https://youtu.be/QHhj0iPPqoQ
Satya Nadella, CEO of Microsoft, interviewed by Farred Zakaria
Deep Minds Dennis Hassaba said last week, "We've essentially found a way to make sand think. Silicon chips are made of sand."
Artificial intelligence is fueling the American economy right now. The appetite for anything AI related seems never ending as tech companies rush to build data centers, buy chips, and fuel technology development. But so much of this spending is one massive bet. And many on Wall Street are worried about whether they will see returns on these investments.
Here's part one of my exclusive interview with Satya Nadella, the CEO of Microsoft.
Satya Nadella, welcome to the show. Thank you so much, Fared, for having me.
Are we in an AI bubble and has it begun to deflate? You have a 30% stake in open AI. They have promised to spend hundreds of billions of dollars. They make tens of billions of dollars. They'll make$2 billion dollars this year in revenue. Uh it just feels like the the math doesn't add up and there is going to be a moment of truth. Am I wrong?
I think the the moment of truth really more is the following. Uh the way I look at it is this is a new input. This is a new general purpose technology that is going to drive productivity and that productivity has to translate into very broadspread economic growth uh that is economywide in terms of GDP growth and if we don't see that uh then we are going to have a problem. So unless we see the that broad economic growth uh we're not going to h you know have this movie end well. But I am all about how do you ensure not about any one firm right quite frankly it's about every firm in the economy right whether it's a small business whether it's a large multinational or a public sector institution can they see real benefits of this technology we are in the early innings of it but there's real proof points of that so the big news this week is that a Chinese firm Moonshot AI released a model Kimmy that is opensource course open weight which means you can kind of see the inards of it which American uh firms by and large do not allow. Uh people think it's very very good almost as good as the top American models. Um is it not likely that the most of the world is going to adopt these openweight Chinese models because they're much cheaper. They can do mostly what you need to do. um you know most companies are not using uh AI to solve for mats theorem they're using it to rationalize their inventory systems or things like that so is this you know does this mean China has an edge when I think about let's say American competitiveness in the digital sector or in it's always come from not any one thing but it's come from this approach I think the US has always taken which is the ecosystem approach all over the world it's been exportled uh it's been about trust in our technology right so for example if you take the Chinese models guess where where these models run they run on um a lot of the hyperscalers that are American all over the world uh in fact that's good uh because we then these are openweight models that means we get to monitor them we get to test them we get to postrain them so when tinker machines or thinking machines releases a new model. Is that an American model? Is it a Chinese model? Yeah. There may have been a base model that was Chinese, but they've done post training. They've released it. So, I think that one of the things that's lost in this is the understanding even of how the US became competitive in the first place. They didn't become competitive because of one invention. They became we became competitive because we took our technology we built a rich ecosystem where others could participate in other countries and trust our stewardship of this ecosystem and as long as that remains we will absolutely be competitive and we will win and Chinese will have a role in it whether it's in the uh openweight models or other technologies but you know it's not about that zero sum it's about really thinking in ecosystems next on GPS Yes, many people are worried about how AI uses their data. [music]
It may come as a surprise, but so is Satya Nadella. We'll discuss when we come back.
Microsoft CEO Satya Nadella made headlines earlier this month when he warned that companies using AI pay for intelligence twice. once with their actual payments to the AI firms and again with something even more precious, their data and their unique knowledge.
In other words, asking AI questions doesn't just result in answers for us.
