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…Bill was always obsessed. I remember him distinctly saying this in the nineties. He said, “There's only one category in software. It's called information management. You've got to schematize people, places and things and that's it.” The problem is people are messy. Do people have loyalty to a model or do they have loyalty to an AI brand? You want an ensemble of models. You have agents intermediating that ensemble so that it meets your needs. Will everyone’s preference not just be for more intelligence? I'll go into the picker and manually select o3 for “where should I go get ice cream” query. It's like a rite of passage for certain software companies to try to take on Excel. Why is it so durable? We sort of don't give it enough credit. It's like I can make him do— The world's most approachable programming environment. A hundred percent. And Pieter here is who? Pieter Levels. He's like an indie— Oh yes. Yeah. Pieter Levels. I know him. Of course, you're so online. See, Satya knows who Pieter Levels is. This is why Microsoft is like a $14 trillion company. It’s the most fun place to go, man. Satya Nadella took over as Microsoft CEO in 2014, but he’s been with the company for more than 30 years. And he’s seen a lot. Microsoft has grown by 10x in the time that Satya has been running it and he’s credited with Microsoft’s success—first in cloud and now in the AI boom. Cheers, John. It was great. So what should people be excited about at Ignite? The Ignite Conference for us, more than anything else, is about making sure that AI is getting diffused inside of the enterprise, right? I mean, if there is one thing, it's more about, “Hey, what does it mean not to just admire somebody else's AI factory or AI agent, but how to build your own AI factory?” So organizing the data layer turns out to be probably the most complicated thing, which spans the enterprise, such that it can meet the intelligence. And so that's the stuff that I think we'll probably do a lot of. We still don't really have “deep research” in a corporate context. We do, that's what Copilot is about. But most people day-to-day do not have this. So are they just underusing AI that exists? Yes. In fact, it's interesting you brought that up because to me that is the killer feature. So the biggest thing we did was, we took this graph that is underneath what I think is the most important database in any company, which is underneath your email, your documents, your Teams calls, what have you. It's the relationships that, by the way, people are not working in an ad hoc fashion in an unstructured way, but they're all doing it in relation of some business event. That semantic connection is in people's heads and it's lost and for the first time there's much better recall of that. an unstructured way, but they're all doing it in relation of some business event. That semantic connection is in people's heads and it's lost and for the first time there's much better recall of that. Why do you think this is underpenetrated the enterprise? I feel like people are using lots of LLM tools. They are uploading individual documents, maybe, but I don't think most companies have the all-singing, all-dancing, all of the company's context is plugged into their everyday AI. Yeah, in fact, I would say there are two sets of things. One, it's starting, right? I always say at least compared to anything we have done, in terms of all the Office suites over our history, this is the fastest in that sense, because it's change management. At the end of the day, you got to get it in, people have to use it. Oh, by the way, in the enterprise setting, it has got to mean all eDiscovery has to work. All of the data governance has to work. We have had to plumb this purview into Copilot such that any time I'm trying to retrieve something that's confidential, it's labeled confidential, it's IRM’d and so on. So there's been a significant amount of work and that I think is where we are starting to see the uplift. The other thing I'd say is, it’s one thing to have it work across the Microsoft 365 graph, but then the next thing is, oh, what about your ERP system? The connectors kind of work, but they don't really, because they're two thin straws. You just need a much better data architecture where you have to essentially semantically embed all of these into one layer. Okay. There's been a vision for decades of your company's data at your fingertips. My favorite example of this is I really like the book Softwar on the history of Oracle and it talks about Larry Ellison doing EBCs. I think they're talking about one in Japan in the 1990s, so it's the late 1990s, and he is pitching executives on all your company's data in one place. Part of the reason this is an evergreen pitch is because companies don't actually have all their data at their fingertips. Companies do not eat their data infrastructure vegetables, and the pitch to executives is always you can go answer your questions yourself at the touch of a button as opposed to sending a request to an analyst who goes and does an investigation for you. Will we finally, this time, eat our data plumbing… You can push back on the premise, but that's my question. No. In fact, I think, if I'm not mistaken, Bill coined this term “information at your fingertips” at a COMDEX speech in the nineties. I think that's right. back on the premise, but that's my question. No. In fact, I think, if I'm not mistaken, Bill coined this term “information at your fingertips” at a COMDEX speech in the nineties. I think that's right. Yeah, and for the longest time, Bill was always obsessed about, he felt that… In fact, I remember him distinctly saying this in the nineties, which I picked up in one of the reviews I was in as a junior guy sitting around and he said, “There's only one category in software. It's called information management. You got to schematize people, places and things and that's it. You don't have to do anything more, because all software…” And that was the dream Bill always had because, for example, he hated file systems because they were unstructured. He would've loved it if everything was a SQL database and he could just do SQL queries and program against all information. That to him was like an elegant solution to information at your fingertips. The problem is people are messy, and even if data is structured, it sort of is not truly available in one index or one SQL query that I can run against all of that. So that has been the fundamental challenge of the old world, I would say. I would've not thought, none of us thought that somehow this AI thing and a deep neural network at some scaling will suddenly become the thing that figures out the patterns, not some schematized data model. In fact, one of the longest time, we used to always obsess about, “Oh, how complex do the relationships have to be or the data model needs to capture the essence of an enterprise?” And it turns out it's lots of parameters in a neural network with a lot of compute power. Dwarkesh talks about this really smart remote employee who started five minutes ago, getting at the point that the models can be arbitrarily smart and they can do RAG and they can have access to everything in your enterprise, but it's not quite the same as the model actually knowing something as a model. And so the models, unless you train custom models inside your company, cannot actually get smarter at what it is that you do. And the thousandth query is not any smarter than the first. Where do you think that goes?…

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