主持人: All right, everybody. We're thrilled to have the one, the only Tata Nadella here, the third CEO of Microsoft for a impromptu fireside chat with David Saxs, Arzar of AI and crypto. Satia third, CEO of Microsoft, born in India. What an incredible story. came here right after college and you had a little round trip to pick up your wife in your book to to bring her here. Tell everybody briefly how that occurred.

萨蒂亚·纳德拉: Well, um, you know, so that's that's a great story of the the labyrinth that is the immigration policies of the United States I think. Um, I my wife and I went to college together in India. I came here for grad school. We then got married. I got my green card. Um, and she couldn't come join because we got married. So the story goes basically I had to give up my green card. So the funny thing is I went to the American embassy in Delhi

David Saxs: and I said where's the line to give up my green card? And they said there is no such line. Um, that would be a crazy thing to do in the '9s. So it was a strange thing to give up your green card, get an H1 so that she could join, but it all worked out. So, um, you know, it's a long lost memory but it was you know, a way to work around it. Um, I wanted to ask you, uh, having

David Saxs: I wanted to ask you, having launched a Copilot first with GitHub then having a Copilot on the desktop. You made a very bold move for Microsoft to put that in the Windows product, which I use every day, on the desktop, but you did that before it really could recognize the file system and interact with applications. Got a little bit of a lukewarm reception, but now you've been doubling down, doubling down, and there seems to be, in my estimation, three modalities for knowledge workers. Elon's building at XAI, what they're calling a human emulator, if you saw that leak this week. Yeah. where they're just building employees and just putting them into their chat rooms and email. Then you have Claude came out with Co-Work this week. Incredibly powerful. People are kind of losing their minds over it. I've been playing with it for the last 40 hours. Truly impressive. What's your vision for Microsoft and how knowledge workers will actually put this to use because there seems to be a gap between you know playing around with ChatBT and getting some interesting results and getting business results.

萨蒂亚·纳德拉: Yeah. So I think it one of the most um perhaps illustrative examples um of trying to understand these various form factors is looking at coding which is obviously a form of knowledge work or uh probably the best example of knowledge work and if you think about the journey coding has been it started with u essentially uh uh the next edit suggest right that was the first time in fact my own belief in this entire uh generation of tech really sort of got formulated where I started seeing I think it was G you know there's a Codeex model back in the day it was preGPT35 uh that's when next edits started working with some real accuracy then we went to chat then we went to actions and now to full autonomous agents and then the autonomous agents can be both foreground background in the cloud or local right so that's all the form factors that exist today when you're coding and interestingly If you look at it, you use all of them, right? It's not like there's only one form factor. So that's I think probably one of the other lessons. So for example, when I'm in a CLI, I can you go a foreground agent, background agent, and then just literally go edit in VS Code, right? There all happening in parallel, right? So that sort of shows how these form factors even composed. So then you bring that to knowledge work to your point. We started with chat. chat with reasoning sort of goes beyond just request response because you now have that chain of thought uh where you can see it work now they're actions right essentially either through computer use or through uh AP you know basically skills uh and agent calls so you can do actions so that's kind of the state of the Copilot today now there is a way to think about you know the the theory of the mind evolution Right? Because you need like if you remember you know Jobs had the best line I would say for PCs or computers was to say if you it's a bicycle for the mind. Bill had a line which I liked as well which was it's information at your fingertips. We kind of need now a new concept metaphor for how we use computers in the AI age. And you have one

David Saxs: and the one I like actually came from

萨蒂亚·纳德拉: and the one I like actually came from the CEO of Notion which I you know that manager of

David Saxs: incredible product. Yeah.

