it's very difficult to do. But in this wave, obviously with AI agents, it's way more focused on enterprise, and we're sort of making a tack where we kind of push toward, toward, toward, toward, uh, toward basically enterprise. How do you think about consumer? Do you still think that, like, that's a proving ground? Or is it one of those things where it's like, hey, that's, you know, that's just a completely different world that, that, we, no one knows how that's gonna change as we move to AI?

• 26:08Aaron Levie?

  Um, I, I think, uh, I think there's plenty of, of consumer opportunities. I don't think I would sort of pre-plan a pivot, uh, so, so like, like, like-

• 26:19Speaker 01

  That was not planned, Aaron?

• 26:21Aaron Levie?

  It kind of breaks the definition of, of a pivot.

• 26:23Speaker 01

  Yeah, yeah, that's right, that's right.

• 26:25Aaron Levie?

  So, okay, in six months from now, we are going to pivot the company, but we're gonna first start in a different state. Uh, so, so, so I, I would say that it's, it's probably still very good advice if people do need to pivot, but I think there's gonna be plenty of consumer opportunities, and-

• 26:40Speaker 01

  Yep.

• 26:41Aaron Levie?

  I'm, I'm partial to the enterprise, because it's a space that I spent a lot of time in. I think that the, I think, you know, by TAM, I would largely bet on AI being a breakthrough for the enterprise market by just sheer size of the TAM, um, simply because, uh, you know, AI is like fundamentally a form of productivity, and productivity generally shows up in a meaningful way in the enterprise. In the consumer space, it's sort of like, not a thing that, that we think about as much. Um, so I just think, like, most of the use cases tend to lean enterprise. Um, you know, and it's interesting, um, Dario, uh, from Anthropic had a, had a, had a point on a recent podcast that, that I just, I think is the most salient way to think about

• 27:22Aaron Levie?

  it, which is, you know, if, if they improve, if Anthropic improves, uh, uh, the AI model from, uh, basically being like a, an undergrad in, in chemistry, um, uh, to a grad student in chemistry, the consumer won't notice, you know, in Claude.ai. Like, there's no, there's no question you're gonna ask about chemistry in your personal life that, that sort of is gonna require that PhD level. I mean, you know, barring, barring you have some deep healthcare, you know, related issue.

• 27:54Speaker 01

  Yeah, yeah.

• 27:55Aaron Levie?

  But, but the, but the, the PhD jump is gonna have massive gains for Pfizer and, and the life sciences industry. And so just if you think about where we are in the, uh, kind of progress of AI, like, I think like, most, most of my, I, I'm gonna just pick on her, just because it's, it's, you know, kind of makes the point, like, my mom's AI use cases are like, they're like, fully solved, like, we're done. Like, she doesn't, she, she would be fine, she would be fine if GPT-5 was just like the, like, the last thing that AI ever produced, because it's already solving every problem.

• 28:28Speaker 01

  Because she's not, no more chemistry questions. She, she's done with her chemistry questions.

• 28:31Aaron Levie?

  She is not trying to create a new life sciences drug. Um, even, even in my personal life, like, for parenting, let's say, I think AI could stop right now, and it would already have been a huge, a huge net positive for, for me, and, and like, like, we'll make songs for the kids, we draw things, we get stories made, like, I don't need stories to be any better for my six-year-old. Like, we're, we're, we have reached, we have reached the, the full saturation of capability that is needed in, in most of my personal life. But, again, you go to a law firm, and you're, and you're like, hey, I ran this contract through an AI model, and it's like, well, there's like 70 mistakes. So by definition, and, and back to the original point, by definition, most AI progress is

• 29:13Aaron Levie?

  going to now amortize in, into enterprise use cases. So from here on out, it's an enterprise, you know, kind of industry, you know, with, with, again, plenty of opportunity for starting consumer companies, to be clear, but it's not because we needed the PhD thing, it's because we needed new packaging in a consumer app that, that sort of brought this experience together in a better or a new way.

