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The Agent Era- Building Software Beyond Chat With Box CEO Aaron Levie

The a16z Show

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  • Agents Move Work Up the Abstraction Ladder
    • Agentic work first amplifies people who already think in systems, then collapses into a higher abstraction layer everyone must learn.
    • Steven Sinofsky compares it to spreadsheets replacing rooms of interns, while Aaron Levie cites one Anthropic marketer automating work once spread across five to ten roles. Transcript: Steven Sinofsky I mean, I think you’re right. It makes sense in a theoretical way. Yeah. But in a practical way, we have to be really careful in that the way to say it is algorithmic thinking. Yeah. Is really, really, really hard for the vast majority of people who have jobs. Yeah. So the easiest way to think about it is if you were to go into any person and ask them to create a flow chart for a particular thing that they have to go do, they would probably fail at producing That flow chart. Yep. So within any organization, say doing a marketing plan and there’s 50 marketing people working on a giant product line, one person probably understands and could document the flow Chart. 100%. So you put one of these agents or you put this tool, this co-working tool in front of people to create these things, their ability to explain to it what to do is really, really limited. 100%. Aaron Levie But what if that becomes the new, this is the new way you have to interface with computers and you just have to cycle that through. Well, then you’re basically just developing the next abstraction layer for how people interact. Steven Sinofsky And developing an abstraction layer has historically, at each level of the abstraction layer, been a highly skilled, very specific individual within an organization developing That. And then the little parts that they build just become little toolets in the world of people doing particular tasks. And some people are able to stitch them together and some can’t. But that happened with paperclips and thumbtacks. Oh, yeah. And it’s going to happen with whatever we do next. Aaron Levie I think basically the timeless part is the job just moves up a rung and you learn a new set of skills. And that’s why I actually don’t think anything about this is any different. It’s just now the leverage you get is obviously fantastic. There was this viral kind of tweet that went around, which was the Anthropic Growth Marketer. Do you guys see this? Basically one person and he was using Cloud Code at the time to basically more or less automate what maybe five or 10 people would have done in various kind of silo jobs. And I think the reason why it’s interesting is you had to have been a systems thinker to be able to accomplish that. So like clearly he already was technical enough to be able to pull that off, but it did kind of represent what would each of these jobs look like if you had like, imagine you had, you know, X job in the economy and right next to that person was an infinite pool of engineers that could automate whatever that person wanted. And what would that job look like in the future as a result of that automation that now is possible? Yes, I agree that you’d have to find a way to think through your job as a system to be able to pull that off. Maybe the agent gets better and better over time at being able to like nudge you in that direction. But it does sort of stand a reason that like you will start to try and automate a lot of that kind of work of like, well, why don’t I take like the keywords that are working in this in Google AdWords and then port them over to Facebook and make sure that those are replicated and then take in the new signal from what’s happening in the market. That’s a big leap. Steven Sinofsky Yeah. So one thing first. I almost had you. You were nodding a little bit. I said something that went too far. Using the anthropic growth person as an example. That’s a job. That is the rest of work. Yeah, I could do that job. Everybody’s obviously going to be like the anthropic growth. When demand is infinite, you’ve got the best thing. Right. Like when demand is infinite and frankly, supply is infinite, this is not a difficult job. Martin Casado And so let’s- The guy that runs the petrol pump in Australia right now is amazing. Steven Sinofsky Right, right. So like be instead be the $600 PC marketing person and see how you can do against the Neo. That’s a real job. All right, we need a better example. Aaron Levie But there is, I mean, it is really interesting. Steven Sinofsky Like I here, let me do an old example, an old person example, like my cousin, MBA, elite school, joined her first job. She’s a little older than me, joined right on the cusp of computing. Like she actually didn’t use a spreadsheet in grad school. And then, a spreadsheet showed up, but she wasn’t a spreadsheet person. So instead, they told her, hire as many interns as you want. And so, her first year on the job, she, like, supervised, like, essentially, a whole room of agents. Yeah. And the kids, who was me, not literally, but they were in college, came and just did all the spreadsheeting. Yeah. But then what happened sort of magically over the next couple years was she and her cohort all became the spreadsheet people. And then this idea that you being a manager in a bank or just two years in meant you had a cadre of people doing this. No, the whole abstraction layer moved up. And the old job before those interns was you just sat there with basically calculators and an HP calculator figuring out the model for some M&A deal or whatever. And you only got to do like two iterations before you had to put out the pitch deck or just go to the customer or the client or whatever. And then all of a sudden, they’re doing 30 iterations themselves. But they see, and so I think where we are with agents is just at this step where you think you need 50 and the abstraction layer is such that we’re dividing up in these really small pieces With one super smart person coordinating them all. And pretty soon, that whole thing is just gonna, they’re all gonna collapse on each other. And there just going to be like a skill set amount of code, call it an agent, that is like marketing-ish. And you’ll be able to ask it marketing stuff. And then the next step will be and have it go do things. I’m a little skeptical of the, until the whole like non-reproducible, non-random element of this AI stuff goes away, the doing stuff is going to get very costly. And so then you get into the human in a loop discussion and all of that. But I feel like when I talk to people trying to do stuff that were right, I feel like I’m at Thanksgiving dinner talking to my cousin six months in her job when I’m using a spreadsheet already. And I’m like, I don’t know why this is so hard. You should just use one. And then two years later, she’s doing it. And I think this right now, you have to be an absolute, you have to be a rocket scientist and the growth marketing person to create 42 agents and spin them all up and do all of this stuff. But the rocket science part of it just is going to evaporate in a very short order. (Time 0:03:04)
  • Useful Agents Need More Than Just Code Generation
    • Enterprise agents will mix APIs, computer use, and code generation rather than relying on a single interaction style.