It tells AI what we're thinking. This creates what Nadella has spent the reverse information paradox where AI models and their providers are the ones gaining more knowledge and overwhelmingly reaping the benefits. more now of my conversation with Satya Nadella. So this is something you've been quite vocal about the idea, you know, to put it in layman's terms that every time you use an AI model, you're giving them your data, you're giving them your your thought process and they're essentially stealing that and making their models better and eventually they they have all that information. You don't. A version of this happened to the media companies uh you know and the newspapers and magazines when Google and the internet uh came about. So there's two arguments against this. One, what you're describing is of course very beneficial for Microsoft because your business model relies on commoditizing that space and then you know putting value where Microsoft has lots of products. Uh is it feasible? C is there a way in which you can take advantage of AI and still control your your data and your reasoning particularly for an average person maybe a fancy company like yours can do it but how does an how does an individual say look I do want to use AI but I want to in some way be in charge of my data 100%. So in fact this is the the real question right because my thesis is simple which is if the firm has to exist let's take let's leave consumer markets outside because to some degree there's got to be some value exchange in the consumer space where you're getting something for free maybe for your data that's sort of how the advertising business model has worked so let's leave that aside but at the firm level this is the first time where the decision should be okay I am a firm that creates knowledge and I need that knowledge to stay inside the firm. I not only have human capital, but now I'll have increasing levels of token capital. The only way to preserve that is what I describe as your control over ensuring that the reverse information paradox doesn't happen, right? Which is every time you use the model, all of the metadata around it is sort of retained by you so that you could use all of that to train perhaps your own weights or your own, you know, model. uh and to me that's what I think is going to be absolutely you know you know if you go back the patents copyrights trademarks all were created to protect the seller this is the first time where we will need to have I would say even the rights that protect the buyer uh but even the short of that in the immediate term there is an technical approach that's kind of what I wrote in my post that you could take uh to protect yourself right where not only are you able to use the frontier models but for example example, by keeping the harness separate from the model, the context and memory separate from the model, you absolutely can use multiple models for what they're great at. Uh at the same time, any one model can go away and you can still continue minutes, 2 secondsto be in sort of uh control of your own destiny. And so to me there is an absolutely an approach and that's what is a sensible approach and it's of course not what Microsoft does but it's not about a a firm specific thing because any firm that doesn't have this control I will claim will not remain a firm because you've essentially outsourced your thinking. Let me ask you about the future of work. Microsoft employs about 200,000 people, but the number of AI programs, programmers, you know, what people call agents, it's probably 2 million or 20 million soon Um, is is it likely that 10 years from now, Microsoft will either have the same number and not have grown or maybe even have fewer given the amount of work and the kind of quality of work. Anthropic says almost all its code is now uh written at the first uh uh level by by computers by AI. Um what happens to human beings?
Yeah, it's a great question. You know, if you think about this is the the real challenge in all of these transformations, right? The lump of labor fallacy and our lack of imagination get in the way, right? Which is if you sort of somebody came to us for in the early ' 80s uh and said, "Hey, you know what? three billion people are going to get up in the morning uh and start typing. We would have said why does the world need 3 million typists? Uh except we invented
in the last whatever 40 years this entire economy of knowledge work uh and all of us went to work in it in
different roles. And so that's the type of transformation even inside of Microsoft right what does it mean to be
a software engineer is changing uh because at some level these coding agents have made all of us right creating a document or a software program to some degree are now the same.
Does that mean somehow the specialized deep systems engineer who we still needed in order to be able to build the distributed systems in Azure goes away?
No chance. But will anyone be able to create an app that required in the past some IT? Absolutely. And so as that
change diffuses, I think the core spine of the organization, how we're organized, what functions we have, the work artifacts, the work flows will change, wages will change. Uh and that process is going to have some
significant displacement. It's all not going to be hunky dory. But when we come out on the other end, uh I absolutely believe there will be new jobs that we will value as humans. In fact, you can see it even today, right? One of the reasons all of us react to someone who
gives you just pure AI output and you say, well, I don't want that. I want to know that there was a human behind it,
who actually looked at it and our ability to discern what that human did with the AI output is going to be the new quality we will in fact value. And so I think as we get through this trans transformation uh we will understand uh how humans continue to evolve and value each other's contribution uh to advancing our societies. People say that human creativity is the one thing that AI models cannot match. What if that's not true? I'll ask Satya Nadella that next.
And now more of my exclusive interview with Satya Nadella, the CEO of Microsoft.
I'm struck by something about AI. People often talk about creativity as one of the things that human beings will be able to do that AI can't. But I'm struck by because of the nature of AI, you know, it's a kind of predicting what the the next likely word token.