萨蒂亚·纳德拉: You haven't bought it yet? I've not got that. Uh, but the it's both management of you know basically a manager of infinite minds. That's a nice way to think about it right when you sort of really look at all the agents that you are working with. You kind of need to understand what I in fact the other term I like is we macro delegate and micro steer. In fact you kind of need that in in in coding you kind of have it right. So you do a macro delegation and then I can in parallel give it instructions while it is doing work. So that's sort of the state even today of Copilot or what have you. you bring up a little bit of what one of one of the form factors I'm very excited about and you'll see us even in the next week even uh do things is while I'm sitting in GitHub Copilot what it's not as if software developers sit in isolation right it's not like the only thing I work on is my repo I attend meetings um I write specs or others have written specs that I'm implementing uh I need to have my repo be consistent with that so that means using either a straightforward MCP server or a skill I want to be able to call into my work IQ which is the Copilot bring that in that's the type of composition uh of knowledge work that'll happen same thing with security say you're a security professional you have lots of logs uh how do you sort of really analyze them you drop them into a file system then write code on top of it create a dashboard what have you those are the types of knowledge work that we can enable there I think you bring up one more thing which is can you create quote unquote digital employees digital co-workers or what have you and it's all about credentials right so the I today you could like you can literally assign

David Saxs: are you working on that as well

萨蒂亚·纳德拉: yeah so in fact we introduced something called Agent 365 as a way to give identities in fact extending the identities we have for humans today uh and the endpoint protection we have for their compute devices to agents so

David Saxs: so you might clone me working in the HR department or working in the marketing department and have a virtual correct version of me inside of office.

萨蒂亚·纳德拉: That's correct. So, so there are two sort of modalities there. One is you give every knowledge worker infinite minds. That's kind of one and then you create even infinite minds independent of the your identity because the identity is one of the key things you got to get right even for it to work right. Right. So

David Saxs: permissions

萨蒂亚·纳德拉: and decision making

萨蒂亚·纳德拉: permissions decision- making and like one of the key in things is who did what to whom is sort of the most important query in an organization right at the end of the day the organization needs to understand what work got done h and what's the provenence of that work uh and how do you trace it back right so therefore you kind of want either what if it's a human with a lot of agents then it's really macro delegation micro steering by the human whose identity was passed on. So it's delegation versus a separate identity.

David Saxs: And that was done by a level of management, product management that you've eliminated, that Alphabets eliminated. Meta has started to eliminate in their organization four years ago. You had the same number of employees you have at Microsoft now, but you put a $90 billion onto the top line of the revenue in that time and you doubled your income during that time. So how did that happen? Is that automation of those jobs? Is it you were a little bit overstaffed?

萨蒂亚·纳德拉: Unpack.

萨蒂亚·纳德拉: I think it's it's actually you're pulling on a very interesting thread which is at some level what's the big structural change that needs to happen. In fact, I would say this is probably the biggest change in knowledge work since PCs. I mean I always you know think about like how did work happen precise right? I mean think about a multinational company like ours trying to do a forecast. uh right faxes went around, inter office memos got sent and then you kind of created a you know uh a forecast then suddenly you know PCs became standard issue uh you put an Excel spreadsheet put some numbers sent it in email everybody entered numbers and you had a forecast so the work the work artifact and the workflow all changed that's what's happening so for example I'll give you uh at LinkedIn uh we used to have product managers we had designers uh we had front-end engineers and then we had CIS backend engineers and so on. So what we did is we sort of took those first four roles and combined them in fact increased scope and said let's they're all full stack builders. So I like that because that's a structural change that allows for us to increase the change both the work and the workflow between these functions and I would assume the velocity because you don't have four people communicating and that throughput of ideas it's just one person and vibe coding. Exactly. And there's a new workflow. So what at the same time as you can imagine if to build an AI product today there's a complete new workflow right it starts with eval right so basically there's this eval to science to infrastructure and so eval are done by these full stack builders and what have you and product managers in the new form the infrastructure is built by the systems engineers at the back end because they support the science that supports the product. So in some sense there's a new loop uh and you have to structurally change and so a lot of what is happening inside a tech is that change uh which is I think going to be pretty massive uh and at the same time a company like ours I have to do everything. It's not like I can just so go live in the future. I have to make sure we're doing a fantastic job of doing hot patching on Windows is done with quality uh while at the same time building the evals that are improving Copilot quality. Right? And so both of those have to be first class.