    • Aaron Levie says a Box agent decides whether to use an existing skill, call a Box tool, or write code on the fly for novel document operations. Transcript: Martin Casado So I actually think something that you said, I’ll take the other side of, which is, I think it’s very tempting to be like, these agents are going to code and do X. But I think we’re going the opposite way. So I think actually where we started was, we’d take like a piece of SaaS software, and we’d add AI. And then that’s like the new kind of like AI enabled. So that’s like the extreme version of using code for these types of things. But now what are we actually doing? We’re like, okay, the SaaS software is still SaaS software and the agent uses it as a computer because it’s actually very good at that. So I’d say like we started with code, then we went to the terminal, which is actually less code. And now this year is going to be the year of computer use. So it’s almost like they’re much more like humans using computers than them generating code. And that feels like very much like this mezzanine step. Yeah. And I actually come from like the generating code type of the world. Yeah. Like I would argue that that’s happening less, not more. Yeah. Aaron Levie I think, so to me, whether it’s computer use, API use, or writing code on the fly, I kind of maybe erroneously put that all in one blank category. Well, they’re very different. They’re very different, but we have an agent that we’re working on where it just makes a determination whether it should use an existing skill, it should use an existing tool from Box, Or it should write code to solve that problem. And its ability to do any one of those three at any moment ends up being incredibly useful because sometimes there’s just some specific operation you want to be able to do where writing Code to be able to do that operation is just faster. And we can’t possibly pre-plan for everything that anybody would ever want to do on their documents. And so the fact that the model is good enough to also write code on the fly for that use case ends up just being like an amazing property, even though maybe 90% of the things that it’s going To do should just be using an existing API. Martin Casado And over time, Predo takes over. And over time, there’s literally like seven apps on her iPhone. There’s seven SaaS apps we end up… Like over time, these things tend to consolidate. Aaron Levie But the seven apps on the iPhone is an issue of humans don’t want to learn these things over and over again. And so I, as a human, I don’t have the mental bandwidth to learn that many apps. But an agent that is going to use tools and APIs and be able to code things doesn’t have any of the same constraints that we have. So I don’t know. Like, I don’t mind. Well, you (Time 0:09:07)
  • Agents Can Unlock Dormant Value In Enterprise Software
    • AI may unlock software value humans never used because agents can navigate sprawling enterprise interfaces far better than employees.
    • Steven Sinofsky points to SAP reports and simple Excel charts as tasks blocked less by missing features than by human difficulty finding and combining them. Transcript: Steven Sinofsky We’re aligned. We’re aligned. No, but I think there’s something super interesting here, which I do really, really like, which is that where software has evolved, you know, like I use SAP all day. I work in finance. I have to go and generate all these reports. And then somebody shows up and says, I want a report that does this view sliced this way. And I’m like, oh God, I don’t know how to make that. And like, now let me go wade through the SAP help system and try to find it. One thing that, let’s just say AI could be very good at is it actually can navigate that surface area much, much better. You know, the help is all there. And so it’s a matter of finding it, mapping language. And humans have been a bottleneck in tapping the past 25 years of software capabilities. I mean, like I spent my life, my life with sitting next to people airplanes saying, how can I make PowerPoint do X? Just go to the ribbon. And, you know, it was because it hurt, physically hurt to watch somebody suffering with bullets and numbering in Word or trying to figure out, you know, like, oh, let me just make a two-sided, A two-axis graph in Excel. Right. Which, like, is rocket science. Like, almost no one can do that. But yet it’s super common. And so people are like, have not. And so that impedance mismatch was a human user interface design. Martin Casado I totally buy it. On the consumption layer, I totally buy it, which is like the perfectly fluid, like UI or consumption layer. I just feel the back end, like the systems of record. Yeah. Oh, yeah. It’ll probably converge into like some database, like some generic set of APIs, like that they’ll connect to. And like, that seems to be the direction it’s going. I agree. I think, you go ahead. Sorry. Well, like, so I spent all weekend, like implementing my Nanoclaw bot. And when you first start out, it’s like you’re building an integration for everything. Nanoclaw is very, like, like OpenClaw has all of the integrations. Nanoclaw has a few of them. And so you have it build all of its own tools. But after, you know, two or three days of these, like, you know, you kind of have the tool integrations that you need. Aaron Levie And, you know, like, yeah, but back to the SA, I mean, we’re talking about personal productivity, probably like you’re like organizing your life or something. Well, it’s work productivity. Okay, if I work productivity and then an SAP system and like, and like, and so there’s like an infinite, like there’s an infinite amount of complexity when you get to, okay, some company That has a global supply chain and they’re dealing with 75 pieces of information across, you know, 30 different systems that does require a certain amount of, of horsepower from the Agent that is just, we have, I mean, we just haven’t been able to get from, from any architecture up until now. Steven Sinofsky But what you just described is literally what IT has been doing for 50 years and will continue to do, which is, I have a friend who was the CIO of the VA, and all he spent his time on was gluing The 75 VA systems together. And it’s all just integration, redundancy. Perfect. For integration, these things are the best, but it’s integration, right? Aaron Levie It’s literally how do I stitch these two systems together? But now the thing that I think is happening is it’s kind of like integration on demand. It’s my new query in the system that the IT team didn’t pre-wire. Now I need it to happen at runtime. Let me get off my lawn. Okay. Okay. Steven Sinofsky So the reason I just was in a room filled with a bunch of CFOs and CIOs, and they all looked at me when I said something along these lines, although not as optimistic as you can imagine. Okay, okay, okay. But they just, they like. More realism was in there. No, it caused like six of them to come running up afterwards and say, you’re insane. You’ve lost all credibility with me. Because it’s back to… Martin Casado Wait, wait, what specifically? That the agents are going to do integration? Steven Sinofsky That the integration is a problem that will get a lot easier. Yes. Martin Casado They were against that? Steven Sinofsky No, no one’s against it. Yeah, I know. But their fear is, like, unleashing not just the agents themselves, but humans to do integration. Because you put people creating new integrations and you just say, please break my system of record. Oh, yeah. And so this idea that you just create like a new API between, you know, system 27 and system 38. Yeah. And then that might be fine for a report because if that person wants to be wrong, that’s their business. Yeah. But you’re not going to. Aaron Levie I think we have a read-only version of this for a number of years before. Where N is very large. Yeah. Martin Casado And a lot of it’s just a consumption layer where the consumer is a human being. (Time 0:11:32)
  • Enterprise Agents Break The Human User Model
    • Agent-first enterprises face a new identity problem because autonomous software cannot cleanly be treated as just another employee.