It's actually quite creative because it's kind of like in a sense hallucination is the is is a feature not a bug. It's it's thinking up things, right? And so you love poetry. I love poetry. AI is astonishingly good at poetry. What does that tell you about what's left for human creativity?
You know, the the fascinating thing is it's that ability to empower each of us to be more creative. I'll just give you even a simple example this morning, right? You know, with the something like GitHub now, right? the ability even for me like I was a programmer [laughter] you know over the years as I've sort of evolved in the organization uh it's not like I'm daily programming but now I am like this morning I come in and I wanted an app which went into my inbox triaged my inbox created a project tracker application just for myself um it I was able to do that to me to be able to have that power that somehow I can express a highlevel intent right the int like the intent itself is creativity but then the rest of it was all executed and automated I think is going to create I would say new form of art new form of expression uh new form of ability to I I sort of sometimes describe the new work as macro delegation and micro steering right every one of us will become better at management uh through intents and at the same time having the ability to steer exactly to the place where we want it.
So, a bunch of Microsoft employees, former employees have started a company uh and they say that that company is going to be run at the CEO level by AI by an AI agent. So, effectively they will they will execute the orders that the AI CEO tells them. Do you think that will work and why and why or why not?
I mean to having an agent that works for a CEO is like essentially a delegated AI that takes your identity uh and your credentials. So to some degree I think we're already at an age where I think about the fundamental unit of work is a human plus their agents and at the end of the day human control is what I think all of us will value personally as institutions and as a society. So that is the key thing. So even when for example I thought what the pope did at the encyclical was fantastic right because he talked about any technology
that takes away human dignity and agency is going to be rejected by definition right I don't think we will accept it as
a society but anything that empowers us to do more to achieve more to be more ambitious about you what we can do
whether it's a CEO or a frontline worker we will accept it and so at least that's certainly the direction of travel that I'm for.
And so do you think that it's fairly clear that the human being will be in control? You say he should or he or she
should be in control, but do we have the kill switch? Can we pull the plug? Or do you worry, as Elon Musk used to, that the machines will eventually rule us?
I think I have much more faith in our political economy and its institutions
that the backlash, right? I mean, you've written a book about this. Revolutions uh are great as long as the backlash is
managed. Uh and that's sort of been the lesson of history. Um and so I always say that's why I want an English
revolution, not a French one. And that will only happen if we really really manage through this process uh where we are in control and that I think is the foundational issue that uh will be defining our era.
Satya Nandella pleasure. Thank you for coming on.
Gemini:
In his interview on
Key Interview Topics
AI Investment & Bubble Concerns [
08:10 Opens in a new window Discussion on whether massive AI spending and high valuations represent a bubble. Nadella frames AI as a new general-purpose technology that must generate broad, economy-wide productivity and GDP growth across all sectors to justify its investment.
U.S.–China AI Competition & Open-Weight Models [
10:01 Opens in a new window Addressing the rise of competitive open-weight AI models from Chinese firms (such as Moonshot AI's Kimi). Nadella argues that American tech competitiveness relies on an ecosystem approach and trust, noting that international open-weight models often run on American hyperscaler cloud platforms.
Data Ownership & The "Reverse Information Paradox" [
12:35 Opens in a new window Highlighting the risk of organizations paying for AI twice—first financially, and second by giving away proprietary data and knowledge. Nadella outlines technical approaches and rights needed to help companies protect their data harness while leveraging frontier models.
The Future of Work & Job Displacement [
16:18 Opens in a new window Analyzing how AI and autonomous coding agents will transform roles like software engineering. Nadella references the "lump of labor fallacy," arguing that while displacement will occur, human work will evolve toward higher-level oversight, discernment, and new valued roles.
Human Creativity & Macro Delegation [
19:14 Opens in a new window Exploring how AI matches or aids creative tasks like poetry and app creation. Nadella describes a shift toward "macro delegation and micro steering," where humans set high-level intent while AI automates execution.
