Today, I’m talking with Wassym Bensaid, the chief software officer at Rivian, and the co-CEO of Rivian’s platform joint venture with Volkswagen, which everyone just calls RV Tech.

That joint venture kicked off about a year and a half ago with a nearly $6 billion investment from Volkswagen. It effectively puts Wassym in charge of the operating system and electrical architecture for every future EV from Volkswagen and its associated brands, including familiar names like Audi, but also new companies like Scout.

There’s a lot of Decoder ideas in there — I really wanted to know how that joint venture works and how it’s structured to preserve Rivian’s unique software culture, which you’ll hear Wassym talk about as the core element of the whole thing. I also wanted to know where the lines were — what parts of Rivian’s software get to be just for Rivian, and which parts of the core technology would be shared across the smaller company and the behemoth that is Volkswagen Group. And, of course, I wanted to understand how Wassym navigated the tension between the two. You know, classic Decoder bait.

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It’s also a big moment for Rivian in general right now. The company is gearing up to deliver the more affordable Rivian R2, which is the first vehicle based on this new architecture, and the company also just shipped the AI-powered Rivian Assistant in its R1 vehicles. You’ll hear Wassym talk about Assistant as the beginning of a big bet for Rivian, as it tries to create a more agentic software platform in its cars. 

I actually got to spend some time with the Rivian Assistant in an R1S ahead of my conversation with Wassym, and I found it to be a fascinating experience — certainly powerful and engaging while at the same time frustrating in a lot of really interesting ways. So I had a lot of feature requests, bug reports, and questions about the future of AI and voice assistants in cars. 

So I asked Wassym about all of that, and also about his statements over the years that buttons in cars are just an anomaly and of course how he’s feeling about Apple CarPlay and Android Auto these days. You’ll hear it, but spoiler alert: Don’t get your hopes up.

This is a really fun episode of Decoder — we really get into the weeds on a lot of my favorite topics to talk about here on the show.

Okay: Wassym Bensaid, chief software officer of Rivian and co-CEO of RV Tech. Here we go.

Wassym Bensaid. You’re the chief software officer at Rivian. You’re also the co-CEO of a very important software joint venture between Rivian and Volkswagen, which is straightforwardly called Rivian and Volkswagen Group Technologies. Welcome to Decoder.

Thanks, Nilay. Super excited to be here.

I am very excited to talk to you. I have a lot to talk to you about. It occurred to me as we were doing the prep for this episode that you’re in charge of building a new kind of software for cars. But because of this joint venture that’s building a new kind of software company that’s building a new kind of software for cars, it is the most fractal Decoder I think we’ve ever had.

Awesome.

There’s a lot here. Let’s start with the organization. So, you’re the chief software officer at Rivian. I think a lot of people understand what that means. You’re the guy that they can yell at about CarPlay. Don’t worry, we’ll come to that. 

There’s also the new Rivian Assistant, which is an intelligent agent inside the car that I’ve been playing with and I want to ask you a lot of questions about. Then, there’s RV Tech, which is the joint venture with Volkswagen. You’re building a new zonal architecture for a bunch of cars. I believe the R2 is the first car that’s going to run that new architecture.

Correct.

How does that all work? What are the lines between RV Tech, where you’re the co-CEO,  and your role with Rivian, and what is the boundary between the software you build in the joint venture and the software you build at Rivian?

Before we dive into RV Tech and the joint venture, I think it’s really important to talk about the overall industry landscape. The automotive industry is going through a major disruption. The amount of software content in cars with technologies like electrification, connectivity, and autonomy is significantly increasing. That is creating a big divide between traditional OEMs and new tech-forward companies. 

Consumers now have much higher expectations in terms of the overall experience and convenience. Multiple OEMs have tried really hard to get software content, but it’s not easy. It requires a very different type of talent. In some cases, it requires complete cultural change because you’re not only developing software. You also need to adopt different methodologies and ways of doing things. You need to be much more agile. When you look at the industry, companies tried to do that in-house. Some of them tried to partner. Some of them tried to use Tier-1 suppliers.