• 29:36Speaker 01

  I mean, this is the, this is the sort of test I always check, we have Terry Tao, the, the Australian mathematician, right, like, says something, then he, then I'm just like, oh, things are going really well, he'll, he's gonna get us warp engines very soon. Um, so, so I, I guess, I'm curious how you think about the, we talked about this a little bit, which is that, like, you should have product insights, but in addition to product insights, you sort of need distribution insights.

• 29:57Aaron Levie?

  Yes.

• 29:58Speaker 01

  And it doesn't seem like, this is like, a big debate where some people say, AI's provided some clear product insights, but it hasn't changed the world of distribution in any way, but we obviously see some natural adoption of AI tools. But I'm curious how you think that might evolve? Is it because, like, you know, we're just waiting for things to platform, and then we'll have distribution insights in, in that regard? Or, or do you think that actually, it's a whole new ballgame, we're thinking about it like radio on television right now?

• 30:22Aaron Levie?

  I am gonna take the, I'm gonna sound really lame and possibly, you know, possibly very wrong in five years from now, I don't think distribution changes that much.

• 30:32Speaker 01

  Ooh, interesting, okay.

• 30:34Aaron Levie?

  I think that the, you know, there'll be new channels, like, you'll, you know, you'll be like, I'd like to show up in the OpenAI App Store, uh, you know, Asian store, like, like, there'll be new ways that you think about getting distributed, but, but I don't think this is a fundamental and, like, you know, transformation or disruption of the distribution model of, of tech. If you're a consumer, you better figure out how to go viral. Uh, if you're, if you're enterprise, you better figure out how to do, uh, you know, build a go-to-market machine. Um, if you're, uh, if you're fortunate and you're kind of like, and you're like enterprise-y, but your audience is, is somewhat technically savvy or, or able to do self-serve, then you'll do PLG plus a go-to-market engine, but I don't, I don't think we're gonna see a new

• 31:18Aaron Levie?

  invention of, of go-to-market, uh, uh, because of AI. I don't think AI is a, is a go-to-market-related disruption, uh, model. Maybe there's an important corollary, actually, and maybe, and this might be appreciated by AI startups. If you build it, they will not come. So, so if you think that because you built this amazing agent, that now you've solved your problem, like, that is like, totally, you're gonna fail. Like, like, you, you are gonna be drowned out by 10,000 other startups and priorities that companies deal with all day long, so if you do not think about distribution, then, then you, it just won't work. And, and I think we might have a little bit of an over-orientation toward the, hey, I

• 32:01Aaron Levie?

  made this really viral video, and everybody saw it, and I got all the likes, and that's not distribution, that's like a cool one-time marketing stunt. Like, distribution is, is just the grinding of like, like, you know, the way I kind of think about it, and I think AI affords this quite, quite effectively, you have to own an audience, there has to be a universe of people that are just so passionate about the thing that, that you're building, you need to figure out how to just continue to keep access to that relationship. Um, so you better own your community via LinkedIn and X and Reddit and wherever those people are, and, and you need to find a way to like, just bear hug them as an, as an industry or as a cohort. Um, and, and you need, and then that's gonna be marketing, that's gonna be salespeople,

• 32:46Aaron Levie?

  that's gonna be PR, all the things. Um, and, and the companies that discount that, uh, you're just waiting to be rolled over by somebody who has better distribution and just says, okay, I'm gonna get this in the hands of all the, all the customers.

• 32:58Speaker 01

  I look forward to every founder basically requiring every employee to have worked in that industry as a blah blah blah person, and then being like, oh, I worked in that industry for five, three, four months, just like when people say, like, you know, you have to have worked in customer service to know how to deal with customers.

• 33:12Aaron Levie?

  Exactly. All right. Uh, Aaron, thanks so much for doing this, that's a great one to end on, uh, so we really appreciate you for joining us.

• 33:20Speaker 01

  Awesome, thanks, guys. Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or review, and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z, and subscribe to our Substack at A16Z.substack.com. Thanks again for listening, and I'll see you in the next episode. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund.

• 34:02Speaker 01

  Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com/disclosures.