How close is AI to replacing you as the CEO?
I just think the CEO job is not that complicated.
People are standing and telling about how AI could make a lot of jobs go away, right? And like why wouldn't you feel a sense of anxiety about it, right? And like I think those are deeper issues which we have to tackle as a society.
I/O ended with Demis Hassabis, the CEO of DeepMind, coming out. He said, "Google's cutting-edge research and products will help unlock AGI's incredible potential for the benefit of the entire world. When we look back at this time, I think we will realize that we were standing in the foothills of the singularity." Can you tell me what it means to be in the foothills of the singularity?
Hello, and welcome to "Decoder." I'm Nilay Patel, Editor-in-Chief of The Verge, and "Decoder" is my show about big ideas and other problems. Today, I'm talking with Google and Alphabet CEO Sundar Pichai in a conversation we recorded just after the Google I/O developer conference. This is the fifth year Sundar and I have sat down after I/O, and it's become one of my favorite "Decoder" traditions. There's always a lot of news at I/O, and this year was no exception. Google has powerful new Gemini models, it's putting AI agents in everything, and it's making huge changes to Search on both the web and YouTube that will once again reshape the information ecosystem. That's a lot to talk about, and Sundar and I got into all of it, but I also realized that it's been a long time since I'd asked Sundar the "Decoder" questions about structure and decision-making, so I started there. You'll hear Sundar say he realized he needed to rethink how Google worked a few years ago in response to ChatGPT. And he made a lot of executive changes and big decisions to get the company in a more aggressive posture. Of course, we also talked about all of those Search changes and how it seems obvious that the future of Google Search is bringing things like the new intelligence Search box together with Google's new Gemini Spark agent platform so that searches can set off tasks, not just deliver results. That's exciting, but it seems likely to yet again change the dynamics of the open web. If you're a "Decoder" listener, you know that I coined the term Google Zero a few years ago. That's the idea that Google traffic to websites would fall to zero as the company answered more and more queries directly on the Search results page. That's gone from an idea that Sundar batted away in previous interviews to something that the entire media industry is grappling with. The CEOs of major publishers like Conde Nast are now publicly saying they're planning for a world of zero search traffic from now on. Google is also training its models on YouTube videos and changing YouTube search to summarize and index videos so they get dropped directly into the relevant parts. That's sure to cause some creator angst. So I asked Sundar if he's ready to fight the same battles with YouTubers as he currently is with publishers. Finally, I had to ask Sundar about Google DeepMind CEO Demis Hassabis ending the I/O keynote by saying that we are at the foothills of the singularity. It's no surprise that Sundar agrees with Demis, but his thoughts on the timeline to AGI are worth paying attention to. Like I said, this is one of my favorite episodes to do every year because Sundar is always game to actually take the questions and even look at Search results on my phone with me. I think you're really gonna like this year's conversation. Okay, Sundar Pichai, CEO of Alphabet and Google, here we go.
Sundar Pichai, you're the CEO of Alphabet and of Google, welcome back to "Decoder."
Well, it's great to be here. Nice to see you again, Nilay.
Yeah, this is one of my favorite yearly conversations. I think we've done it at I/O now almost five times.
Wow, I quite didn't realize it's been five times, but I enjoy it, thanks again.
Yeah, I wanna start with a little bit of a lightning round. I was thinking about this. We've talked a lot, we always get deep into the weeds of the web and search and big heady ideas, and I realized I have not asked you the "Decoder" questions in quite some time, and I was just looking back at our previous conversations and Google itself, you've made quite a lot of changes to Google. I think a number of your direct reports have changed over time, you've obviously restructured DeepMind, platforms and devices, and Android has been restructured itself. Tell me how Google is structured right now.