A lot of recipes did not really work, and that was the genesis of the great partnership we have now with the Volkswagen Group, which has really taken the Rivian technology stack — taken the software, the electrical architecture, as well as the Rivian DNA and culture — and married it with the Volkswagen Group’s incredible scale. It truly provides a fantastic opportunity for both companies because now we have a solution that can not only underpin Rivian vehicles — as you mentioned, the R2 is the first car the joint venture is shipping — but then also, in the future, every single electric model in the VW Group. This is from your premium cars like Audi, to luxury cars with Porsche, Bentley, and Lamborghini, all the way to mass market cars.

That suddenly provides an opportunity of scale. Also, it exercises the technology in very different ways, and it puts us in a wonderful position so that we can build an architecture and operating system for the entire industry.

That question about the architecture and operating system feels very complicated. As you said, the industry is moving to software-defined vehicles, which is a great buzzword. Every car executive I talk to clearly has a different definition of what “software-defined vehicle” means. What is your definition of “software-defined vehicle”?

First of all, I hate that buzzword.

[Laughs] You brought it up.

Actually, I can’t find a better name. So, I admit that I’m also using the same for a lack of a better definition. 

But think about it this way. When you look at the older architecture in cars, it’s really an aggregation of multiple mechanical components. Underneath that, there are, in some cases, hundreds of electronic units, and each one of them is meant to do one thing. That’s actually mirroring the way those cars are built because they are developed using different Tier-1s and other suppliers. 

In that world, integrating an end-to-end vehicle feature requires a ton of coordination between many of those suppliers. It requires very long development cycles. That approach kind of worked in the past when the expectations of consumers were not super high in terms of those end-to-end features. But I think with the advancement of EVs and with the types of user experiences that Tesla, Rivian,, and the Chinese cars are offering now, that’s no longer an option for any car manufacturer.

I’ll give you a small example. When you walk to Rivian — and I know you’re currently testing a [Rivian R1] Gen 2 Quad —  let’s say you have your Apple digital key. You walk to the car and then the car recognizes you. Then, there’s a lighting sequence, and your entire profile is configured. Whether it’s the seats, the steering wheel, the infotainment system, the HVAC, everything is configured for you.

That sequence takes probably just 15 seconds, but doing that in the traditional world requires the coordination of more than 10 suppliers. You need to talk to the seat supplier. You need to talk to the door supplier. You need to talk to the HVAC supplier. You need to talk to the infotainment supplier. You need to talk to the security system. You need to talk to the cloud. You need to talk to the third party for the digital key. Just imagine that you want to slightly change that sequence for whatever reason. You have to go through another cycle of changes. 

This is why that old model really doesn’t work anymore. Cars are now integrated systems with what we call “zonal computers.” We think about them as general-purpose, powerful compute that we place in the middle of the car, and they become the centralized brain of those different functions. The more software you can move on those zonals, the more it can provide control over those end-to-end features for the customers.

So, this is the pitch that every pure-play car startup has been making for a long time, right? The way that the OEMs built cars was done, and you shouldn’t have 1,200 ECUs from 1,200 different suppliers. That was fine for gas cars that were pretty dumb, where the only computer was like my old Pioneer head unit that had a fold-out screen. By the way, I love that head unit, if you could bring that back. I have fond teenage memories of my dumb old car with that head unit. 

Now, the whole car is a computer, and you expect a lot of things to happen but that integration is too hard. What I would say broadly is that legacy OEMs have known this for years. They have been on their own journey to solve this problem, to cut down on the number of ECUs.

Ford CEO Jim Farley was on the show five years ago saying things like, “Too many ECUs; we’re going to cut it down.” Volkswagen, in particular, had its own giant project to do this that failed. I think there’s enough distance. You’re a year and a half into the new joint venture, and we can say Volkswagen’s CARIAD failed. 