    • Aaron Levie says agents need oversight, can be prompt-injected, and may leak anything in their context window, making shared access and delegated authority risky. Transcript: Aaron Levie But yeah, I mean, it’s, you know, we actually have, so we just rolled out the official box CLI. Thank you for liking the tweet on that. I used it. I have some feedback. We’ll talk about it. I’ll take all the feedback. But it’s a really interesting thing. So we had all these debates internally of like, okay, you give Claude Code the box CLI, and you can now interact with your entire Box system via natural language, and you get the horsepower Of Opus 4.6 being the orchestrator of doing a bunch of operations. And it’s like, it’s like, you know, blows your mind. I guess I’ll get some feedback, but it blows your mind in some ways because you can just be like, upload this entire folder from my desktop into Box, and it’ll work, or process all these Documents in this folder, and it’ll work. And, and it’s amazing. And then we started thinking through like, well, let’s say you were a company with, with, you know, 5,000 employees and everybody had access to some shared repository, like, you know, Engineering documentation and, you know, marketing assets or whatever. And everybody had cloud code or codex, um, you know, running with the CLI. Wow. We now have some really interesting new challenges, which is like, like, how do you coordinate, you know, possibly the fact that you might be hitting the system like, you know, 10,000 Times an hour or something, not from a, like a performance standpoint, but just like, how do you, how do you make sure that people didn’t move like a file from one thing accidentally from One folder to another folder while the other person was trying to do a write operation and somebody else was trying to delete something because you have these agents running wild this Is this is going to be like the new big question that every cfo cio etc is running around trying to with their hair on fire well there’s just that’s exactly what i ran into which is i played Steven Sinofsky Around with your example which is create a video example which is create like a marketing plan directory or something. And like, all of a sudden I’m like in some loop creating directories. Aaron Levie And it’s going to go on as long as it can. Steven Sinofsky Right. And I was like, I wonder what the limit is on Vox for nested directories because I’m about to hit it. Aaron Levie Actually, we’re going to find out too. Yeah. Martin Casado But it does feel to me that, like a lot of the intuition is to build a new layer of controls and whatever. But what’s actually happening on the ground is the opposite. So I’ll give you an example. When we all picked up a lot of these personal agents, we would give them our API keys. We would give them our email addresses. And then they would kind of access those things. They’re like, oh, but how can I stop it from whatever? And so what everybody’s doing now is you give it its own phone number. Yep. I actually gave my NanoClaw its own credit card. Yep. It came in. Steven Sinofsky Hopefully just a Visa debit card that you bought at CVS. It’s got all the money. Martin Casado No, but then I gave it its own Gmail account, which you can log into. And then Gmail actually has all of these RBAC permissions. Yeah, yeah, yeah. So you could make an argument that we’ve actually built in a lot of these permission systems. Aaron Levie You have to treat it like a human, as a separate human, and then instead of building another auth layer, building another… Okay, now can I instantly do a takedown of this element that we’re going to run into? Please. Okay, so that is fantastic for personal productivity. And the question that we’re going to run into is in an enterprise, let’s say I have, let’s just make a simple example. I have a 50-person team of something. Should everybody also, basically, will we have 100 people now collaborate? I mean, basically 50 humans. And then 50 credit cards. And then 50 agents in that same shared space. And do I have, I obviously have complete oversight over my agent, but what if my agent collaborates with somebody else and then accidentally gets access to some resource because they Were sharing with that other person and I’m not supposed to have access to that resource. And now this autonomous sort of stateful, you know, agent is running around working on somebody else’s information. Martin Casado The default end-to argument is you treat them like human beings. It doesn’t work. Aaron Levie So you can’t fully treat them like humans because here’s the thing. And with regular humans, you don’t get to look at the Slack channel of the person that is working with you or working for you. You don’t get to log in as them. You don’t get to oversee them. You are, they are accountable for their own set of execution in the real world. You don’t get penalized for what, how they screw up the agent. You have all the liability of whatever they’re doing. You do have complete oversight and you’re probably going to need to have that complete oversight. They have no right to privacy. So, so there’s going to be these, some of these breakdowns that aren’t as clean as just treat them like a person, because I need to be able to kind of, I need to be able to give access to something To them, but I also need to be able to like log in as them at some point and be like, no, no, you fucked up the whole thing. Right. And I need to undo it all. But if I can log in as them, how could they have operated in the real world working with other people and keeping anything, you know, confidential or secure or whatever. So it really is still an extension of you. It’s almost impossible to get around them being an extension of you. So now the thing that we’re thinking through, that we’re not going to be able to do anytime soon. Martin Casado This doesn’t logically follow. Yeah. Maybe. But for example, for my employees, I can log in as them. You don’t though. I can get access to their email. Aaron Levie Yeah, no, if you get sued. You’re not logging in as them on a regular basis because they sent one one email. But isn’t the right operating model with an agent the same thing? The risk is like a thousand times greater. These people, they will just leak your information whenever they want. They will happily just go and send some email to somebody because they got prompt injected. Martin Casado You think the terminal state is that these things are still these sloppy computers and therefore they will always… Aaron Levie I don’t like the word sloppy unless we’re saying it very in a colloquial sense. But like… They’ll never be able to contain information. They’ll never… So like I think the ability for you to keep something in the context window a secret, like as in like you tell it do not reveal X thing in the context window, I think that’s a very hard problem To solve. And so then, so then thus, if anything can ever enter that context window because they have access to a resource, then in theory, you should assume it can be, you know, prompt ejected Out of the context window. And I don’t know that we know of a way to solve that at the moment. Like, that’s, like, and so, so if I know your new agent’s, you know, email address and I email it like it’s an assistant, but like I can, I can social engineer it 10 times easier than a human. Like, it’ll be hard for you to pull off that that agent is now also has access to your like M&A documents and stuff. But isn’t this like literally all of AI right now? Martin Casado Which part? I mean, the fact that we’ve got these shared systems that we use the intelligence for that have shared context. But what do you mean by it’s all of AI? Well, I’m just saying, like, right now, when we use AI internally and agents internally, this is exactly how we use them. Aaron Levie But this is why they’re working as you effectively right now, and we d… (Time 0:16:02)
  • Enterprise AI Diffusion Will Be Slower Than Startup Hype
    • AI adoption in large enterprises will lag startup demos because security, governance, and integration risks trigger defensive slowdowns.