Okay, it is Google and Alphabet. You know, obviously we have Alphabet as well, but broadly I think about it as there are three main businesses in Google: Search, YouTube, Google Cloud. There are enormous platforms we run, which is Android, Chrome, and the whole area to do with it, and powering it all is all these important technology areas, which is AI and our infrastructure work, and then you have the functions to go with it. But at a high level, you can think of it as Search, YouTube, Google Cloud, and then our big computing platforms. Those are the main groups, and obviously powered with Google DeepMind and our infrastructure teams. So that's one simple way to get a mental model around it. And of course, we have other bets beyond that, Waymo being the most prominent of them all, but there are many, many other bets like Isomorphic Labs and so on.
Yeah, I wanna stay focused on the Google of it. I feel like we could do an entire hour on Alphabet and how that's structured and how that works, is a public company with many bets. But just to say focused on Google for one second, the knock on Google historically is this is a company that ships lots and lots of products, you cancel lots of products, there's not tons of focus. There's like thousands of names of different products that are overlapping in kinds of different ways. And where that comes from, at least in my view, is that you do have these big infrastructure bets. You have all these capabilities and the people running the businesses can use those capabilities to spin up products. And there's maybe not a lot of overlap or central planning on like, "All right, did we launch two of the same thing?" How do you resolve that tension? It does seem like Google has gotten a little more focused, but that is the company's culture, right? We're gonna make a lot of bets and see which ones work. How does that resolve for you?
Look, I think there's a lot of intent in what we do too. I think it's not an accident, you know, we have 13 products with a billion users each, and we've been committed to those products longer term. You know, you can go back and think about when Gmail launched, or Maps launched, or Google Docs launched, or Search launched, or Chrome launched, and like so we've been deep and consistent in many, many areas over a long period of time as well. I do think one way I've internalized in the AI moment is for the first time we have such a common infrastructure powering all of them with our Gemini models and the underlying AI infrastructure. So we are more able to intently, you know, with intent do things which cut across things, right? So Personal Intelligence is a great example of it. It's one effort, obviously users get a choice to turn it on in each of the products, but it's built with one common infrastructure so that it works consistently across your products. The underlying Gemini models itself is an example of it. So we are able to bring that model in the context of the products, like Ask Maps in the context of the Maps product. But a lot of the technology powering it, the voice stack, the model, the intelligence is all one work. So, which is why I think the AI moment offers us a new really new way to think about it. And not just across Google, across Alphabet too over time. I think that's what makes this moment so uniquely powerful is that you can invest so much in R&D and infrastructure and develop a technology, which then you can apply across all these areas. You know, obviously in a context in which they're useful for users, but the underlying technology platform is common. So there's a lot of intent that way and so on. You have to give room for innovation otherwise, so allowing room for innovation where teams on the margin are able to ship some new features, sometimes you later work to harmonize them. Take Notebook, NotebookLM, and Notebooks are now showing up in Gemini, right? And like, you know, it's effectively projects as Notebooks and you can create a Notebook in Gemini, you can go to NotebookLM, you'll see the same Notebooks, vice versa. So that's an example of where you innovate it first and then you are harmonizing later.
I was watching that keynote yesterday and I saw a lot of intent and confidence from Google. We have this core technology, we can express it in lots of ways. It's still essentially Googly, like there's lots of products, lots of Gemini words, I'm gonna figure them all out, I promise. I would contrast to, I don't know, three, four years ago when there was the ChatGPT moment, everyone worried about what Google would do, could OpenAI show up and take your market share and Search away? Between that and now, you have changed Google, right? You have restructured it. There are new people in leadership roles. Connect those dots for me. How did you think about, "Okay, I need to actually change how the company works," with the competitive moment you were in that got you here?