Why do you think the new joint venture and the infusion of Rivian culture is going to be successful when Volkswagen’s attempt to do it on its own did not net any positive results?

You’re getting me in trouble, Nilay.

That’s what I do.

What I personally appreciate about the Volkswagen Group’s decision is the recognition that developing what are called software-defined vehicles requires a complete, clean-sheet approach. You cannot approach it with Band-Aids and by having some level of software content in the car. As you said, the Volkswagen Group has tried. Actually, it has tried twice. But deep inside, there are two things that are really important here. One is that you need the right talent who are able to develop true software. Not abstracted functions like what the automotive industry is using — you have probably heard about AUTOSAR — but a true, hard-coded operating system. 

Then, you also need a deep cultural change with a very different way of approaching the car and its overall development. The traditional model said that cars were defined many, many years in advance. People claim they know about software features four or five years in advance, and then it’s a very fixed waterfall approach. The way we design cars at Rivian is that we actually design the car around the electrical architecture, the software, and the adaptability of the software. So, software and technology have been at the table since very early on. It actually impacts the overall packaging of the car. We really use that platform and that operating system mindset so that we have a car that can evolve over time and get better and better for our customers. 

Such changes are so deep that to do it well, you either need to have the right partner or you go with a clean-sheet approach. I think the Volkswagen Group has made the right decision to partner with Rivian in this case and to not only embrace the technology that we built from the ground up but to also embrace the culture, the approach, and the DNA of Rivian as a company.

How is the joint venture structured? I know you have a co-CEO, Carsten Helbing, who’s the Volkswagen CTO. So, you’re the two co-CEOs. How is it structured underneath that?

There’s a technical team underneath that: software engineering and electrical engineering. The technical team reports to me, and Carsten is my partner in crime. He takes care of the operations, and he’s also the main interface with the Volkswagen Group. There’s a ton of complexity in terms of managing different requirements and different inputs from the brands. He’s really doing all that arbitration so that we continue pushing towards a platform approach and reduce the overall complexity of the portfolio we’re supporting with the VW Group.

One of the questions I have here is that you describe it as an operating system. That seems like a good framework. People understand what operating systems are. I realize car operating systems are vastly more complex than people give them credit for, but it’s an operating system.

Then, there are the expressions of the operating system. I know that when our audience thinks of the software in the car, they think of the infotainment screen and that’s it. That’s just one expression, right? The user interface that Rivian is running… There are going to be other expressions for Volkswagen, for Scout, and I presume for Lamborghini. They’ll all be running the same core operating system expressed in different ways.

That is a real push-and-pull dynamic. Where do the features live? Who gets to build which feature? What are the core capabilities of the operating system and the platform versus what Lamborghini wants that it doesn’t want Rivian to have? How do you make those decisions?

First of all, I think it’s important to clarify the role of the joint venture. So, we’re responsible for the underlying electrical architecture and the operating system. When you look at a modern car today, pretty much every single interaction you have with the car is powered by software. You don’t realize it in a lot of cases. People tend to associate software with infotainment and with what they see on the UI and the screen, but there’s software everywhere in the car. I mean, there’s the way the car navigates, the way the car drives, the way the car saves energy, the way the car does cabin comfort. All of that is actually managed through software. 

So, the way to think about this is that our role is to, first of all, build an electrical architecture with as few computers as possible in the car so that we simplify the overall packaging and the overall bill of materials. This is the brains of the system. On top of that, we develop software that the different brands can use so that they express their own identities. Think about it as us doing  80 to 90 percent of the hard work. Then, we provide customization hooks so that an Audi drives like an Audi and a Lamborghini has a different UI than a Rivian. But what’s happening under the hood, what’s happening behind the scenes, is based on the same platform.