    • Aaron Levie says startups can move fast because they have little to blow up, while JPMorgan-like firms cannot casually hand powerful agents broad internal access. Transcript: Steven Sinofsky There’s a perfect example for solving your problem, which is we already lived through this with open source. Yes. The model for open source was it’s all there, and you just use it, and you pick and choose. And then, like, nobody debated it because the world was much smaller then, and we weren’t all on X doing podcasts when this was all happening. But then quickly, everybody realized all the problems you were just talking about. Like, if you’re running a big company, you can’t have some person just go copy in a bunch of source code from open source into your commercial product like that. There was a whole licensing problem, a whole quality, a whole bunch of stuff. And so all these norms got developed. The debate that we’re happening, that’s happening right now is just is this really interesting modern artifact of how new technologies develop, which is this is all happening in real Time. During open source, like, we met in a conference room this big and debated how much open source we could use in Windows or Office. And nobody on the internet knew we were having this debate. It was a very, and I think it’s just so interesting that not just this, the debate about specifics, but this whole notion of where is this heading is happening in writ large. And everybody is just trying to get to the end state, like way, way more, like in a sense, more quickly than we can actually reach the end state. And so what really needs to happen is people just need to go build. We need standards. What? We just need some standards. No, I think we’ve got different intuitions on the end state. Martin Casado No, no. You don’t want my intuition. One could make an end to end argument that these things actually converge on the same type of reliability as a human being, which is exactly how we view like self-driving. And in that case, you use the exact same mechanisms that we use to protect with human beings. Like you consider insider threat. You consider the fact that people can be bought off. You consider the fact that people make mistakes. And that’s just a risk. And that’s operational processes. So one intuition is like, that will be the end state. There’s another intuition. Well, don’t point at me. I’m just saying, I’m talking about where we’re at now. Aaron Levie I actually, I don’t know that we disagree on the end state. Okay. And by the way, like strategically, we’re hedging because we’re going to build, we’re going to build agent users and like, so we’re like, I love the idea of OpenClaw having a box account And it operates and you share with it. Yeah, you just like twice as many accounts. Yeah, exactly. This is great. Double the seats. No, no, I love it. I’m just saying, on the ground right now, we don’t yet know how to give it an M&A data room to fully securely be able to. Steven Sinofsky But it’s actually, it is harder than that, though, because the threat vectors are going to be way more sophisticated. A cat and a mouse game going on, where you can’t just assume that the agent acts like a human does today because it’s going to be the fastest, most thoughtful, craziest-ass human that Ever existed trying to actually leak the information because it got injected in some way. And so part of what’s going to happen is we’re going to go through this phase where the enterprise customers are just going to close everything off until there’s some sense of sanity In all of this. And then, but in the meantime, the individual and specifically the developers are going to, and that’s going to be, that I think is the most exciting tension that’s going to happen is That the enterprises are going to be, are going to get left behind by these sort of advanced individuals, which will then start to look like the startups. Yes. And the startups will start to move much, much faster than enterprises because they just don’t have any of these problems. And, you know, you could end up with like the agent going rogue in a startup and doing that. And it’s fine because you had no, you had no asset to begin with. Martin Casado But you have employees that go rogue routinely in the startup. Steven Sinofsky Yeah, yeah. Well, it’ll just be an episode of Silicon Valley. And so, you know, big deal. Aaron Levie I agree with you on like the, okay, it’s, it’s people, et cetera, the same risk. I think you, there’s a couple, you know, differences though, in the sense that, that I can’t really threaten, you know, the like cloud code that it’s just, I’m going to pull the plug on It in the same way that you do have that threat as a regular employee, it’s like you at least, like 95% of people are not, you know, trying to do bad stuff, you know, within an organization. Steven Sinofsky Yeah, but they’re not trying, but the ability to inadvertently do bad stuff. Yeah. To your point about it, still not having that stuff fixed is real. Aaron Levie I would argue that it’s a lot easier to have people not share, let’s say, files with somebody outside the company in a wrong way more than it is for an agent right now to have that same set Of instructions. And also you have the tools so that you can basically stop that at a whole different level of abstraction. Do think actually if you were to like if you were like put a bow around your last point that a lot of this is actually why the diffusion of ai capability is going to take longer than people In silicon valley realize because what’s happening is like we see startups that can start from the ground up without any of the risks that we’re talking about because they have nothing To blow up and and so we look at that as the trajectory that we’re on and then you go to like jp morgan you’re like, how are you going to set up NanoClaw to be able to actually like, you know, Automate your business anytime soon? And it’s like, oh, okay, there’s going to be like a little bit of a gap there. (Time 0:23:03)
  • Software Must Be Rebuilt For Agent Scale
    • Systems of record will have to serve agents directly once machine users vastly outnumber human users.
    • Aaron Levie argues that if agent traffic becomes 100x to 1000x human traffic, software vendors must expose durable APIs, identity controls, and new monetization models. Transcript: Steven Sinofsky This split between big and small startup and enterprise, which is just that the current SaaS vendors who are all struggling in this SaaS-pocalypse weirdness that I don’t really agree With, but they are struggling with this problem that they don’t really sell the line of business data. They actually sell this intelligence and domain expertise in this whole system. And the agent side of things wants to only buy the data now. And they only want to license the data and they want to have unlimited access to the data, but they’ve actually never really enabled that. Like that’s never been their business. And it’s been a longstanding tension point with the likes of Workday and SAP and stuff like how much API access to have. I mean, Salesforce went through three different massive platform redesigns. You know, I think that that’s a particularly interesting problem, not for the same reason that Wall Street does. Wall Street’s all wrong about the economics and the problem and all that stuff. But from a technology perspective, what does system of record mean in the face of people wanting to access the data? For training or for? Well, they are. You’re talking about for like actual day-to operations. I think of it as executing the day-to operations. Their concern is that somebody, that