That's a great question. Look, I think for me, I always internalized that moment. It was tough to convey it outside, but we had set the company, you know, I pivoted the company to be AI first. We had all the ingredients, so in some ways I felt like the Overton window had changed. People were adopting these technologies faster than we had expected. And so to me it was a way to go and actually express ourself through our products, but I realized we had to organize ourselves for it. And going back to my earlier point, I realized we need a core models and a core infrastructure team to power everything we are doing across Google, so a lot of my initial energy was to go set that up. One AI team, we had world-class research teams in Brain and DeepMind, bringing that together as Google DeepMind, you know, which was harder than it sounds because it's like saying, "Go put Stanford and MIT together and create a department out of it or a university out of it," so I think doing that well. And then at that time I also set up with Amin Vahdat, who's our SVP of AI Infrastructure now, a centralized infrastructure team, which has paid great dividends. And then another evolution was realizing we need a Chief AI Architect to kind of architect this technology across Google, and Koray taking on that role as well. So those were important changes. We obviously made sure Search needed to move faster, so Search was split across many leaders. So pulling it under Elizabeth Reid with Nick Fox being responsible for the overall area, Josh Woodward coming to help with our Labs product and working on Gemini later driving innovation as well as obviously extraordinary leaders in the company, other leaders like Philipp Schindler who runs all our operations and so on. So it is stepping back and end-to-end thinking about the structure and make sure we are set up well for this moment where we need to move faster as a company, which meant we needed to make faster decisions. I set up these new product reviews once a week. These were, you know, they were AI product reviews, making sure we are intentful about how we apply this technology, where we apply them, and wanted to review everything firsthand that anything to do with AI, which we were shipping to users, went through that channel, and I spent time directly with whoever was working on it.
Yeah, we have a "Decoder" question I ask everybody is about decisions, you're describing a lot of big decisions, some of them uncomfortable as you change people around, how do you make decisions? What's your framework?
A big part of my framework is over time understanding that there are very, very few decisions which are really consequential, and most decisions aren't. So what matters much more is that you make the decision because that's what determines the velocity of an organization. And so the more you're able to make those decisions and keep the company moving forward, you're generally better off. Of course, there are a few decisions like combining and setting up Google DeepMind, you know, those are more consequential and you want to take your time deliberating and doing it, but a lot of decision making is about just making them. And so the more you're able to do that, you do develop over time some pattern matching and some intuition for you've seen a version of the problem before, and so I think it's good to rely on that and separate the signal from the noise so that the signal is that this is a really important decision and you want to really deliberate around it versus this is just it may look big, but it is more a normal course of action you need to take.
Yeah, looking around the industry, your peers in big tech have some of the wildest org chart ideas I've ever heard in my entire life. I think Meta wants to have 50 engineers report to a single manager with the power of agents. Jack Dorsey at Block wants all 6,000 people to report to him. Are you having similar thoughts that you should invent some of the craziest org charts with AI ever?
Look, I think leaders and people are incredibly important, and I think our company is, you know, depends on what the company, some companies have a much more narrower suite of products, and so different structure may work. When you're running something at the scale of like, take the scale of Google Cloud, right? I think it's important that there is a CEO in charge and we are serving all the top enterprises in the world at a scale, you know, and so how do you set up for that? So I think great leaders end up mattering a lot, like we have Thomas there. So I do think I think about it, but what I do think about it is how are we using AI more effectively? And we have seen the transition internally, particularly amongst our developers, where we have transitioned from using AI tools to assist coding to them, a portion of the engineers, working directing teams of agents effectively more and more. And so I think those are transitions underway, and I think that will flow beyond just engineering into the rest of the organization, it's already happening. Like even the work we are doing in Gemini Spark is to give that superpower to the hands of consumers, what you can do with these agentic workflows, et cetera. So I'm more focused on making sure we are actually deploying that capability in a native way and that it's working well because for us it's more than just making the company efficient because it's the products we provide to others, right? So I look at it with a very different lens. How we do it internally is what we are giving to users outside. We use Antigravity internally, right? That's what we are providing outside. So the agents and Antigravity is what our developers are using, and so that's what we are trying to put outside so it has that extra dimension to it.
The number one question "Decoder" listeners want me to start asking CEOs, I'll just ask it straightforwardly, how close is AI to replacing you as the CEO?
