Excellent. Thank you everyone for joining. Keith Weiss, I run the software equity research franchise in the U.S. here at Morgan Stanley, really thrilled to have with us from Microsoft, Satya Nadella, Chairman and CEO. Satya, thanks so much for joining us.
Thank you so much. It's a thrill to be here.
Excellent. It's really a amazing time to be talking to you about what's going on in software, partly because of how much innovation is going on in software right now, partly because of how much uncertainty there is in this room amongst investors, and we're seeing it in the stock market. I'd say over the past several weeks, we've seen an even renewed pressure, even more uncertainty about real fundamental questions on how software is gonna be built, how it's gonna be delivered, how it's gonna be priced on a go-forward basis. Maybe we could start there and get your perspective. What's your view on how software is fundamentally gonna change over the next three years, over the next five years?
I mean, it's fascinating, right? Here we are in 2026, you sit around and you say, "God, you know, there are startups that are getting founded and funded you know, in massive amounts." If you're an Excel plugin, you are a VS Code fork. People are in love with file systems again. I mean, yesterday there was a tweet which I loved, which is somebody said, "Oh, instead of just using grep, I can even do an index now." I mean, like, this is mind-blowing in the sense that something's happening where we are rediscovering some of the oldest things we had, like CLIs and IDEs and Excel plugins. It's a good question. Like, what is changed? I think to me, I go back to, what is this AI thing all about, right?
It's a pretty powerful capability we now have to essentially predict trajectories, right? That's what AI does. AI sort of takes what is called knowledge work or a consumer, sort of task, right? It could be a shopping task or a research task or I'm trying to create a, you know, a sophisticated Excel model, or I'm trying to do a forecast. Those are just basically knowledge work. They're trajectories, and AI is just great at predicting them. A couple of things are happening as you put these models, as they get better and better into our work and into our workflow. The first thing that's happening is the velocity is going up. If you think about, there's all the stats, right?
Which is, you know, Dario, I think, was here last night, and he talked about sort of what's happening in coding. You see that even, you know, what's he's seeing in with Claude, we see it in GitHub, in the sense the repos are sort of skyrocketing, right? Where the public repos have, what, four or 5% are all basically generated by these coding agents.
Right.
The same equivalent is happening in Office. I mean, it's crazy. I mean, our SharePoint, OneDrive, I mean, the artifact creation has become the thing that everybody does, because it's cheaper. It's so much easier to create sophisticated... you know, it's not just bad artifacts. These are sophisticated artifacts that are getting created, as part of a trajectory, as part of a task, as part of a workflow. In fact, last night I was playing with this where I wanted to track all startups and said, funding in startups. I put up, you know, we have tasks now in Copilot that's in research preview. Think of it as our coworker. It created this fantastic spreadsheet, right? It went off, did a bunch of work.
The spreadsheet, the problem. What it did is it generated an unbelievable spreadsheet at the end of a long-running sort of horizon task. You know, it was great because I handed up my cognitive load to it, but then it transferred it all the way back to me by creating an artifact and said, "Now go. Here is the output. Go make sense of it." This back and forth between human and AI is gonna be the next thing, which is, AI is gonna be great at doing cognitive work because it offloads cognitive work, but then it also is great like a GitHub repo that was sort of completely wipe coded. What the heck are you gonna do with it? I mean, you gotta then go, again, apply AI to understand it.
Right.
The same thing is happening even in Office and in knowledge work. What I did, in fact, was go into Excel agent mode and use it essentially as a new linter, a new reasoner, a new profiler, because that's kinda what Excel does, right? It allows you to make sense of You know, it's sort of my tool to reason over sophisticated outputs. In the past, only humans created it. Now humans and AI create it. That is sort of what's happening. The one other thing, Keith, to your point, which is also fascinating, the network effects of intelligence is how I think of it. Think about I'm sitting in front of my CLI in GitHub. I'm coding away, and I say, "God, you know, we had all these design meetings that are going on.
I updated... I know one of my colleagues updated a sort of a spec. It's in SharePoint. I want to make sure that the code that is in my repo is in sync with all of that," right? Literally, meetings and some document. I can go to WorkIQ, which is the database underneath M365, right? In fact, I've always said that's the most important database in the company that is least used as a database because they use it as just a transactional store. Now you can. I can load it up as an MCP server in GitHub, and I can say, "Please go check all my, you know, meeting notes, transcripts, and SharePoint documents and make sure that the repo is in sync." Literally, it goes off and creates a plan and then starts executing a plan.