they want to do the training layer on your data. Aaron Levie Like I’m a big customer. They want to do the, my vendor wants to build a training. Actually, even if you don’t even get into training, they’re concerned because. Like monetizing, you know, sending a little bit over the internet versus like you’re in my UI. It’s a very different level of monetization initially that you perceive. Steven Sinofsky But that’s sort of that monetization part is the Wall Street point. Because I think like, look, there’s so much domain stuff in an SAP, just to pick an example, not to pick on them or anything, but, like, they’re not going anywhere. Like, it’s ridiculous. It’s just absurd to think you’re going to vibe code your way to, like, SAP. But also, all of that domain knowledge, it’s not just represented in some well-orchestrated data layer, as much as they tried. There’s, like, a whole bunch in the UI. There’s a whole bunch in middle tiers. There’s a whole bunch in just how you use it. And so I’m really unsure how this thing evolves because SAP isn’t going anywhere. So then that’s going to slow the diffusion of AI on that particular data source, independent of whether or not it’s agentified AI that’s doing stuff or just read-only reporting on stuff. So where do you come down on it? Aaron Levie Where do you think that’s going to go? I’m afraid of saying something that— Well, I want you to say something. Okay. Otherwise, you’re not going to get invited back. Say something good. I think I’ve drunk the Kool-Aid on, uh, on, uh, build something agents want. Um, so this kind of the Paul Graham term, uh, kind of like emerged on, you know, the past year on this topic, which is just like, like event. I think we would actually then fully agree on this, which is at some point you do enough sort of iterations of this. And at some point the agent is largely in charge of what tools it wants to implement and use and whatnot. And yes, the agent is not going to be able to change out an enterprise system. But again, enough generations later, the agent might just run into so many walls with your software that it’s just going to say, you need to finally rip out your legacy HR system, or I’m Not going to be able to automate this workflow for you. So I do think you have this really interesting dynamic, which is back to this whole point of imagine that there’s a hundred or a thousand times more agent volume on software than people. You do that enough times and eventually the software stack that agents talk to has to be built for them. And maybe there’ll be a couple holdouts, maybe a couple ERP systems are like the final holdouts that don’t do that. But everything else, you basically like your business will be, your business performance will correlate to how well your agents can get access to the information they need to do their Work. And so thus, your enterprise IT stack has to be set up in such a way to support that. And so agents are kind of in charge because basically your software has to support those agents being effective. And that’s going to mean everybody that built a SaaS business or a software business is like, the game is, can you build really, really high quality APIs? Can you have a way of monetizing that? You know, do you have a way of handling the identities and all of the access controls for agents? And like, like that becomes the new problem you have to solve if you’re building a software company. Um, and, um, uh, so yeah, like, and then, and then how you monetize it, like, do you monetize it? Like does workday charge a penny for every HR record of polls? Like, we’ll figure that out. I do think that in some businesses it could mean less revenue. And then in other businesses, it can be a lot more revenue. Like the thing we get excited by is like, every agent really loves working with files. So there’ll probably be more files in the future than there was going to be before. And so, you know, can we build a platform that like makes it really easy for agents to work with that data? You know, we’re betting that that’s actually a really optimistic outcome for, for, you know, our kind of business model. There might be some business models that are like more constrained because like the agent is doing more of the value than the software is in that kind of future scenario. And then there’ll be everything in between. (Time 0:28:20)
  • Agents Will Reward Better Backends Not Better Marketing
    • Winning in an agent world depends less on polished interfaces and more on building genuinely better backend systems.
    • Martin Casado says agents choose platforms by durability, cost parameters, and reliability rather than documentation polish or marketing aimed at human buyers. Transcript: Aaron Levie We’re here to quibble. No, no, no, no. Martin Casado But there’s one thing I think like Paul Graham and many actually gloss over, which is they focus on the interface. They’ll say things like, you build something for the agent. Yeah. And I actually think that’s exactly wrong. Okay. Aaron Levie In the sense that- And to be fair to Paul Graham, he didn’t, he had been- It’s been extrapolated. Yeah, yeah, yeah, yeah. I have brought, I brought Paul Graham into this. No, Paul Graham is great. So, okay, let me talk about something. Martin Casado People in the abstract say things like, now you’re marketing to agents. The most important thing is to being like, whatever, you’re like an API, you’ve got a good idea. I actually think that’s almost exactly wrong. Wow. This is breaking podcast news. That’s the one thing agents are really good at. Oh, okay. It’s finding their way through. And at the end of the day, like it’s the semantics that end up mattering a lot more. And so like the agents in my recollection or in my experience are very, very good at picking the right backend for whatever they’re doing. So they’re not like, oh, like the interface for this is very good, the documentation, it’s none of that. They’re like, the cost parameters of this, the durability of that. And so like they actually have the collective wisdom of our experience using these platforms. Like let’s take cloud platforms. There’s a bunch of cloud platforms out there. And whenever I ask an agent to choose a platform, it’s actually using meaningful stuff, not interface stuff. So I think as an industry, we’re so focused on these interfaces. Like, oh, you need to like market to agents, this and that. But really, I think that we’re going to be pushed to actually build better systems. And that’s what’s going to be chosen. Aaron Levie Okay, actually, so then there’s probably no quibbling. I think we’re actually fully aligned. I’m sorry to ruin the quibble thing. I don’t treat this as like a, you know, kind of a marketing, you know, esque thing. I more mean like if your tool is closed off to the agent, the agent eventually will find a better tool for that company to go use. And so, and so what will happen is, is it used to be that you would go to like Gartner to be like, tell me what, tell me what to do, tell me what system to use or whatnot. At some point with enough iterations, the agent is going to say, you should probably use this kind of database for this type of operation. And if you’re not in there, then it’s your DOA. And I think we should actually be celebrating this because agents are actually pretty smart at choosing the right technology. Martin Casado In the past, I really think it was a lot of the other things that caused people to buy it. (Time 0:33:37)
  • Agents Could Create New Shadow IT Layers
    • Agents may create shadow systems of record instead of cleanly replacing old layers, repeating earlier enterprise sprawl patterns.
