The Exchanges

Q you've mentioned that, like, you get a groundswell of support to use AI from, let's say, C-suite and people on the ground, but then you go to, let's say, legal or finance, and they won't allow it to go forward. They're terrified. Is this part of it? Is it, is it, is it because you just kind of give up control, or what exactly is holding up? The rollout here.

A I think it, I mean, fear. Almost always. Okay. Yes. Um, and the, the fears are, Will my proprietary data, like we were talking about earlier, ends up, end up in the hands of, of these model providers? Will that be used to train models, uh, in the, the future? Um, you know, what if I, I'm using, you know, AI operationally as a site reliability engineer, or as a SecOps engineer, what if it makes the wrong changes, just like I just mentioned? You know, what, what ha, how do I control operationally? You know, what's, what's going on? Uh, so many, many fears, and more than that, the things that move slower are things like procurement, legal, right? Like the, so when we go sign an agreement, we have AI terms in there, and then, then they come back with red lines, right? Like, okay, nope, nope. For, for me, if you want to sell to my organization, these are the terms that, that you must accept, or you can have no AI terms in there. So you'll literally have, you know, a chief information security officer on a podcast talking about what they're doing to protect themselves against mythos, and I can tell you that I'm selling to them right now, and you're telling me you won't use any of my AI technology, which will help you defend yourself against the, these sort of things. It's getting better, and that's a temporary, I mean, in five years we'll have forgotten that, that this was, this was …

AI assessment note: “I think it, I mean, fear. Almost always. Okay. Yes.”

Q of AI model leaves exhaust, uh, and then the AI model companies can come build competing products. Um, I just want to ask you, like, how true is that? Uh, how, like, is this data actually valuable enough for an anthropic or an open AI to see people using their models in certain ways, and then being able to go out and basically go up market and build another product?

A So my co-founder likes to say the value of this data is essentially zero until suddenly it is not. Um, and so, yeah, it's a lot of, like, individually looking at one user's trace is essentially worthless, unless I have some security problem I need to go urgently look at it, but normally it's worth nothing. But in aggregate, it's incredibly valuable, because the being able, and it's also valuable It slices different ways, right? So there is value in saying, okay, hey, watching every developer, what questions they ask, what code gets generated, whether that code is good or bad, will allow me to reinforcement learning, ah, on the, on these models to make them better for everyone. Then there's also, okay, well, there's also organizational specific value, which is the, the model, you know, working inside of an organization. Uh, we believe we will be doing reinforcement learning for specific organizations to tune the models to their specific, uh, environments. Um, and so the, uh, and there's also, uh, there's also value from a security perspective as well. Both individually and in aggregate, understanding what is good and what is bad. So it's valuable, but it's also incredibly expensive. This, this data is emitted at very, very high velocity and very large volumes, and so, you know, we're having to build new technologies for how to process this cost effectively so that we can actuall…

AI assessment note: “individually looking at one user's trace is essentially worthless... But in aggregate, it's incredibly valuable”

Q couple months ago that, like, only five to ten million people use agents, um, but I'm curious to hear your perspective on, like, are you seeing it now in terms of the increase in the amount of data that's being generated, and where do you expect this to go as, you know, these agents aren't used by, like, five or 10 or fifteen million people, but by a billion people?

A Yeah, so I believe it's felt, but I don't think we can measure it yet. So the, the general growth of data as measured by IDC is about a 30% compound growth rate. And that, that's been, that's gone up from, let's call it 25, 27% over the last couple of years. But the, to your point, agents are only in the hands of a handful of people today. Um, It's not only in the data that's output by, by using the agents themselves, it is also the other exhaust as the agents move at machine speed as opposed to human speed. So, if I now have agents that can work 10, 20, 50 times faster than humans, all the things that they are replicating that humans used to do, Now also amplifies. So if that agent is browsing a website and I used to have, you know, let's say I'm an enterprise and I used to have 10,000 internal users of this application, but now I have agents which are, you know, exploring multiple hypotheses and now start to look like 30,000 or 50,000 users. Well, now I just had an increase of a factor of three or five on all of this other exhaust and all my other systems that, that are, uh, emitting this, this data. That being said, it's still too early to be able to point to like an industry example of like, well, we know it's going to be blah. So logically, we're feeling it. We know it's happening. Uh, you can kind of get some samples and some observations of AI native organizations genera…

AI assessment note: “I believe it's felt, but I don't think we can measure it yet.”