Here are additional key topics and expanding ideas that build on Satya Nadella’s main discussion points from his
Expanded Ideas & Deep-Dive Angles
1. The Macroeconomics of AI Productivity ( ROI & GDP Impact )
Beyond the Hype: Nadella argues that AI ROI won't come from tech company valuations alone, but from broad-based GDP growth across traditional sectors (retail, healthcare, manufacturing).
Added Idea / Perspective: Explore how companies can move from early "proof of concept" experiments to measurable bottom-line improvements. Key metrics to track include unit cost reduction, cycle time improvements, and revenue expansion from new product capability.
2. Open-Weight Models & Global AI Geopolitics
The Cloud Neutralizer: Chinese open-weight models (like Kimi) compete closely with U.S. proprietary models, but Nadella emphasizes that they still run on American cloud hyperscalers (Azure, AWS).
Added Idea / Perspective: Examine the growing trend of post-training and fine-tuning. By allowing developers worldwide to post-train open-weight models, American cloud providers maintain ecosystem dominance and security observability, shifting the strategic advantage from who built the model to where the model runs.
3. Data Sovereignty & "The Reverse Information Paradox"
Protecting Enterprise Capital: Organizations risk surrendering their proprietary knowledge (their "token capital") to foundation model vendors when querying AI systems.
Added Idea / Perspective: Highlight technical frameworks that decouple the model from the business knowledge base, such as Retrieval-Augmented Generation (RAG) and isolated context harnesses. To maintain long-term competitive advantage, enterprises must establish "buyer rights" over their metadata and context memory.
4. Evolution of Knowledge Work: "Macro Delegation & Micro Steering"
The Shift in Skill Sets: Rather than typing or writing code line-by-line, workers transition toward defining strategic intents and orchestrating autonomous software agents.
Added Idea / Perspective: Discuss the changing nature of workforce training. Software development shifts from syntax mastery to systems architecture, prompt intent formulation, and validation/discernment, where human oversight guarantees output quality.
5. Autonomous Agents & Human Agency
AI-Led Organizations: Reacting to scenarios like AI-driven CEOs, Nadella frames the fundamental unit of future work as "Human + Agents", prioritizing human dignity and executive control.
Added Idea / Perspective: Address the legal and governance implications: Who holds ultimate legal liability when an autonomous agent makes an operational error? Emphasize the necessity of institutional "kill switches" and governance frameworks that enforce accountability.
Here is the transcript of the interview segment between Fareed Zakaria and Microsoft CEO Satya Nadella from
Segment 1: AI Investment, Bubble Concerns, & US–China Competition
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But I am all about: how do you ensure not about any one firm, right? Quite frankly, it's about every firm in the economy—whether it's a small business, whether it's a large multinational, or a public sector institution—can they see real benefits of this technology? We are in the early innings of it, but there are real proof points of that.
[
[
So, for example, if you take the Chinese models, guess where these models run? They run on a lot of the hyperscalers that are American all over the world. In fact, that's good because these are open-weight models, that means we get to monitor them, we get to test them, we get to post-train them.
So when Thinking Machines releases a new model, is that an American model? Is it a Chinese model? Yeah, there may have been a base model that was Chinese, but they've done post-training and released it.
So I think that one of the things that's lost in this is the understanding even of how the US became competitive in the first place. We didn't become competitive because of one invention. We became competitive because we took our technology and built a rich ecosystem where others could participate in other countries and trust our stewardship of this ecosystem. As long as that remains, we will absolutely be competitive and we will win, and the Chinese will have a role in it—whether it's in open-weight models or other technologies. But it's not about that zero-sum game; it's about really thinking in ecosystems.
Segment 2: Data Ownership & The "Reverse Information Paradox"
[
So this is something you've been quite vocal about—the idea, to put it in layman's terms, that every time you use an AI model, you're giving them your data, you're giving them your thought process, and they're essentially stealing that and making their models better, and eventually they have all that information and you don't. A version of this happened to the media companies and newspapers and magazines when Google and the internet came about.
So there's two arguments against this. One: what you're describing is, of course, very beneficial for Microsoft because your business model relies on commoditizing that space and then putting value where Microsoft has lots of products. Is it feasible, and is there a way in which you can take advantage of AI and still control your data and your reasoning, particularly for an average person? Maybe a fancy company like yours can do it, but how does an individual say, "Look, I do want to use AI, but I want to in some way be in charge of my data"?
