An Interview with Microsoft CEO Satya Nadella About Finding Core Competencies
Listen to this post: Good morning, This week’s Stratechery Interview is with Microsoft CEO Satya Nadella . I have previously interviewed Nadella in May 2024 , October 2022 , April 2020 , and May 2019 . As I noted yesterday , I spoke to Nadella shortly after the conclusion of his keynote at Build , Microsoft’s annual developer conference . One notable thing about the keynote was the fact that Nadella was — outside of product demos — the sole presenter; one gets the sense he has shifted into a much more hands-on role at Microsoft over the last year. The reasons why are clear: my first question to Nadella was if he was happy about where Microsoft was currently positioned as a company. We talk about the reasons for that question, the status of the company’s partnership with OpenAI, and whether Microsoft has invested sufficiently in AI infrastructure. Then we talk about the future of software, Microsoft’s business model in the age of AI, and if they can operate independently from the leading edge models. At the end we talk about Project Solara and whether Microsoft will ever pay residents to build data centers. One note, with regards to a misunderstanding towards the end of the interview: there is no documentation I could find about being able to use Copilot Cowork with non-Anthropic models; Microsoft’s own documentation fits my understanding. As a reminder, all Stratechery content, including interviews, is available as a podcast; click the link at the top of this email to add Stratechery to your podcast player. On to the Interview: An Interview with Microsoft CEO Satya Nadella About Finding Core Competencies This interview is lightly edited for clarity. Evaluating Microsoft’s Competitive Position Satya Nadella, welcome back to Stratechery. SN: It’s great to be with you, Ben. So first off, I don’t know if you realize this, but at least according to my daughter, the defining word for the real grinders in Gen Z — first off, LinkedIn is like the social network. SN: That’s great! Number two, the word they all use is “build”, “I’m building, I’m building”, so who knew when I was at the first Build, I think, in 2010? Or was it 2011? Who knew you were such a trendsetter? SN: (laughing) There you go, I’m thrilled that your daughter is building and is on LinkedIn. Yeah, well, I’m not sure if she’s on there, she’s more making fun of people, so we’ll see how it works. We last talked the summer of 2024 after Build, this was up in Seattle. To say a lot has changed since then is an understatement. I had a bunch of questions I wanted to ask you about the business as a whole, things going on, I’m going to start with those, then I have questions about the presentation at the end. But relative to that, I want to ask you one simple question: Are you happy with Microsoft’s current competitive position? SN: You know, always this is the trickiest thing, you can sit here and say, “I’m happy” — that means you’re not ambitious enough and when you say, “If you’re not competitive, what the heck are you doing?”. And plus you have like 57 different product lines. SN: I’d say the thing in these platform shifts in particular is to, one, get the conceptual model of, “Where is the opportunity for us as a company?” — most people measure competitive position as if it’s a complete zero-sum game, and it’s never been the case. Which is, it is not the case with the cloud, it is not the case in client-server, and so to me, “What is Microsoft uniquely capable of doing in this new world” — that’s the key thing that we have to answer before we even get to the competitive position. In that context, “What is it that we really have a shot at?”, which is we can be a trusted purveyor of a platform, which is what we’ve always done, that allows people to create more value on top of a platform, which is again the DNA we have. Even in a world where these frontier models seem to have no limit— A very large appetite. SN: They have large appetite. That is what I feel even this Build , this conference, we are at that state where we can now really turn this from any one frontier model to saying, “Hey, there is actually a way for a frontier ecosystem to emerge where there are many stakeholders who all actually are operating with their own frontier intelligence”, that is a place where I think we have a unique shot, a unique competitive angle, and most importantly, brand permission. This is the other thing I’ve learned, Ben, which is every company thinks they can do everything, and then they realize that the world doesn’t need them to, the world wants them to do the one thing. Is that a lesson that you had to learn? SN: Yeah, absolutely. I’ve always said this, at Microsoft we are at our best when we do what the world expects us to do, we are at our worst when we do things out of envy, which is just because somebody else had some cool hit, somewhere, doesn’t mean we should go do that. But enough about the Zune, right? SN: (laughing) Yeah, Zune was a great device, but the world didn’t need Zune from us, and so that was the end of it. This identification of your unique capabilities, is that one of the changes over the last two years where that has emerged? SN: Yeah, in fact, it has emerged and also the world’s kind of gotten to it. Has it been forced on you to an extent? SN: Yeah, even my own conceptual understanding, I started by thinking of, “What are models?”, models are kind of like some stateless APIs, then I adjusted and said, “Oh, maybe there’ll be like databases” — they’re really more than that. I don’t remember talking about this with you, but last time I talked to [Microsoft CTO] Kevin [Scott], we analogized it to processors at some point, and you actually did make a comparison in terms of the partnership to your partnership with Intel. SN: Exactly. So the question now is, it’s a better conceptual model to think of what we’re doing is you have to really build a learning machine, and any company has to build a learning machine, so what I want to build is essentially a multi-tenant learning system that allows everybody to have their own hill-climbing machine . So that conceptual idea, now I’ve turned what is essentially frontier is not about any frontier model — I want to build whatever you did with M365 or with Azure into a platform which allows everybody to basically build their own hill-climbing machine right because the future of a firm at a foundational level they’ll have human capital they’ll have token capital and for the token capital they need their own hill-climbing machine. MAI Models All right, so I’ll jump to the end, you released seven new models, you emphasize the work you’ve done to build these models from scratch, not with distilling, not with using other models as teachers — so did you just articulate what the ambitions are with these models? SN: Yeah, there are two sets of things. One is we wanted to build from ground up with clean lineage, the models that we will have that we can license and allow enterprises to continuously hill-climb, so that’s why we want that model. By the way you talked about distillation — the point is to not use distillation during any of our own hill-climbing but at the very end, in fact some of the things that we are doing is, after all, we have all the OpenAI IP, in fact some of the performance gains we get is by doing RKLD, which is reverse knowledge distillation , and RL on top of it. So we have effectively two frontiers, we have our own, we have the OpenAI, and we’re going to use these things to eval match. And the clock is ticking to get to the right state you need to be while you still have that access . SN: Yeah, and there’s five years of it. But the bottom line is at any given point in time, I want to make sure that I’m using the best, most efficient model for whether it’s in coding, whether it’s in security, making sure also in our case, we’ll have a harness that’s independent of these models, we have the GitHub Copilot harness that’s used everywhere across Microsoft. Our goal is to make sure we have a model lineage, which we control end-to-end, we then use OpenAI IP, even with all of the capability it has — ultimately, the tests are going to be the evals for us and our customers. In the long run, the way it was framed today, and I thought it was very compelling, and it speaks to what you just said, was this idea of enterprises being able to take these models and in their own RL environments incorporate their data at a much deeper level than sort of a slap-on RAG implementation or basic post-training. Is that the end goal, though? SN: Yeah, the end goal for me is the following, which is I go back and say, let’s say that they’re a generalist model — if you go back even, Windows could have a release, then another release, and Adobe and Autodesk could keep building and keep going up, what’s the moral equivalent of that? That is the thing. And then in the first time, we said fine-tuning, it kind of didn’t work because we didn’t have the tools, we didn’t have the data collection regime, none of that. But now we have it. So let’s say the generalist models keep getting better, MAI models, let’s say, or OpenAI models, then you have this RLE. Right, but this deep customization of the models you’re talking about is only possible with MAI models. SN: That’s correct, but the thing that we want to start getting everyone on is this multi-tenant hill-climbing system — so if you think about it, we literally turned your use of M365, which already is a multi-tenant system, into a hill-climbing system for you. Okay, I’m gonna have to stop you, I’m going to give you an ELI5 opportunity, explain hill-climbing to the audience. SN: Hill-climbing is basically when you think about, “What does AI do?” — AI is all about taking an objective and continuously learning how to go predict and create that output that is the representation of that objective, and do so continuously. So that’s why a metaphor of hill-climbing is the