That unlock of intelligence or the network effects of intelligence, in fact, I like to say that the next Office, which is bigger than all of the Office that came before, may be headless. That is sort of going to be, you know, the TAM expansive part for us.
Right. Let's dig into that TAM expansive part and maybe focusing on Microsoft 365 and that franchise. It's always been a core franchise for Microsoft. You're talking about the increase in volume and artifacts in GitHub. One of the other things we've seen is an increase in subscriptions. I think over a 20% increase in subscriptions. The users are increasing as well. Microsoft, particularly Microsoft 365, has always been about enabling those users. When you're thinking about this agentic future, is it more users or is it just more agents? How does Microsoft make sure that they stay in front of that curve?
Yeah, I mean, I think... Remember, subscriptions are just entitlements, because it's easier to budget, right? Like, why doesn't everybody just do consumption? The reason why everybody doesn't do consumption is sometimes it's easier to forecast. In fact, we're running into this now, right? With coding agents, we're running into it, which is because you kinda have this effect of sort of there are people who are using lots of tokens, there are people who are using what I'll call normal sort of volume of tokens.
Right.
That bimodality or the distribution is not yet stable. I think what's gonna happen there first, even for just users, because if you think about there are three types of modes, right? There's chat, let's call it what we will call tasks or co-work, right? It's delegated access. I give something else, which is asynchronous, my credentials, and say, "Please work on my behalf." That's the second thing. The third would be a full digital worker, right? Which is it'll have its own identity, it'll have its own tools, it'll have its own desktop, whatever, right? That sort of is a third thing. If you take all these three, I think the combination of subscriptions with some limits of usage plus a meter is where I think we will end up.
It doesn't matter if it's a person or an agent. I think the first place where this is happening already with the business models is in coding. I think information work also will have. From a TAM expansive perspective for us, you know, I look at all agents as users and with maybe more flexibility on how people license that.
Got it. Got it. If we think about sort of the conversation of evolutionary versus revolutionary, when I look at a lot of the dynamics in Microsoft 365 Copilot, but also what we're seeing more broadly in the environment of what the AI labs are trying to do with their agentic computing visions, it feels to me like an extension of what we've been talking about for a decade with Power Automate and Power Flow and Power BI of just bringing more visibility in terms of your systems , your data, who you're communicating with into one place. Do you see Copilot really emerging as a new AI-powered user interface for all of that, for the systems, for the data, for your teammates, for your communication?
Yeah, I mean, the interesting thing on this design side is to, you know, what happens to UI in general or what have you is, you know, the dream was always the case that can you have some form of a universal interface to all of computing? I mean, that's kinda how operating systems evolved, the browser came next and so on. This, the power of natural language, and the access to all of the tools, with an agentic loop, I think makes it very powerful. The question is, if you look at even a model company, right? It's sort of they started with chat, and now there's multiple apps. Everybody has to, you know, this is where the power of UI, right?
Yeah.
I mean, what did the OpenAI do with Codex? They have a Codex app. Makes sense, right? When you have something that is so strong in the sense of usage, then having a heads down usage app for that makes sense. The workflow between this is what you have to manage. Like, for example, even in the thing that I posted this morning was I assigned a task, it generated the spreadsheet. I actually used the spreadsheet right on Canvas inside of quote-unquote task interface, right? Inside of Copilot. I even have fantastic edit capabilities. By the way, this has been going on forever, right? Which is how does Google Docs work versus Office? I mean, it has an IR, i.e. an intermediate format.
Basically, you kind of take Office docs, and you have an intermediate format in which you manipulate.
Right.
All these things will have some intermediate format in which you will work, and then ultimately you can export out back to the full UI if you want to, so that you can go deep. The other big thing is sharing, right? One thing a lot of AI still has not yet fully cracked. In fact, you see this in coding. We've not fully cracked multi-user. The next phase is inside of Teams for us, how do you crack you agent to agent to human inside of channels? That's where UI will matter because even if AIs are all doing the work, I as a human need to reason about it. I need the UI that I use, and that I think is where it'll all come down to.
Got it.
By the way, the one other thing I should mention is we're looking at, like I was looking at why are we spending so many tokens on all this, right? Sometimes it's kind of the most token inefficient things, right? The smart thing that I think everybody's gonna start doing in the next year is tools used. That's sort of all software, and that is the way you make AI token efficient. Don't think of this as, like tools. Think of it as even if you're all AI pilled, go and say, "Oh my God, I need a lot more software to make my AI efficient." That's another way this new world will be born.