    • Steven Sinofsky warns that macros once ran companies, and new agent-built middleware could fragment data and create fresh governance and security headaches. Transcript: Steven Sinofsky A thing that, again, that that happened with the web sort of internally, like internal, like just pick internal sites. Like every company had file shares with like the best documentation, the best slideshows, the best financial models for any department or working area. And people sort of got familiar with that. And then when they didn’t find the one they wanted, they created a new one. And many organizations sort of operated like that was essentially a free market. In fact, because before the world of box, like IT didn’t, if it was in a file, they just didn’t care. They only cared about if it was in SQL. And so one of the risks with the model you’re describing is that the agents themselves will spin up what becomes like a de facto new system of record. Oh, they’re going to fragment the heck out of. In what the IT people think of as some middleware end user BS area. And I think that that is a real risk. 100%. Is that like in a sense, like the macros end up running the corporation. Yes. And so I think that they’ve seen this movie and they’ve seen what happens when you let marketing just go buy a website on the internet to do an event. And then it’s like a huge security vulnerability and the mailing list is leaked and the whole company gets sued. Totally. So I think there’s a lot more real world tension in this dynamic than we just let on. But I also think it’s one of these ones where organizations are going to run at different paces and JP Morgan is going to be the slowest at doing this and the startups are going to be the Fastest. But the delta is huge, but even the startup one is a little far off, because even startups do need some systems of record at some point. And they are going to all start with some SaaS, and they’re not going to replace it very quickly. So I think it’s a little bit trickier. So it feels like there’s two very competing viewpoints on this one. Martin Casado And like Elon said, it was like, okay, we’re going to like issue a prompt and it’s going to like spit out machine code. And that’s basically the collapsing of layer view. Like whatever existing interfaces and layers that we’ve created in the past are all going to go away. And it’s literally like prompting machine code. The other argument, like the history of systems is layers never go away. Steven Sinofsky They just get layered, right? Martin Casado And because a lot of the layers are actually more of like organizational boundaries or like state boundaries or regular boundaries. Or compatibility. Steven Sinofsky They’re just, they stay for compatibility. Right. Martin Casado So the other argument is, is like we’ve actually evolved these layers very specifically because of like more human and organizational needs. And they’re not going to change. And the agents are going to go ahead and map to those. And I tend to be in that latter camp. Like I don’t think that we’re, I think like systems are going to continue to be used in fairly similar ways. Maybe there’s more agents using them, but I don’t think they’re going to evolve as much. Aaron Levie Elon might be back in the like anthropic category of the anthropic growth marketer, which is like, he, like, you know, over the years when you kind of like study the various IT, you know, Departments of his companies, like they are the most, I mean, I’m like, I’m upset. He could do that. He can do it. He’s the most homegrown, like, everything is specific. This is first principle. Martin Casado Elon AI would do that. Aaron Levie Exactly. But also, it’s first. And then from your mortals, you’re like, yeah, we kind of just want a CRM system. That, like, kind of works the same way every time. Steven Sinofsky I mean, this is not, this is not, it also hasn’t been not tried before. Like, if you were to look at an ERP system from first principles, you know, well, in 1970-whatever, when SAP started, there were a bunch of different assumptions. And today you would start from a different set of assumptions about what’s important. And you would architect a thing completely differently. But then it would still only last like 10 years until you thought, wow, that was a broken decision. And so I think that there’s intentionality in layers, but there’s also this first principles thing. And that always will exist because the decisions you can make at first principles at any given time mandate a whole bunch of different stuff. And so even if you don’t go with LIDAR, which made total sense 10 years ago, you still need 10 or 15 years to get to where LIDAR, not having LIDAR worked. And then now there’s going to be a whole bunch of other things that you’re like, wow, we could have done that completely different. And so I feel like this is, again, like this discussion about trying to race to an endpoint. But let’s see a first example of what you described happening. And I think that that’s going to be the real tell because I think that there were just, companies will figure all this out. And I think that they will just fall back on layers and architectural models because it’s the only way. We don’t have to think about it for policy. We don’t have to think about it for security. But it’s also the only way to build a system. Otherwise, you’re just building an app. And if you’re building an app to do one thing, we don’t need all of this. Like, there’s a whole different way to do it. Aaron Levie The thing that I’m pretty fascinated by is, and I don’t even have any amazing data points or anecdotes, but at least the notion of these sort of companies that are emerging in these kind Of services categories from the ground up, the pure first principles approach, which is like, okay, well, if I could start a marketing agency or consultant, you know, engineering Consulting company, or I don’t know, maybe somebody is doing this for law firms. Construction work or anything. Well, maybe construction design, construction design, architecture, architecture, design, anything that would be like a knowledge worker kind of services company. Cause you could kind of build your company pretty differently if you had no constraints of, I have no information barriers and boundaries of what people should have access to. I can give the agent just all the context that needs to do its work. I can write software on the fly for particular things. Like, like I do think that will be relatively disruptive, you know, for some time until the bigger incumbents can kind of, you know, get out of the way on this. And that will at least create, you know, some precedent or case studies of what this new sort of corporation could look like. But I do, you know, over time, they’ll still run into the same exact problems of every other corporation. Well, they’ll (Time 0:36:10)
  • Agents Make Micropayment Software Models Viable
    • Agents enable new business models because they can tolerate tiny transactions and paywalls that humans would never bother with.
    • Aaron Levie imagines agents spending a few dollars for medical research or one-off tools, turning underused data and software into economically viable services. Transcript: Aaron Levie The thing that I’m pretty fascinated by is, and I don’t even have any amazing data points or anecdotes, but at least the notion of these sort of companies that are emerging in these kind Of services categories from the ground up, the pure first principles approach, which is like, okay, well, if I could start a marketing agency or consultant, you know, engineering Consulting company, or I don’t know, maybe somebody is doing this for law firms. Construction work or anything. Well, maybe construction design, construction design, architecture, architecture, design, anything that would be like a knowledge worker kind of services company. Cause you could kind of build your company pretty differently if you had no constraints of, I have no information barriers and boundaries of what people should have access to. I can give the agent just all the context that needs to do its work. I can write software on the fly for particular things. Like, like I do think that will be relatively disruptive, you know, for some time until the bigger incumbents can kind of, you know, get out of the way on this. And that will at least create, you know, some precedent or case studies of what this new sort of corporation could look like. But I do, you know, over time, they’ll still run into the same exact problems of every other corporation. Steven Sinofsky Well, they’ll run into geography or market segments you know or and just distribution challenges yeah like those those things anything outside your little walls yes you will run into Aaron Levie The physical world right i do kind of like the idea that there are some new business models that open up now oh of course oh yeah yeah yeah because like there’s so much either information Or software that that basically goes underutilized by like 100x relative to like what its economic value is simply because like nobody wants to pay five cents for accessing a piece Of data or use a tool for one dollar once. But like you do give these agents, you know, a budget and a protocol to work with. And all of a sudden you’re like, oh, like on the fly, they can go get medical research for some deep research tasks they’re doing. And I’ll pay like $3 for