When you think about that underlying electrical architecture and the zonal computers — you say we’re going to cut down the number of computers but have fewer and more powerful computers — one of the things that seems like an obvious opportunity for Rivian that might be way more complicated for Volkswagen is that you have a big battery that can just power those computers all the time. They can be online, they can be functional, they can be available. Volkswagen also makes gas cars and hybrids. There’s some pendulum swinging in the industry between electrics and gas vehicles, particularly here in the United States. Is that a challenge or are you just not thinking about their gas cars at all?

The joint venture’s scope, for the time being, is really about powering all the electric vehicles. This is the agreement we have with Volkswagen. One of the main reasons I joined Rivian is for the mission. I think the joint venture provides us with an extraordinary opportunity to accelerate electrification into many more cars around the world.

One of the first products that we’re building with Volkswagen Group is the ID.1, which is taking our technology to a mass-market vehicle. This is a car that will sell for less than $25,000, and it really opens the technology and that rich feature set to many more consumers around the world. Now, can the technology be used for non-EVs? Can it be used for hybrids or ICE vehicles? Obviously, the answer is yes, but for the time being, that is not the priority of the joint venture.

How big is RV Tech? How many people?

We’re about 1,500 people.

How is that split between Rivian folks and Volkswagen folks? Is it employees from both companies, or are they employees of RV Tech?

They are employees of RV Tech. Actually, we started with about 800 or 900 developers coming from Rivian, and then we had about 50 colleagues who joined us from the Volkswagen Group. The rest are developers and engineers that we’ve hired in the past 18 months. So, everybody’s RV Tech.

The reason I ask is that you mentioned at the very beginning that it’s an infusion of Rivian culture, but now they’re not Rivian employees. But at the same time, you are also the chief software officer of Rivian. How does that culture persist if the thing is its own entity, if it’s not as directly connected to Rivian, or if they’re not Rivian employees?

 The way I define my job and my number one priority is to help the company grow and build on our two main assets, which are technology and our people and culture. With technology, I think we have a wonderful opportunity now to take that tech into many more cars across a wide range of the portfolio. Then there’s trends and culture. My daily obsession is to really make sure that we continue to have the same DNA: agility, being nimble, prioritizing action, quick decision-making, and iterating really fast so that we are at the forefront of innovation.

One of the other reasons I ask is that there are Rivian decisions that Volkswagen maybe won’t make. Rivian runs on Unreal Engine for the graphics in the infotainment. It’s really fun. I’m not sure that every single Volkswagen is going to run on Unreal Engine.

At least as I understand it, that’s a decision the different brands can make for themselves. But you’re the chief software officer at Rivian. You’re like, “We need better support for the Unreal Engine interface.” Maybe the platform doesn’t want that, and you wear that hat, too. How do you reconcile those tensions? Do Rivian’s needs always win?

What wins is how we can build the software in a way that allows for different expressions. I think in this case, Rivian’s interface will show up through Unreal Engine, but then we need to have hooks in our frameworks so that — and I know you will ask me this question — Volkswagen cars can have CarPlay. The team will develop that even though Rivian will not adopt CarPlay. It’s really about creating those different hooks in the operating system so that we allow for different ways to express the user interface.

This is so fascinating. Like I said, this is such a fractal episode of Decoder. It strikes me, just talking to you about this, that there aren’t a lot of models in an industry as big as the auto industry like this, where the big player is letting the smaller company define the culture, the opportunity, and the architecture, which will define its future roadmap. What examples have you looked at that are similar, where you can say, “That’s successful. We should build the model based on this and operate like this?” What versions of this have failed that you’ve looked at where you’re like, “I want to avoid those mistakes?”

I think there are many more failure stories than success stories when people look at joint ventures. This has been one of our guiding principles. We spent a lot of time discussing with VW leadership before we engaged in such a partnership. What made [Rivian CEO] RJ [Scaringe] and myself lean heavily into this partnership is, one, the opportunity and, two, the honest and constructive partnership from Volkswagen Group leadership. 