Got it. Could we talk about sort of with Microsoft 365 and with Microsoft 365 Copilot, the getting this into your customer base. You have a $450 million information workers that are using the suite. Investors got concerned by some demos that we saw from Claude with Claude Cowork. For the first time in really the last, I would say definitely five years, maybe a decade, there's more concern about the positioning that Microsoft has with Copilot. On the other side of the equation, when I look at my CIO surveys, 80% of CIOs say that they're either using Copilot today or expect to use it in the next 12 months. CIOs are seeing something in Copilot that I think investors are missing. Can you help us bridge that gap?
Like, what are the CIOs looking for from Copilot that investors aren't seeing today?
Yeah, I mean, I think first of all, it's great to see. Again, this is where the model capability and also these form factors, right. This happened even in coding, right? Which is, you know, GitHub Copilot paved the way, and then now we have, quite frankly, a lot of good competition. The market's kind of massive, right? It's no longer the tools business that I grew up with for the last, whatever, 40 years. This is a very different market which is, you know, 100x what we were competing for. The form factor innovation that's happening, right, whether it's chat or now Cowork or worker, that's sort of the direction. For us, we wanna do what we've always done, right?
Which is what we did even in the previous era, which is we have our permission in especially commercial customers through IT. We wanna love our IT customers because they are the ones who care about lots of things. They care about, you know, security. They care about compliance. They care about all of the observability, right? I mean, the reality is, come on, I mean, I can't launch OpenKlave as Microsoft. I mean, it, you know, it just wouldn't work. I don't have permission to do that because that would be considered Microsoft launching a virus. I mean, that's just not a thing. At the same time, it's a fantastic innovation, right?
That's where I mean, the fact is, think about like, what the last 15-year journey in Enterprise was. They didn't want local file system , and this is about exposing a full-on local file system. I mean, Morgan Stanley, if I go to Ted and say, "Hey, I have news for you," like, please you know, I launch something that where I want all the state and the local file system, I mean, he'll kick me out of the room. The thing that we have to be mindful of is really know where our permission comes from, and also know what the expectations of our customers are, and do a fantastic job of putting the form factors that people love. That's the path we are on.
To your point, what's happened is the unlock of WorkIQ, which is again, that database underneath M365. If, you know, you're showing me the OneNote. I mean, think about it, right? I prep for a meeting. I just go in and say, "Hey, I'm meeting Keith. Can you prep my meeting brief?" Right? It will literally know everything from 2014 to now, every meeting I've had with you, everything you said and which our folks noted, and reason over it, not like a search, right? It's a stateful agent . In fact, you can think of WorkIQ as our frontier model, right? It's basically the data plus the model embedded together.
Yeah.
That's what the CIO see the value, right? It's sort of compounding. When I say network effects of intelligence, that's a massive value for them, which is they've invested for 15 years on all of this. Now you can even compound the value on it.
Got it. It's a good segue into talking about the model layer, and there's definitely a lot of debate in the industry about the AI model layer and whether it's gonna concentrate to a small number of frontier models that are just gonna get bigger and better over time, or whether we should be thinking about a broader set of models, more task-specific models to open source models. How do you think about that trade-off between is this market gonna consolidate , or should we be thinking about an ecosystem of models?
I think there are a couple of things. One is, I think at this point, it's fairly clear industry structure-wise when it comes to the narrow way we talk about frontier models like, you know, the American ones are closed, a lot of the Chinese are open. That, that I think is going to be multi-model, right? There is not going to be a company or a product company other than the model companies, of course, are gonna be homogenous, right? Any one of them. The reality is everyone's sort of gotten on to, look, if you're building any product, whether it's for coding agents or for knowledge work or wealth management or whatever, you wanna access multiple models, right? That's going to be the case.
That means there's lots of very careful design that you wanna do, which is you wanna have the harness not get coupled with the model layer. People are getting pretty sophisticated in making sure that the harness layer is decoupled. The other is the context layer also should be decoupled, right? You don't want effectively the one model to in fact vertically integrate into these two. That'll be the game that'll be played. I'm pretty clear industry structure-wise where we will go. The other question, by the way, the other thing is people also will use a frontier model. Like let's say there's something, you have an eval. Like everything is all about evals, right?
You have an eval, you wanna max your eval, you use all these models. Let's say one particular all model was doing well on that eval. The next thing you do is you take all your traces, and then you train the model that is the cheapest to be better and hill climb on that eval.