David Saxs: I assume this is the most challenging moment of your career because Microsoft was so dominant duopoly in some spaces. Um but you really weren't up against the competition level you're up against now. I was talking to Elon, you know, and he was sort of saying, well, building cars was pretty easy. Uh because I was up against the legacy car makers and now I'm up against just look at the set you're up against. Yeah, it's it's a pretty intense time. I

萨蒂亚·纳德拉: mean, so the way I I I always think is it's always helpful uh when you have a complete new set of competitors every decade because that keeps you fit. Uh if you think about it, I joined Microsoft in '92 when I had Noel as the big existential competitor we had. Um and here we are in 2026. Uh and it you're absolutely right, it's a pretty intense time. I'm glad there's the competition. uh it's it's quite honestly at the end of the day when I look at it right as a percentage of GDP 5 years from now where will tech be right uh it will be higher so we're blessed to be in this industry it's lot of intense competition but it's not so zero sum as some people make it out

David Saxs: it's getting much bigger

萨蒂亚·纳德拉: much the TAM and the you know just the impact of this tech is going to be so massive um the question then of course is what is like I I always go back to what's the brand identity Microsoft has brand permission. We have what do customers expect from us. It's sometimes we kind of overthink somehow that every customer wants the same thing from all of the competitors and finding that out, right? It's kind of a different take on the Peter Theal thing which is you got to avoid competition by really understanding what customers really want from you uh versus thinking everybody's a competitor.

David Saxs: David.

David Saxs: Yeah. So there are a lot of heads of state here obviously at Davos as well as CEOs of Fortune 500 companies and I think you got asked a question last night at the dinner about how they should think about AI and how to be successful and I recall they used the word diffusion and I was wondering if you could expand on those remarks because that really resonated with some of the policy work I've been doing.

萨蒂亚·纳德拉: No, absolutely. In fact, what you all have been doing to make sure in in this context of the American tech stack um is broadly used around the world and is trusted around the world because I think uh when I look back David to me um uh at the end of the day you create the technology but really the benefits come only by intense use. In fact, one of my favorite studies has always been this work that uh an economist I think out of Dartmouth did uh his name is Diego Comman where he studied uh basically what happened during the industrial revolution um how did countries get ahead? Um and the simple sort of takeaway from that was any country uh that brought the latest technology into their uh country and then did value add technology on top of it. Right? So it's like don't reinvent the wheel. Bring the latest and then build on top of it. That's to me uh what happens you know when you have diffusion. So especially with general purpose technologies like AI it needs to spread like right in our you know in our own country in the United States we now need we have the tech. The question is is it being used in healthcare? Is it being used um in financial services? Is it being used in every sector of the economy by large businesses, small business, public sector? Um so to me un unless and until we see that diffusion and intense use uh we're not going to have the success. Um uh and so that's the phase we are in it's f you know it's diffusing faster um and so some of the work policy work you have done um and in general all you know the good news here is the technologies there the rails around cloud and mobile that were laid out make it possible for this thing to spread right it's not you know impossible to get the tokens the question is what are the use cases how do and how do you manage the change in all of that um you know like one of the questions at least in Davos is it's one for the west and the developed nations. What about the global south? Um I think global south has a huge opportunity too quite frankly because to me like let's say you know 40% 50% of the GDP of most global south countries is public sector. So just imagine this tech making a difference in how the governments uh really parlay their taxpayer money into services for citizens and there's if there's efficiency gains that's probably couple of points of GDP growth right there and so I'm very optimistic that there's going to be a pull uh and that we should as the United States given the technology stack we have uh in Europe in Asia in you know in South America in Africa and everywhere get it to be broadly deployed.