You know, it is today, you know, still I just think the CEO job is not that complicated, right? You know, it is not complicated. There's a big, there are aspects of it where I think it's gonna be very, very helpful in terms of decision-making. I joke around that, partially joke around, which is like I have to spend a lot of time allocating compute, and I'm like, "Well, that seems like the AI is gonna make more rational choices over time because I deal with a lot of appeals and emotions as part of working through a process like that." So I think look, everywhere what I see and which may be a bit different to how I think, I think done correctly, these tools are going to kind of allow us to operate at the next level in everything we are doing. Like it's not like you won't do what you were doing before, you will start from a higher foundation. I wasn't there when like, I don't know, spreadsheets rolled out to companies, right? And like it's almost I have to go think back, how did people do all this financial analysis before, right? And I'm sure it changed over a period of three to four years fundamentally and we got used to it. I think agents, et cetera is a version of it. It's not like you're not gonna plan birthday parties, it is just that what you, let's say you're planning a trip somewhere, maybe you're actually spending your time thinking about the actual things you want to do with your time versus chasing opening times and how to get tickets and so on. So I think it elevates everything to a different foundation is how I think about it.
Let me ask you about that and agents, some of those demos are fascinating. The idea that Search is gonna build custom software for everybody, that seems like an idea in software engineering, a first impression, right? The idea that the computer, you're gonna ask it a question and the response will be for it to make you software that helps you get to an answer. I'm fascinated by this idea, but that is fundamentally changing Search. And then you kind of look at Gemini Spark, which is your agent platform in the cloud, where you're at, you will say, "Go book me some tickets," and Spark might run around and book you some tickets or do some tasks for you, and then there's Antigravity, that agentic coding platform. Broadly every year there's like a new paradigm for AI, right? There was LLMs first and then maybe we're gonna chain some LLMs together, then there's reasoning and then now we're at agents. Is this the foundation or is there another paradigm shift to come?
I think it's a great question. You know, we are laying most of the building blocks in place, I think fundamentally being able to reason, use tools, and code are a lot of like, you know, having intelligence and reasoning, being able to plan, being able to look up things, use tools, and if you need as part of that to build something. So you are kind of laying all the primitives, and obviously Antigravity is for developers, but the Antigravity engine, the harness is built into a Gemini now, right? And Spark is just a mode of Gemini, over time it's a feature, we are positioning it, but it's just a tab within Gemini, and so you are bringing that agentic harness. Users don't need to think about, developers will understand it over time in Spark, they can code powerful things, but as users you may be building something, creating something, planning a trip, and all that is working behind the scenes. So I do think we are laying a lot of the primitives of what we need agents to work end to end, or more importantly, AI to work, you know, this long running vision of assistant we have all had and worked through myriad forms of it and failing to fully do it well, I think we are closer than ever before to deliver on that promise. We haven't delivered it yet. You know, but that's the journey, which I think is closer than ever before.
I look at all the products and they do seem like they should converge, right? You have the new intelligence Search box, and I definitely wanna talk about Search in more detail, but you look at that Search box and then you look at it's Canvas that makes you the apps, but you're planning a wedding and it'll just make you an app, you plan a trip or a wedding or something, and then you have Spark where it can go off and do things. And I looked at that and I was talking to people yesterday and it just seems obvious that that should be one product.
It will, so the agents, just like I gave the earlier Notebook example of like you're creating Notebooks, what are Notebooks? You're effectively putting all the context you want in one place and then working off it. It's folders as they've always existed for people. And Notebooks should be a consistent primitive across the Google products you use. I just view agents that way. It shouldn't matter. And so I do think when you're at the earliest stage of innovation, you create the capability. I think teams are experimenting with it. But for a user over time, if you fire off planning a trip, it should work across both places is how I would think about it. You're right in that.
There's something very important about Google Search, it is a source of truth for people for however many years, decades now. The, "Go Google it," and you'll get an answer and that answer is the same for you and me generally has been a very important idea, like it's I think a fixture in the culture. Maybe Google is the last company saying it will just tell you the truth out of all the companies out there. Okay, we're gonna infinitely personalize the Search box, we're gonna infinitely personalize the Search experience and we're all gonna get different answers to queries, we're all gonna maybe even look at different interfaces depending on what we're asking, what our personal context is, how much data Google has. Do you think about that profoundly? Like how much can you destabilize the last sort of common source of truth most people experience on the internet?