First of all, we are talking about putting Rivian technology into the second-largest OEM in the world. This is, by far, the biggest licensing deal in the automotive industry. As RJ and I started the discussions with [VW CEO] Oliver Blume, his number one priority was that they needed to keep the Rivian way of doing things. We realized that we are not only bringing software IP and electronics IP but also a different process. We are bringing a different culture, and the VW Group needed that change from the inside.

Obviously, in some cases there has been daily tension. There are cases over the past 18 months where, as you mentioned, one brand might request a different requirement than another brand. But what really helped us to continue is that support from the highest levels of Volkswagen Group leadership to help drive that transformation and cultural change.

Let me ask you the other Decoder question, and then I want to turn to the software itself. I ask everybody this question. We’ve talked about it a little bit. How do you make decisions? What’s your framework for making decisions?

So obviously, my job every day is making decisions, but there are a number of guidelines that I try to apply. In terms of coaching with my team, I try to push decisions to the lowest levels of the organization as much as possible. One of the anti-patterns that I see with a bunch of companies is them trying to bubble up decisions with the highest levels of executives, and that tends to create a culture where things are slow and employees don’t feel really empowered. 

Now, in cases where I personally have to make the decision, there are a few guidelines to the team: never come to me with one option, show that you went through an analysis, have multiple options, and then make a recommendation. I want a culture where I empower my team to have a forceful proposal and then come up with recommendations themselves.

The rule that I use to determine how much time I should spend on a decision is about whether it’s a one-way door decision or a two-way door decision. If it’s a two-way door decision, then I don’t need to spend that much time on it. It doesn’t really need a hard framework. We don’t need to go to extremes where we collect tons and tons of data so that we get to a decision. In some cases, I just use my gut. I’m a product builder at heart. I know that with some of the decisions, even if the data is against me, I should go with my feeling. In some cases I’m wrong, and I’m the first to recognize that. 

Now, if it’s a one-way door decision, then that’s a different process that requires much more preparation and much more data, and then it requires arbitration for how we do things.

Give me an example in this context of a one-way door decision and a two-way door decision at RV Tech. 

There’s multiple. I think one of them will probably lead to the next topic of discussion, which is our overall approach around AI. We had a ton of debates internally about whether we should just use a third-party AI solution or develop our own. There was a ton of tension because you look at the advancements in the AI world, and you would think that this is a hard problem to solve with everything that’s happening.

Now, it was really clear for me, given the opportunity and how transformative this is for the entire user experience, that we needed to own our destiny in terms of having a platform that allows us choice, that allows us to change foundation models as we wish and own the integration layer that allows us to power the entire car operating system.

So, this is Rivian Assistant. I’ve been playing with it for a few days now.

What do you think?

I had some searching conversations with it, just to push the boundary of what it can do. It’s super interesting to have a car where even within the interface, it does the wavy line on the main screen. It’s very much that the car is running this assistant, not an overlay. You can tell that the assistant can go and address lots of parts of the car, and then there are places where it can’t or it won’t. 

Actually, I think one of the most interesting things about it is that it won’t tell you why it can’t do things. It is insistent that it won’t tell you why it can’t do things. Don’t worry, I have very specific questions. But it strikes me that this is a natural evolution of, “Okay, the whole car is run by a finite set of computers, and that means our assistant can just run around and talk to those computers and the functions that those computers control.” I have a Cadillac EV. If you try to glue an assistant onto that, it has to go talk to its ECUs. It’s just very obvious that something else is happening with Google Assistant in that car. That’s the opportunity. The assistant can talk to the whole car. Then there are places where it just can’t for some reason. 

I’ll give you one example. It struck me as very odd. I was driving in the rain, and I said, “Hey, turn on the back window wiper,” and it just won’t. I thought, “Is that a safety reason? Is that because you don’t know how to do it? You’re lost in the zonal architecture?” I asked it, and it said, “I can’t tell you why I can’t do these things, but here’s where the button is,” which is really interesting for a car assistant to do. I’m not going to do it for you, but the button is on the stalk. Push the button. How do you make those decisions in the context of an assistant to figure out what it can and cannot do?