David Saxs: You one of the questions I get asked a lot about the AI race is how do you know if you're winning or how do you know if the United States is ahead of its global competitors? And the answer I give is market share. You know, if we look around the world in 5 years and we see that American companies, American technology has say 80% market share, it means we did a good job. If we look around the world in five years and see that it's say Chinese chips and Chinese models that are being used all over the world, well means we probably lost. So you know ultimately usage is the proof of the pudding is in the eating of it. I mean the in this case the way that you know that you're succeeding is through market shares through usage.

萨蒂亚·纳德拉: I and I I would agree with that. But David, since you even worked at Microsoft for a few years, um you you know, one of the things that I'm very grounded on is always uh that Bill Gates line of a platform, right? So, one of the things that I always think about is it's market share, but it's also ecosystem effects, right? See, what the United States always has done is not just about our market share or even um the revenues to US companies. In fact, one of the things I learned at Microsoft is whenever I did a country visit, the data I would first study is in let's say in the UK or in Switzerland or what have you is what is the total employment created in Switzerland uh in our channel that used to be like the number one thing uh in our country reports right and the total number

David Saxs: that be like the number of IT workers the number

萨蒂亚·纳德拉: office workers channel so channel partners we so number of ISVs uh who were there. So we used to have a complete marker of how did the ecosystem around the platform get built one country at a time and that is what the United States has always done. In fact the US tech stack including in China got built because others built around our tech stack the same thing is going to happen. So that's why I think the work you're doing around diffusion, right, is about really increasing the size of the pie, the trust in the platform so that there is true economic opportunity quite frankly.

David Saxs: Well, you're right and and I remember actually you you brought back some memories from this is about a decade ago when my company Yammer was acquired by Microsoft. we were part of uh the SharePoint group and I remember that the um the product managers there were very proud of the fact that the revenue from the SharePoint ecosystem meaning non-Microsoft the um the consulting community the implementers who would go into companies implement SharePoint I think their revenue is something like seven times greater than Microsoft's own software revenue and I think

萨蒂亚·纳德拉: in aggregate

David Saxs: in aggregate and I think and I think Bill had a line about you're not an ecosystem or platform until the revenue on top of your platform is some, you know, factor of your own revenue. And and I and I think that I think what's really important about this is when we talk about diffusion and obviously want the United States to have this leading position, it doesn't mean it's bad for the rest of the world because they're able to build on top of those platforms and create even more value.

萨蒂亚·纳德拉: 100%. In fact, that's sort of the most important point, right? So this is not that this is not about American tech um and America revenues to the United States. It's actually creating opportunity using a new platform everywhere. And in fact you know the you know like I remember I worked on our database products uh in the '90s u you know with SAP in fact the combination of uh SQL Server and R3 were successful on both sides. There's a lot talked about Intel and Microsoft, but one of the other things that I grew up in which has sort of been foundational in how I look at the world is what we did with a European software company that is still uh you know a giant. And so that you know who knows what the next big AI app will be and where and what will happen. But uh I I sort of go in with the attitude that there will be tech companies uh maybe even top five tech companies that could emerge everywhere with even the American tech stack.

David Saxs: you have um done some amazing acquisitions and you're quite a dealmaker on top of being a technologist. It's probably the least reported aspect of your spectacular tenure and the massive growth you've had. But you did a deal with OpenAI and probably one of the most savvy slashcontroversial dealmakers of all time, Sam Alman. That deal was looked at as you you you're you're set up to get a windfall in cash which you don't need as Microsoft. always nice I'm guessing if they IPO but did you create potentially and this was the criticism of it an ultimate competitor to Microsoft and how do you think about that and how can Microsoft which missed Steve Bombber's biggest regret missing the mobile revolution how can you not have a Gemini an XAI a claude that is your own or in your mind do you have that because you have the source code of OpenAI