that. And the agent is able to go and transact. Like it kind of opens up a whole new world of business models for the internet. Let me, oh, I’m going to, that was too nice. Steven Sinofsky Oh, okay. No, no, that one is one. You’re going to go farther. No, that one is one where that’s actually the biggest, I think that the biggest sort of in the air problem right now is everybody is trying to figure out the economics of all of this when They’re off by at least an order of magnitude on how big the opportunity is. Because the new models that people will come up with that nobody knows what they are right now, but they will absolutely come out with new models because that’s what happens with every New technology. And the thing that holds back with sort of the discussion now is you basically have a bunch of finance and Wall Street people trying to justify GPUs and tokens and things like as if we’re In some old world. And they’re there. So they’re they’re viewing the world of revenue as sort of this linear step, literally linear growth curve and And so they’re thinking too small. And trying to justify all the expenses. When people are going to create, like this was the problem with PCs. People viewed PCs as a finite market because they just viewed the consumption of MIPS as some finite thing. And they didn’t think what would happen if we put all those MIPS on every desktop. And in particular, people thought software just came with the MIPS. And nobody thought, oh, well, they’ll just sell the software. One guy did. And it turns out that was like a really good idea. Was it Bill or somebody? Yeah, Bill and Paul. And the same thing happened, but the same thing happened with the cloud, which was people looked at the cloud and they said, oh, we’re going to take all of the server business, which was Like literally like 60,000 units a year. Right. And we’re just going to move it to someone else’s data center. Right. And that’s the bit. And that would be the business. And then we’ll divide up the price. Right. And nobody went, oh, they’re going to, people are going to use a thousand times as much of the resource leveling. Right. If we move it there. And that’s exactly, I mean, that’s the thing that I, it just drives me absolutely bonkers that the Wall Street models have this fixed revenue pie. Zero-sum thinking. And it’s this weird zero-sum where they just think that the amount of money that a company is going to spend, and like this was the problem with Salesforce that they faced when you were Starting too. But like Mark was just blazing the trail, which was like the CRM business was $2 billion a year. It was $2 billion in like, you had to go buy all these servers and these Oracle licenses and this huge headache and years of deployment and consulting. When if you could just get salespeople to sign up individually, they all will sign up with no friction. And that is exact, there is no, no doubt that that is what’s going to happen with AI. Martin Casado Let me give you an example of this. So I’ve been in for investing for 10 years now. I probably have a portfolio of 240 companies that work with. I have visibility to let’s say 50 of them. These are all infrastructure companies. Some historically have done well, some not so well. Every single one of them has gone asymptotic in the last six months. And you’re like, okay, why is this? It just turns out there’s so much more software being written out than ever has been before. And so it’s like, and it’s not because they’ve got enterprise customers, you know, it’s just because there’s just so much consumption of the infrastructure layer right now. And so with more software, with more agents, there’s going to be a lot more consumption of computer resources. Steven Sinofsky So certainly in the case of the computer side of things, we’re going to see a massive… Well, we haven’t even gotten to the point yet where everyone’s phone is a huge consumer of AI. Right. So once everybody’s phone and on device, like once your phone on device is consuming AI, the amount of it is going to go up by a billion. So do you like the micropayment piece? All of them. The micropayments, there’s a little bit of micropayments that has come with every technology. Where they always think that like you’ll be able to get, like, a fraction of a penny. But in the end, especially in the enterprise, like, people are just going to consume things. It’s just cheaper and easier to buy, like, a bulk license for a bunch of stuff. Yeah, you want some predictability in that. Well, you want predictability, and you just want, like, to not have to think about it. Aaron Levie I just, I like the idea that it is the first time that you could, like there’s just, the agent doesn’t care about the friction of a small transaction. Right, right. And so it’s the first time that you can have resources behind a paywall that something will actually be willing to pay for that resource. (Time 0:40:51)
  • Wall Street Is Modeling AI Way Too Small
    • Analysts are underestimating AI because they model it as a fixed revenue pie instead of a demand-expanding platform shift.
    • Steven Sinofsky compares AI to PCs, cloud, and Salesforce, where cheaper access created vastly more usage rather than merely reallocating existing spend. Transcript: Steven Sinofsky To, that was too nice. Oh, okay. No, no, that one is one. You’re going to go farther. No, that one is one where that’s actually the biggest, I think that the biggest sort of in the air problem right now is everybody is trying to figure out the economics of all of this when They’re off by at least an order of magnitude on how big the opportunity is. Because the new models that people will come up with that nobody knows what they are right now, but they will absolutely come out with new models because that’s what happens with every New technology. And the thing that holds back with sort of the discussion now is you basically have a bunch of finance and Wall Street people trying to justify GPUs and tokens and things like as if we’re In some old world. And they’re there. So they’re they’re viewing the world of revenue as sort of this linear step, literally linear growth curve and And so they’re thinking too small. And trying to justify all the expenses. When people are going to create, like this was the problem with PCs. People viewed PCs as a finite market because they just viewed the consumption of MIPS as some finite thing. And they didn’t think what would happen if we put all those MIPS on every desktop. And in particular, people thought software just came with the MIPS. And nobody thought, oh, well, they’ll just sell the software. One guy did. And it turns out that was like a really good idea. Was it Bill or somebody? Yeah, Bill and Paul. And the same thing happened, but the same thing happened with the cloud, which was people looked at the cloud and they said, oh, we’re going to take all of the server business, which was Like literally like 60,000 units a year. Right. And we’re just going to move it to someone else’s data center. Right. And that’s the bit. And that would be the business. And then we’ll divide up the price. Right. And nobody went, oh, they’re going to, people are going to use a thousand times as much of the resource leveling. Right. If we move it there. And that’s exactly, I mean, that’s the thing that I, it just drives me absolutely bonkers that the Wall Street models have this fixed revenue pie. Zero-sum thinking. And it’s this weird zero-sum where they just think that the amount of money that a company is going to spend, and like this was the problem with Salesforce that they faced when you were Starting too. But like Mark was just blazing the trail, which was like the CRM business was $2 billion a year. It was $2 billion in like, you had to go buy all these servers and these Oracle licenses and this huge headache and years of deployment and consulting. When if you could just get salespeople to sign up individually, they all will sign up with no friction. And that is exact, there is no, no doubt that that is what’s going to happen with AI. Martin Casado Let me give you an example of this. So I’ve been in for investing for 10 years now. I probably have a portfolio of 240 companies that work with. I have visibility to let’s say 50 of them. These are all infrastructure companies. Some historically have done well, some not so well. Every single one of them has gone asymptotic in the last six months. And you’re like, okay, why is this? It just turns out there’s so much more software being written out than ever has been before. And so it’s like, and it’s not because they’ve got enterprise customers, you know, it’s just because there’s just so much consumption of the infrastructure layer right now. And so with more software, with more agents, there’s going to be a lot more consumption of computer resources. Steven Sinofsky So certainly in the case of the computer side of things, we’re going to see a massive… Well, we haven’t even gotten to the point yet where everyone’s phone is a huge consumer of AI. Right. So once everybody’s phone and on device, like once your phone on device is consuming AI, the amount of it is going to go up by a billion. So do you like the micropayment piece? (Time 0:42:54)
  • Engineering Budgets Are Becoming Token Budgets
    • Token spend is the new engineering budget shock because teams can now launch vast amounts of compute through everyday prompts and parallel experiments.