Yeah.
That's what everybody does, right? It's no one wants to sort of be inefficient in their token spend, whether it's a company app or whether it is a ISV. The game would always be about continuous optimization of these models. Then the next thing that also, you asked the question, how many models should be there, right? I think there should be as many models as companies because if you think about it, the real sovereignty question in the world is not about even country sovereignty. It's about, look, if really knowledge work, tacit knowledge of any enterprise, of a firm, is in the human capital they have, then it also needs to be in some model way that they control. Otherwise, there's just gonna be enterprise value transfer. Forget the software companies .
It's like the rest of the economy. I mean, that's where that Citrini thing sort of goes off on, which is, that is, you know, what... Like, everybody's gonna wake up. I mean, I just don't think we live in a real world and in a real political economy, therefore, people are gonna say, "Oh, no, that's not gonna happen in my house. I'm going to have, my model that is sovereign and independent of any frontier model," That's the other sort of direction of travel.
Got it. Can we talk about the model that Microsoft is building? Of course, you have a great relationship with OpenAI. You have research IP rights. You get access to their models. Mustafa is also working on models within Microsoft. Is there a differentiation between what Mustafa is working on versus what OpenAI is working on?
Yeah. We have the OpenAI models and the OpenAI IP, we have essentially, if you look inside of Copilot, whether it's GitHub or Microsoft 365, we have lots of models. It's not any single model. The one model would be a mid-trained OpenAI lineage or an MAI model. We basically are continuing to optimize these models. What are we optimizing for? Our evals, right? You know, all of us now at this point, the game is about private evals, because we know the benchmarks are all saturated . The question is, how do you really make sure that any flops we assign to any research compute, right?
Whether it's post-training of an OpenAI model or even our own model, is all about maxing the evals that are private, so that means some product impact. That's the job number one. The second piece inside of that is all about COGS reduction, right? Which is the Auto mode, right? One of the things that I think this week or last week, there was a nice paper by the vLLM guys, the semantic router, right? If you remember when GPT-5 came out, they had a router. Now even the sophistication of the routers are getting good, right? That means the models that you choose, the modes of the models you choose, the tools that you choose with it, that's the think of it as a meta model, right? That's the most important thing.
Our Auto mode inside a Copilot, Microsoft 365 Copilot, GitHub Copilot, is essentially doing that optimization or maxing the evals, reducing the COGS on a continuous basis.
Okay.
Our frontier work, our super intelligence work will all be about really getting good and hill climbing on it. The great news for us is, you know, we have access for, whatever, five more years or what have you to, you know, till 2032. Therefore, we wanna max the value of what the OpenAI R&D is while also making sure we have all the capability. It's no different than, by the way, what we are doing in Silicon. I think you have Jensen here next. You know, we work deeply with him there, which is he's, you know, he's doing lots of the innovation. We are also working on Maya, similar approach.
Got it. Got it. If we talk about the OpenAI relationship, it started 2018, very early before we were talking about any large language models or generative AI. It's evolved a lot since then. What's the current status of that relationship, and how should we expect that to evolve on a go-forward basis? It's a very important relationship for Microsoft.
Yeah. I mean, I think, Yeah, I mean, you know, going back to 2018, I don't think any of us thought of, you know, we'll be here in 2026, talking about, what is it? Like, close to a, what, a trillion-dollar company, right? I mean, that OpenAI is. So we're thrilled to have invested in them, partnered with them. Although none of those things were the, the sort of in my head at that time. Now, who would have thought that, you know, I'll sort of earn the credit of being a good investor, but here I am.
It's a great investment. Yes.
The thing that was foundational to it. It's fascinating. I always think back at it. The paper I read, which by the way was authored, one of the authors was Dario, when he was at OpenAI on scaling laws. That was the bet, which is when they all sort of had the conviction, Ilya, Dario, Sam, all of these chaps were really into, "Hey, look, the scaling stuff works, and we should go at it." They showed me those charts, and I kind of understood it, but then I sort of said, "Man, these chaps are really good at this, and they..." I was always obsessed about NLP, so therefore I wanted to take that bet. It's an important partnership. It's worked very well for them.
It's worked very well for us. We also know that they are now a big company, that they need some flexibility, and we've given them the flexibility. They're also gonna be a customer. We're an investor. We're gonna be a partner. We're also, you know, even the latest partnerships they have are all fine by us because at some level, our exclusivities, our rev share, our equity partnership is all sort of what's gonna be healthier because of all this.