萨蒂亚·纳德拉: yeah I think that that's right so when when people say uh where is your foundation model? I mean at the end of the day we do have the IP but that said I think you bring up a couple different things right one is to us the most important thing when I look at what is Microsoft's uh strategy today one is we want to build token factories right so our biggest business today is Azure business and the Azure business the TAM given what's going to happen is is so huge that we now need to be fantastic uh at building these token factories and um that's means a heterogeneous fleet of infrastructure and that every hyperscaler has always done which is use software to make maximum use of it and for TCO and utilization. So that's one side of it. Then there's the app server business right which is everybody we you talked about like if everyone's going to be building agents have infinite minds have these RL gyms have eval what have you there's an entire just like every platform has had an app server this one has an app server that's what we're doing with Foundry and what have you right so there's an app server business in that app server one of the things that structurally now is pretty clear is anyone building any application or any company is going to use not one model but all the models Right? Why would I not? Right? Which is in fact I will orchestrate for any given task even multiple models. Right? There's this one nice thing that we came out in our healthcare practice called the decision orchestrator. What it proves is that by assigning roles, right? So investigator, data analyst, domain expert, just giving even prompted roles to models and then orchestrating them gets better results than any one single frontier model.

David Saxs: Am I right to read into that then that you're bullish on the open- source models and think large language models will largely be commoditized and that's not where the value will occur.

萨蒂亚·纳德拉: In fact, the way I think about it is that just like what happened

David Saxs: and Apple thinks that too by the way.

萨蒂亚·纳德拉: By the way, what the way you think about what happened in the database market, right? You know, I used to be like everything is just a SQL database until it was not, right? There was I mean, think about it. There dock databases, there is no SQL databases. The proliferation of databases, right? Who would have thought that the database market would have such a richness to it

David Saxs: or that it could ever be open source? That was

萨蒂亚·纳德拉: that's true. I mean talk about Postgress or what has happened even with which is open but there are even companies that have backed it and so so to me that's what's going to happen and to me a model is like the database market you know it's it's got it's going to differences but I sort of somehow think that uh it's not there are definitely going to be frontier models that are closed source you know there going to be open source models that are going to be uh uh frontier class in fact if anything I think in this next year what'll be probably a big part of the discussion is what's the future of a firm? A firm should be able to take the tacet knowledge it has and embed it inside a weights in a model that they control. Right? So when somebody asks me how many models should be there, I'll say as many models as firms in the world. Right? That's sort of the an extreme way. Uh because because to me that's how I think this you know this knowledge economy becomes an AI economy.

David Saxs: Are you secretly and you can say it here since we're on allin working on an LLM to exist on the Windows desktop because that you are you have it like today there's a five silica model which is completely resident using NPUs and of course using GPUs in fact the largest installation

萨蒂亚·纳德拉: um of high power in fact it's one of the fascinating the workstation is back I'm one of the most if you went to see

David Saxs: which is great for Microsoft because you you have a nice desktop business.

萨蒂亚·纳德拉: Absolutely. And so we and in fact we think that that form factor especially I mean I I always say this which is u you know I started my career on a command line. Who knows I may just end it in a command line.

David Saxs: Well you started at Sun which was the original 5 $10,000 workstation. Do you see a time where you'll be meeting with your customers here and advocating a 10 $20,000 desktop machine that has an LLM and the hardware? You can you can put a DGX card and you can have like just a fantastic machine and the models I and by the way you know we are one architecture tweak away from even having some kind of a distributed model architecture right even ane architecture that shows knows how to really distribute itself right that's the type of breakthrough that can completely change uh what hybrid AI may look like but we're absolutely committed and focused on making the PC a great place for local models uh and local models that then do even a lot of the prompt processing and call into the cloud, right? So there's a whole lot of work that can happen and that's sort of definitely something that's underway.

David Saxs: Yeah, I think that the cloud co-work has kind of shown the power of tapping into the local file drive and be able to use that. That that brings up another point. you you got me thinking about Yammer and for people who don't know um you know Yammer's claim to fame this is about 15 years ago was that it pioneered a lot of um well it used a lot of consumer growth tactics to attack enterprise software I'm wondering as you think about enterprise adoption of AI how do you think it's going to spread over the next year it feels like we're at sort of a a a critical point do you think it's going to be top down is it going to come from the CEO directing a team giving them a strategic transformation project and they're going to do an RFP or do you think it's going to spread bottom up in the enterprise through AI native employees who are adaptable who are using the tools in their own lives and they start to bring these things to work and start accomplishing amazing things.