best way to describe learning. And you want everybody to do this individually on their own hill. SN: Individually on their own. As opposed to like, hitching along. SN: What is your moat as a company? Your moat as a company is your tacit knowledge. In a world where AI exists, and network effects of AI exist, you need your own hill-climbing machine in which the models are learning. So the first thing we want you to do is, people don’t talk enough about this, but the private outputs, the evals, as I think about as, maybe the most important IP a firm creates are these private benchmarks and the private evals where you are tastefully recognizing what’s the output, the quality. And by the way, today’s failure cases are informing you to change the benchmark continuously, it’s not a static thing, that’s kind of how the evals work. And so if you have your private evals, then you have your own reinforcement learning environment that you’ve created, then you invite all the models to show up, and then you say, “Model A, generate the output that is maxing this eval using my environment and my trajectories and model B...”, and I can switch. In that context, the MAI models is one more lineage that you can put into,c and what we proved today was even a very efficiently trained reasoning model or a coding model can hill-climb using your traces and that will be more token-efficient and it will be fundamentally a great advantage. Exclusive to you the customer. SN: Yeah, that’s right. But is that just for now? If you fast-forward, is your vision that actually MAI models are fully competitive on the frontier with the other general models? SN: They are. Even today, when you start saying that — the world will keep getting better in general.** Well, I guess this goes back to, is this about how you need to do what you’re good at? SN: Correct. One, what we’re good at and also what’s the equilibrium of the world? Which is, if you believe there are only going to be two firms in the world, then of course, they only need two frontier models, but if you fundamentally believe that there are going to be as many firms as there are today and more, then what is the firm in the age of AI? It’s going to have human capital and token capital, how did that token capital get created? It’s not a bunch of API calls, it’s actually some set of weights even they have. Right. And so do you want to accrue that advantage or do you want to give it to OpenAI and Anthropic? OpenAI and Capex Well, speaking of the OpenAI partnership, I mentioned you referred to it like the Microsoft-Intel partnership, and sometimes partnerships are the only way to get ahead. How do you think about that partnership now? SN: I still think that it’s — I’m very proud of the fact that we came together, you remember the circumstances in which we came together were very different and the fact that there is a company now that may go public and be a trillion-dollar company— This is my question — how long were the knockdown, drag out fights between in this corner, there’s Satya Nadella, the operator, and in this corner, there’s Satya Nadella, the investor, tussling over what to do? SN: (laughing) At the end of the day, we are an operating company, investment is just more of an accident. Yeah, but the shareholders are ultimately those investors! SN: I’m glad and it’s a fantastic outcome for our shareholders too and what have you. But I think the way I came at this, Ben, is to say genuinely I’ve always approached it as, if there’s a partner that we can partner with and ourselves innovate, and they’re also successful, that’s fantastic. I always go back to the story of having built SQL Server with SAP. SAP was successful, we were successful, we also then went on to do other things. And so therefore, I think OpenAI, I’m glad we worked with them, we’re working with them, they continue to be a premier partner. As I said, until 2032, we still have a lot as a customer of theirs, them as a customer of ours, as an IP partner. So every day OpenAI does well, Microsoft does well. Is there a bit where everyone thought you were so far ahead because of your partnership with OpenAI, and now when we talk about things like your MAI models, it’s like actually “We got a little bit lulled to sleep because we offloaded too much to them, and now we’re having to recalibrate”? SN: Lots of things, one is, like all things, there’s a lot more competition, there is OpenAI, there is Anthropic, there’s Google, there is tons of folks who are in there. And so I think for us, the beginning, it was great that we got started with OpenAI. Think about where we were in 2018 to where we are in 2026, here we are competing with Google and a bunch of people whose names I wouldn’t have known in 2018, and so that itself proves that to your very first question, “How competitive is Microsoft?” — I’m glad Microsoft took that shot. Here we are competing with a bunch of new people, a bunch of old people, and we have our own game.
Source: Stratechery by Ben Thompson