For me, one of the things that has marked your tenure as CEO at Microsoft is really embracing openness and open ecosystems, right? I think one of the foundational moments for me is when you came on stage and said, "We're gonna treat Linux as a first-class citizen on Azure." It almost feels like OpenAI and OpenAI relationship is similar, right? That it behooves both parties to have more flexibility, more openness to let them grow. You get the IP, you get the revenue share, and you both benefit from a more open relationship.
Yeah. I mean, I think, you know, since this is an investor conference and not a feel-good conference, right? The thing that I go back to is there are very few zero-sum battles, and I think we overstate that a lot. Some of the big strategic mistakes are made when you're not clear about, wow, what could be an expansive way for me to think about my opportunity-
Right
... versus getting narrowly stuck on everything being a zero-sum battle. In fact, our biggest mistakes, I would say, strategically would have been historically made when we didn't view, like somebody else's success doesn't need to be your failure if you can ride it. It's sort of a thing that needs to be talked about more. In fact, it is. Like, without Intel, I don't know if Windows would have happened, right? Without, in fact, without Mac, I wonder whether Office would have happened, right? I mean, that's sort of the world I come from, and I'm always looking for, first, what's the non-zero sum, where we can add value to our customers. Then, of course, there are zero-sum battles, and we'll compete.
Excellent. If we talk about vertical integration, we talked about it a little bit in terms of needing to maintain flexibility with the harnesses and the context layers within the model. There's also some really great innovation going on from Google, where they're integrating the TPU layer with the model layer. Is that something that Microsoft has to pursue more aggressively? Because I know you guys do have your own silicon initiative. How important it is to have that strong integration between sort of the silicon layer and the evolving software layers on top of it?
I think the way I think about all of this is, if you take the like the broad, perhaps investor question on this, which is what's the best way to think about ROIC on capital spend? I would say there are a couple of different dimensions to it, right? One is, you want TCO to be great. You can't be upside down on cost. Now, my belief is, since this is a multi sort of generation thing, it's not about any one time, right? You really wanna make sure you are always going to have the best TCO. That's why my fundamental bet is you wanna have system software over a heterogeneous infrastructure. That way, then the latest innovation, right?
I'm sure Jensen will come talk about sort of some very cool stuff he's working on next and, you know, let's call it on some low latency inference. God, I want that, right? Why would I not like, you know, he? Maybe I'm also working on it, but it may be two years from now or 1 year. No, I want the best always in my fleet. Then I want my system software laid out on top of it, right? That's kinda where I like our thing about, hey, we have a Maia 200 today that does competitively, right? It's in fact marked on TCO per dollar, performance per dollar. It's leading, in fact.
Right.
It's leading today. That is not a guarantee that it's leading all the time. Therefore, I shouldn't get too high on my own supply here of just because I have this means that's the end of the game. No, I want that, and then let me then sort of make sure I'm also getting everybody else's innovation in. Use software to then schedule across all of this and manage TCO by generation. The next layer, of course, is utilization, right? That's again, a software game. Really max the util on it. Make sure you have a diverse demand, right? We have 1P and 3P, even 3P. We have OpenAI book, we have Anthropic book, but we wanna also have the long tail of enterprise IT.
All three of these, I think, are more important than just like, oh, I have a model and a sort of an accelerator. Like TCO, and cost economics is, you know, you gotta have diverse customers, great utilization, multi-generation TCO curve. It's a lot more sophisticated than just one simple thing.
Got it. You're talking about unit economics and the ROI of the CapEx spend. I think it's equally as surprised as we would've been in 2018 to be talking about how big OpenAI is. I think we'd be equally surprised to see how much we're spending on CapEx today, how much infrastructure we're building out in terms of data center. It has caused concern amongst investors. Does this fundamentally change the economics for Microsoft? Does this fundamentally make it a more capital-intensive business that's gonna bring down gross margins? How do you see that equation playing out in the near term and then longer term?
I mean, I think I mean, that capital intensity has been true even in the cloud era. That, by the way, is the other thing that is probably worth pulling the thread on, right? We talk a lot about AI accelerators, which are obviously super important, but these agents are really driving up, guess what? Regular compute use, right? They're like, you know, the innovation on the microVMs and the containers and the security boundaries on this and storage requirements. Basically, it's a full-on system upgrade of everything: the network, the compute, the storage, this AI accelerator, and that's all obviously all exploding, therefore, the capital intensity increases. I fundamentally think that this is a capital-intense business, but it's a knowledge-intense business as well, right? That's a softer business.