萨蒂亚·纳德拉: Yeah. No, I think you know like all things David I think it's both the top down bottom up right. uh the that the reason I say that top down is if I look at the ROI uh of uh applying AI in customer service uh or in supply chain or in HR self-service those are the easy projects where uh IT and CXOs can make calls and that's where you'll see the first drop of uh real AI adoption but the bottom up is what ultimately will happen right I mean with even with the PCs in fact if you think back at the lawyers brought word in and then finance bought Excel in and then email came and then it became standard issue. That's what's happening right now. So for example, these agents when I sort of talk about everybody's building agents, they are figuring out a way to go create these things that are changing workflow and removing drudgery in their work. Right? That's sort of the beginning of what is a bottomup transformation. Um I you I was in fact the thing that I'm most excited about is this bottomup change even at Microsoft for example we manage something like 500 odd fiber operators around the world in in Azure today and by the way I not myself realized it a lot of it you know it's called DevOps but it's a it's a physical asset things get cut and when you sort of say DevOps that means you literally are emailing people and saying hey what happened to that fiber cut how do we repair it so there's a lot of back and forth so this network the the person who runs our global network basically has built to your point about these person they're just digital employees essentially that are doing all of that devops uh and so that's and there's a completely bottoms up uh where you see the tools it's kind of like hey I have the new way to build agents it's there I'm going to use it to create levels of automation uh that remove drudgery improve efficiency improve quality and that ultimately is a skilling thing which is sort of the big issue which is um and skilling is not mystical it's just by doing right so it's not like I go to a class per se it's like the diffusion of the tools uh and using the tools and that I think is what's really going to be happening

David Saxs: and and we're in a very interesting moment empowering an existing employee with these tools is so much easier than hiring and mentoring and bringing up the next generation so it feels like we're in a little bit of an indigestion moment at Microsoft, do you think who's going to have my job in 30 or 40 years, if the company stays the same size? Because given your technology first approach, there's really no reason to ever add another Microsoft employee at the pace this is going and you haven't for four years. So, how you may have swapped some in and out and changed the texture of it. So, how do you think about maybe this next generation? What advice would you have for these college graduates who maybe don't have an offer for Microsoft right now? And you used to spend a lot of time on that building that group, but maybe you don't have that luxury now. Do you think about it ever?

萨蒂亚·纳德拉: No, I I mean it's a great question. I you know there's a little bit of a debate what happens to early in career and how is college recruiting. I still am a big believer in uh college recruiting because at the end of the day um this is going to change the curve by which anyone can pick up proficiency in a codebase. Let's just it takes sort of just regular CS hiring. uh what has changed is perhaps for someone who comes in new into a team and to be able to ramp up thanks to all of uh the markdowns, the skills, uh the fact that I can go ask the agent. I mean, think about it, right? It's like having an unbelievable mentor who is getting you onboarded onto a codebase faster. So in some sense the productivity curve uh of a college hire is going to be much steeper than it ever before. So I think there might be a difference. In fact, one of the things we're experimenting with is a different type of apprenticeship, right? Which is you take somebody who's an IC senior dev have like a cohort of college uh hires working with them because it's a new way of working. It's like I remember like all you know everybody who joined Microsoft would say go how how did you know whatever um Cutler implement Malik or what have you right he would go try to read uh his code to understand uh what great craftsmanship looks like nowadays I think that great craftsmanship uh comes by looking at even how the 10x 100x engineers use AI to build great quality products uh and that is what these new college grads will learn and learn faster and so that's a beneficial thing for a company like us because at the end of the day you know until we saw longevity or something we need people to come into the workforce be successful at Microsoft so we are very committed but we are also making sure that the scopes of the jobs make sense for what the aspirations of people are going to be both who are currently in the workforce and people who are entering the workforce.

David Saxs: Okay, on that note, Sache Nadella, thank you so much.