Look, I think there are factors well beyond our control, which is people today have a wider variety of sources than ever before, so I think people are getting content from so many different sources. But within the world of Google, I still think we deeply care about this being a source of knowledge and information. I think there are objective experiences and subjective experiences, right? What's the capital of USA? You know, it's not going to be custom created for anyone, right? These are objective things. Help me plan a nice trip to Montreal for a weekend. You know, naturally the answers don't need to be the same for everyone, right? So there is a continuum there. I do think the more, you know, so we deeply care about, you know, for certain categories of information, we do still anchor around authoritative information to present as much of an objective view as possible. And if it is health-related queries, we naturally tend to show more authoritative answers than if you're saying, you know, "What sweater should I go by?"
Can I show you a Search result?
A few years ago I showed you a Search result, I've been tracking this one for years.
I always love amongst the 10 trillion queries.
Yes, well, this one's a favorite. I think this is important, and I want to get into how consumers might be experiencing these products. So this is a search I just do all the time, for best Chromebook. I'll just show it to you, there it is. So it starts with an AI overview, it just very confidently tells you the answer, and then there's a bunch of sponsored boxes, and then the one that gets me is right below that, I believe the result is Reddit. And it has a top result in Reddit, and it's actually a different answer than the AI overview. And then there's like the Times which has a different answer and you kind of scroll this and you're like, "The AI overview is telling me one thing, the first organic result is like fairly down the page, and all of these are different answers." And I hear what you're saying about objective results and subject results, what laptop should I buy is somewhere in the middle of those things, right? And I'm just curious how you think that experience for consumers is today in AI mode and where you think it should go?
Look, I think I mean to be very clear in the world of AI or using AI mode, we are organizing giving context, but there are sources throughout, so you're still presenting organic content in a different way, right? So I mean there are links and sources you're giving too, but there is an opinion to go with it too, which is what you're talking about. I do think some of this will be iterative with users, right? I think one of the great things we find with Search is it's easy to measure user satisfaction. Over 25 years we've learned to measure user happiness, user satisfaction in a correlated way with improving the quality of the product, not for short term, so that's why we do these long-term studies, and if we get wrong or get any experience wrong, it shows in the metrics and we course correct. And we pride on the ability to track this over longer term, be it engagement, sessions, you know, returning to a topic, the number of bounce backs they do, so very, very sophisticated way of looking at it. I think in some areas like that, I think the experience will continue to evolve. You're right.
Do you think that experience is good today?
I think it's probably more opinionated than it should be for the particular query you showed me.
That's how that was my reaction as a user, right? So I think that's a scope for improvement is how I would say in a fast evolving space and, but I would expect that to happen in the product, right? Like my intuition there is, "Oh, that's way more opinionated." There is some chance that's personalized to you may be testing it in a way that you're uniquely personalizing, you are the reason that query might not be exactly representative, though I think because I know how you review all these things, like so there is some chance you're on the .0001% type.
Well, this is kind of why I'm asking about infinitely personalizable results, right? And I'm also asking if the experience is good because I would bet that most people experience AI in Google Search, like all the time, they have that experience or they kick to AI mode and there's the stuff you can measure about user satisfaction and then there's how the public feels about AI. And I think there's a pretty yawning gap in, "Hey, there's these user numbers going up and we're close to a billion users and the free products people are experiencing how good they might be," and then just the polling data, young people dislike AI is as objective as that gets, you can go ask them and they will tell you in measurable ways they dislike it. Eric Schmidt, the former CEO of Google, was booed at a college graduation speech he was giving, 7 in 10 Americans oppose data center construction. There's some gap between the product experiences people are having and how they feel about the technology. Do you think you can close that gap? Do you think these products are good enough?