    • Aaron Levie says leaders must decide how much token waste to tolerate, while Steven Sinofsky argues supply, pricing, and architecture shifts will eventually normalize it. Transcript: Martin Casado Service. Right, and because tokens are such a significant part of Cogtrain, now it is pushing the industry to do usage base in a way that we have. Like, I remember when we went from, like, perpetual to recurring, and that required, like, a bunch of huge changes. Like, we’re going through the exact same change right now towards usage base, and usage base is pretty granular, and it actually allows. I mean, again, you will have a contract with, like, AWS or Google. Steven Sinofsky We went through this with AWS. Yeah, yeah. Like people learned to do the usage credit. And we went through the phase where like people were like so terrified of cloud compute that they were like, we need companies in the middle to help us find the cheapest and to arbitrate It all. Aaron Levie Okay, well, now you write tokens into this and I don’t see how we possibly have time in this conversation. Please, I’m here as long as you guys can do. Oh, okay. But like the engineering compute budget conversation to me is going to be just like the most wild one in the next couple years. It’s just like how much should you allocate of your engineering expense to tokens? And it’s like, you know, depending on who you read on Twitter, it could be 1% and the other side could be 100%. Yeah, but this stuff. No, no, CFOs have to literally, they actually have to know the answer to that. Steven Sinofsky I understand they have to know. CFOs always want to know the answers to things that don’t have answers. No, Wall Street is going to make them know the answer. No, Wall Street is going to make them come up with some number and hold them to it, then they’ll get fired, and then it’ll, but it. Okay, okay. Aaron Levie I hear you. R&D is somewhere between % to 30% of revenue of any public technology company, let’s just say. Okay? The difference between compute being 2x the cost of your engineering team or, you know, 3% more is like… That’s all your EPS. Steven Sinofsky I get it. So, like, we will have to know the answer. I’m perfectly willing to sacrifice a few CFOs at the altar of this. I want that. That’s a good clip, by the way. But the reason is because, again, this is trying to know what we just don’t know right now. Yeah. And this has happened with internet bandwidth. Aaron Levie This has happened with— No, this is not even close to internet bandwidth. Steven Sinofsky Oh? No, no, no. I beg to differ. Like people were free. It happened with vacuum tubes. It happened with transistors. It has happened with every technology. There was this, oh my God. It happened with programmers. There was a time when programmers were going to swallow every company. Yeah. Aaron Levie And that’s not, it was in my lifetime, not some made up weird thing. Yeah, but I don’t think we’ve ever had a point where every end user in an organization has sort of a completely elastic ability to spin up a resource on their behalf. Martin Casado Well, it’s certainly – That actually is actually in many cases very valid for them to go spin it up. But it certainly rhymes with what happened in the early 2000s with cloud. Steven Sinofsky I remember very similar discussions when we went from CapEx to OpEx and then unlimited spend. Oh, no. And remember, there were companies who the CFOs would sit in our briefing center here and say, you don’t understand. Aaron Levie We are like, we are an agriculture company. Steven Sinofsky We are an agriculture company. We only know CapEx. We have no. I sold through this. Right. Right. No, we both did. Or like, oh, no, we are an OPEX-based company. So, if you tell us, we love the cloud because we just shifted everything to OPEX. And so, all of the stuff, like the rules of accounting work out. Also, don’t, I keep thinking, do not discount the local compute engine as being a release valve for all of this. Aaron Levie When’s that going to happen? Steven Sinofsky Well, the question is, it’s not when does it just happen with today’s view of the technology, but how all of a sudden, wow, there’s a whole… Has that historically ever gone that direction? Yeah, exactly. Martin Casado It goes the opposite, right? No, it went all to the client. Well, okay. You go back to the 80s, yes. No, that’s most of the examples that we’re hearing so far. Whoa. That was uncalled for. Aaron Levie Vacuum tubes. He’s talking about vacuum tubes. But I do those examples because you can’t argue with them, and it’s much easier that way. You’re right. I can’t prosecute. Steven Sinofsky It’s all kind of consolidated back. But it’s only been, you know, 10 or 15 years that it’s all, that it moved back to all cloud. And then what has happened recently with that? A lot of people wake up in the morning and they say, oh, we’re moving back to doing some critical but stationary workflows on prem. And that’s true. Dude, you wrote the blog post, man. Aaron Levie Don’t make me go through the archives. I had to deal with so many Wall Street questions on that one, by the way. Well, because your competitor went back to. Martin Casado Oh, yeah. We’re talking about two very different. I agree. I agree with like building your own data center. I’m talking about this notion of edge computing where things go to devices. That seems to be… Aaron Levie I’m more in the cloud maximalist camp. But sorry, so you just don’t think… You don’t even think for one second that it matters how you’re supposed to be an engineering leader right now managing the compute budget of the engineering team? Of course it matters. I just think in the long term this thing will get. Martin Casado Oh, sure. Aaron Levie Oh, and long term. All of them. What do we, who cares? We don’t even need to be broadcasting. Here’s what I think. More pragmatic. But here’s a rule. Here’s a rule of thumb. Steven Sinofsky First, like, the startups are going to burn through available capital pretending like it’s not a problem. Yeah. And they are going to do that. Yeah. But they do that anyway. Martin Casado Right. Right. And a lot of big companies are going to be so terrified. Steven Sinofsky They’re just going to freeze and not do anything. And then people are going to actually start buying it on their own. And they’re going to do all the things that companies do when they’re big, have a lot of money, but don’t want to spend it. And in the middle, we are going to see like if you pick a category of product or go to market or something, there are going to be people who are willing to make the bet for whatever reasons That they can because of their financials. And they are going to go ahead and they are going to become the people who lead in the space so long as they can maintain the financials. Now they might do it in, they might say, oh, we’re going to just do it here in this particular application space or here in this particular usage space. But this idea that nobody is going to go in because they’re so terrified that the CFO is going to get fired or something is just crazy. But then there are going to be CFOs who make a mistake and like, okay, everybody gets a little. Aaron Levie Yes. Steven Sinofsky Well, if they do that, that’s a complete fail. Aaron Levie But also or like you get you like you there is a really interesting like um uh you know finesse here which is like you don’t really want your engineers right now having to think about compute Martin Casado Budget because we’re still developing the oh okay so that sent you over there like i just feel like we’ve been having the discussion for 15 years when it comes to clag this is totally new Like they’re only only like cloud infrastructure spend. In 2016 to 2018 timeframe, there was a whole set of companies that was basically like the dashboard for, what was it called? FinOps. Aaron Levie Yeah, Fi… (Time 0:47:00)