Q for, um, but I, we've been talking about this on the show recently about, like, what these models might use the exhaust of our interactions, um, with their products, uh, for whether that's disintermediating our own products or building new things that we don't get a cut in. Um, as someone who works in this day to day, how right is Satya Nadella in picking this out as a problem?

A Well, I mean, it's particularly a concern for me because, you know, I, I, I have a near 100% belief that the, that these companies will eventually want to compete with my business. Uh, and so, you know, I need them. I need their models. I need the intelligence that they're selling, but I'm, I have some very real concerns that, you know, within the next six, 1218 months, uh, they're going to have Telemetry products, security products that are going to be directly competitive, uh, with mine, and I think most of the enterprises I'm talking to have similar concerns, like the, you know, they're starting to build, you know, large forward deployed, uh, engineer forces that are, you know, presumably out to help these enterprises build great applications, but, uh, also are they helping their competitors with all of that knowledge that they are, that they are accumulating, but that is exactly the type of data that we, that we deal with, and One of the interesting sort of, uh, things that happened over the last couple months is a lot of my customers are now asking for AI observability. They want to look at this trace data. They want to know, what's this costing me? They want to know, uh, what tool calls are these agents making? And that from a security perspective, like, I need, like, rich auditability about these autonomous intelligences going out and, and doing things on, on my behalf. …

AI assessment note: “I have a near 100% belief that the, that these companies will eventually want to compete”

Q know, one of the things that I've sort of, you know, brought up here is if, you know, the capabilities seem real enough, um, that I, I wonder exactly like, you know, do you, do you just release them to everybody or where do you draw the line and how much of this mythos situation do you think was, um, sort of irrational, uh, hype versus based in some reality?

A Well, I mean, there's all kinds of rumors swirling, like the, really, it was, it was marketing hype, because they didn't have the compute, and so they didn't want to look like they were falling behind, they couldn't release it, or otherwise, uh, people would have gotten a bad experience, and then as soon as they got the SpaceX compute, you know, you know, magically, you know, it was out. I don't know, I mean, like the, I mean, it's fun, it's fun to speculate on that sort of thing, but I, I, you know, who, who's to say whether any of that, that, that is true. Um, I think that creating a, a have and have not system whereby which Anthropic or the US government anoints which organizations can be secure, and then everybody else is not, ah, does not feel right to me. That, that does not seem to be, ah, On the other hand, I mean, I think there, as with all security related things, like responsible disclosure is a thing. Like we should definitely privately tell people about things so that we can patch them and, and make sure that we minimize the number of zero days in the world. So I think it's a very difficult situation, and I don't know that I, you know, unilaterally have, uh, all of the, the, the right answers. Um, I think it's certainly, it's certainly within the US government's right to ask That they get early access, and we have a very large federal business, and, and I, uh, I sp…

AI assessment note: “creating a have and have not system whereby which Anthropic or the US government anoints”

Q Is it going to be worth it in the end, Clint? I mean, costs seem to be escalating everywhere to enable this AI moment.

A Well, I mean, the, the real cost for most organizations are, are human costs, right? So if I can, and we're seeing this with our own engineers now, like the, the amount of software that we're shipping at Kribble, I mean, we're, we're shipping in a factor of two or three what we were a year ago. I mean, amazing productivity increases. And such that, you know, what I've been telling customers is, it's gonna be really, really hard soon for you, for there to be differentiation in the market. So building software is so productive, especially copying software. So if I, like, if you have a feature, I can implement a version of that feature. Super easy. You point the models at it, and they make you something that looks like that, feels like that, does those things. So basically, everybody's going to have everything. Every vendor is going to start to look an awful lot alike. And so then the question becomes, well then, God, if everybody looks the same, how do I decide What I should buy? And that's going to become an increasingly difficult question because all the vendors are all going to have the same features. Which one do I buy from? And one of the things I've, I've long said is software is a people business. And people buy software, especially enterprises, buy software from people they trust. And I've worked with this rep for three years. They've treated me well. They've given me goo…

AI assessment note: “real cost for most organizations are, are human costs... amazing productivity increases”