That's sort of the way I think that this industry is probably unique in the sense that you can't think of it as just a pure industrial. This is where, interestingly enough, even on the schedule of how profit comes, right? You think about it. It's not like we've retired any GPUs yet, even though we have all the power constraints and so on, just because we have gotten our software so good, and some of the workloads optimize so good on that we are able to take the life of these things and really max them out.
Overall, I would say, yeah, we have to manage a capital-intensive business, but using all the levers software gives us in managing TCO, managing utilization, optimizing the kernels by workload, ensuring that there's a diverse set class of customers, using the diurnal curve even, of utilization to create new SKUs to clear markets. I mean, those are all things that I think will generate great ROIC. This is probably unique. I know the way we have set it up is you track the Azure KPI. The thing that I keep complaining to Amy always is like, "Hey, I love the Azure KPI, but I don't allocate my capital to Azure KPI, right? I allocate my capital to the Microsoft KPI because I have these, all these other businesses that are using the same capital.
Right.
It has a different growth margin profile. If, you know, so that's kind of at least how we will, between Amy and me, will take a look at the long-term ROIC and margin profile of the business, and the margin dollars, not even just the margin in percentage.
Yeah.
Because even if it's a capital-intensive business, and we have the ability to use software to generate margin dollars, this, you know, will be a much bigger business than we ever had. I mean, that was the thing. If you remember, Keith, it's funny that you tracked us all through, right? I remember when I became first CEO, everybody said, "Oh my god, isn't it too late, man? Like, why bother to even build a public cloud, because Amazon's so far ahead?" We knew it was going to be multiplayer. We knew that there is gonna be margin. We kept building. That is, I think, what, and the reason why that was the case is it's software.
Got it. You touched on the allocations and capacity constraints. Definitely a hot button topic for investors, the need to allocate towards R&D and first party versus just Azure. I was having dinner with Jonathan Neilson last night, he said the real solve to all of this is more capacity. It's kind of a first problem, a first party, first class problem to have of you have too much demand versus your capacity. How should we think about the timeframe for that settling out, for the capacity coming online that you could feed all of the mouths within Microsoft?
Yeah, I think Look, I think the challenge is what we are seeing is not just linear growth in some of the demand. Therefore, I think the capacity challenge. It's also not any one thing, right? It's not just power. It's sort of silicon. It's, you know, it's wafers. It's substrates. It's memory. It's storage. It's everything. It's compute. I feel like, you know, it's gonna take a lot more upstream capacity to get built, quite frankly, before we have some relief. This is where this is there to stay. The question is what you said, which is, how do we make sure we allocate things here that are strategic? That's where I think the tension is, right?
Which is, and I get it, which is you would like, and not all of you uniformly, but some of you would like that allocation to work in ways that just maximize the short term. That makes no strategic sense for Microsoft, right? Microsoft investors who are long term. Because you wanna be careful, right? You don't want to sacrifice your own 1P, which is gonna be higher margin, by just not feeding that product. I mean, that's not a sensible thing.
Right.
Even, like, when we say, well, we're gonna allocate to our R&D, as I said, we're not allocating to our R&D, in ways to just sort of, you know, win some contest. No, I wanna allocate my R&D to create a model that's gonna COGS reduce, which is again, sort of margins for investors long term, right? That is the asymmetry we will have, right, between what, you know, decisions I'll make, versus what you may want me to make in the short term given the supply constraint. That's where we will just have to be very disciplined, in not...
Oh, by the way, one other thing that I'll mention is we'll also wanna be careful about pricing, which is, you know, look, we see this even in our supply side, which is people are gonna take, you know, different strategies. Some are gonna be very long-term oriented.
Right.
Some will be short-term oriented. We'll remember that, by the way. The thing that, we wanna be is long term oriented, even with our customers.
Yeah.
These cycles will go, you know, come and go, and we don't want, you know, we wanna earn trust in periods like this, with customers who depend on us. These are all, you know, fairly important sort of criteria for us.
Outstanding. Unfortunately, that takes us to the end of our time. Really exciting times in software, really exciting times for Microsoft. Feels like you guys are really positioned well for this opportunity. Thank you for coming in.
Thank you, Keith, for your covering of us over all these years, throughout my entire tenure. I deeply appreciate it. I know you're going off to do, you know, newer and better things, we wish you all the best with that. Thank you so much.