[
But at the firm level, this is the first time where the decision should be: "Okay, I am a firm that creates knowledge, and I need that knowledge to stay inside the firm. I not only have human capital, but now I'll have increasing levels of token capital." The only way to preserve that is what I describe as your control over ensuring that the reverse information paradox doesn't happen, right? Which is every time you use the model, all of the metadata around it is retained by you so that you could use all of that to train perhaps your own weights or your own model.
To me, that's what I think is going to be... if you go back, patents, copyrights, trademarks all were created to protect the seller. This is the first time where we will need to have, I would say, even the rights that protect the buyer.
But even short of that in the immediate term, there is a technical approach—that's kind of what I wrote in my post—that you could take to protect yourself, right? Where not only are you able to use the frontier models, but for example, by keeping the harness separate from the model, the context and memory separate from the model, you absolutely can use multiple models for what they're great at. At the same time, any one model can go away and you can still continue to be in control of your own destiny.
So to me, there is absolutely an approach, and that's what is a sensible approach. It's, of course, what Microsoft does, but it's not about a firm-specific thing—because any firm that doesn't have this control, I will claim, will not remain a firm, because you've essentially outsourced your thinking.
Segment 3: The Future of Work & Human Creativity
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[
Which is: if somebody came to us in the early '80s and said, "Hey, you know what? 3 billion people are going to get up in the morning and start typing," we would have said, "Why does the world need 3 billion typists?" Except we invented in the last 40 years this entire economy of knowledge work, and all of us went to work in it in different roles.
And so that's the type of transformation even inside of Microsoft. What it means to be a software engineer is changing, because at some level these coding agents have made creating a document or creating a software program to some degree now the same. Does that mean somehow the specialized, deep systems engineer who we still needed in order to be able to build the distributed systems in Azure goes away? No chance. But will anyone be able to create an app that required in the past some IT? Absolutely.
And so as that change diffuses, I think the core spine of the organization, how we're organized, what functions we have, the work artifacts, the workflows will change, wages will change. And that process is going to have some significant displacement; it's not all going to be hunky-dory. But when we come out on the other end, I absolutely believe there will be new jobs that we will value as humans.
In fact, you can see it even today, right? One of the reasons all of us react to someone who gives you just pure AI output and you say, "Well, I don't want that, I want to know that there was a human behind it who actually looked at it." Our ability to discern what that human did with the AI output is going to be the new quality we will in fact value. And so I think as we get through this transformation, we will understand how humans continue to evolve and value each other's contribution to advancing our societies.
[
[
With something like GitHub now, the ability even for me... I was a programmer over the years, as I've evolved in the organization, it's not like I'm daily programming. But this morning I came in and I wanted an app which went into my inbox, triaged my inbox, and created a project tracker application just for myself. I was able to do that.
To me, to be able to have that power where I can express a high-level intent—the intent itself is creativity, but then the rest of it was all executed and automated—I think is going to create a new form of art, a new form of expression, a new form of ability.
I sometimes describe the new work as "macro delegation and micro steering," right? Every one of us will become better at management through intents and at the same time having the ability to steer exactly to the place where we want it.
Here is the remainder of the transcript segment from
Segment 3 (Continued): AI Agents, Human Dignity, & Control
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And at the end of the day, human control is what I think all of us will value personally, as institutions, and as a society. So that is the key thing.
So even when, for example, I thought what the Pope did with the encyclical was fantastic, right? Because he talked about how any technology that takes away human dignity and agency is going to be rejected by definition, right? I don't think we will accept it as a society. But anything that empowers us to do more, to achieve more, to be more ambitious about what we can do—whether it's a CEO or a frontline worker—we will accept it. And so at least that's certainly the direction of travel that I'm for.
[
[
And so I always say that's why I want an English Revolution, not a French one. And that will only happen if we really manage through this process where we are in control. And that, I think, is the foundational issue that will be defining our era.
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