So, there’s a lot of things here. First of all, I think you described it really, really well. Our philosophy for the Rivian Assistant was to not just put in a chatbot and then slap it on top of the UI. It’s also about developing what will become the connective tissue that enables our users to interact with pretty much every single feature in the car and, even more than that, to bring their own personal digital ecosystem in the car through agentic integration.

Now, to your question about what it can do and cannot do, it’s obviously possible for us to control the wiper. I’m sure that you have seen that it can do way more. It can change your drive modes. It can change your ride height.

I could raise and lower the car at 55 miles per hour with the air suspension, which was cool and like the slowest low-rider experience you could possibly have, and then I couldn’t turn on the wiper. So, what is the split there?

Honestly, that’s one of my favorite features. The way I like to interact with it is that I don’t tell it to change the ride height. I tell it, “Okay, give me a drive mode with more pep,” and then it does it and changes to sport mode. I mean, this is really the magic of that true conversational experience.

Now, the reason it does not control the wiper is by design. We actually block a number of features that are safety-related. Cars are homologated and regulated. So, things related to wipers, windshield controls, highway assistance are regulated functions, which we block for safety reasons today through our framework. Safety is one of the core tenets in how we develop the entire experience.

The other one that struck me is that your cars have rear-seat sensors. We have kids, so every time I get out of my car, it reminds me there might be a kid in the back seat because it has sensed the weight. I think this is one of the funniest sensors any car can have because the car seat is always in the back seat. So, it’s always reminding me that the kid might be in the car.

So I asked, “Is anyone in the back seat?” Maybe this is just a bug, but it said, “I’ll find out,” and then it said, “I can’t access that sensor.” I said, “What sensor are you trying to access?” And it refused. I probably had a five-minute argument with your assistant about why it wouldn’t tell me what sensor it was trying to access.

The reason I’m asking this is not because it’s a bug or I really needed to know if anyone was in the car seat at the time. I’m just curious. You think about building the assistant that can access all of the sensors and the architecture and how that might work and how we might interact with cars. There’s a moment where you realize maybe it’s for safety reasons or maybe it just won’t work right now with the version you have because the LLM has to go talk to another computer and that computer has to give it permission. I don’t know if anyone in any part of the tech industry has figured out exactly how that should work, and I’m just wondering what your point of view is.

I think in this specific case, it should have actually told you what’s in the back seat. So, that’s a bug. That’s on me.

No, it was like, “I’m not telling you what sensor I’m trying to use.” I was like, “Why?” and it was like, “I’m not going to tell you what sensor I’m trying to get to.”

Yeah, that one is on me. I think the beauty here is that we have the team in-house. We’ll be able to calibrate that answer, and then we’ll fix it. Don’t worry. Nilay, I’ll send you an OTA next time when that’s fixed. 

That’s very good. Every time we get a car executive on the show, I just complain about the experiences I have. It’s perfect. 

But every assistant at every level is running into that specific barrier concerning how you talk to the computer and what permission does that other computer give you. Every assistant at every level is running into that specific barrier, and I’m just curious what you think the answer is.

Think about our architecture this way. The assistant has deep integration into the entire vehicle operating system. So, in theory, unless we have a bug like the one that you experienced, , you should be able to do everything with the integrations that we have built.

The only functions that are not allowed are functions that are safety-related, obviously because of the homologation reasons. But also there are functions where we are not comfortable with the level of reliability we can get from the LLMs to expose them to the end users. But that’s really the beauty of the internal, in-house orchestration layer that we have built where we have a ton of guardrails that allow us to control which functions are exposed by the assistant or not.

All right. You mentioned that I was going to get you in trouble. I’m going to get you in trouble again. In 2024, you said using buttons in a car is an anomaly of modern design. People love buttons in their cars, so you got in trouble for saying that, but the thing you said was that voice should be the future. This is the first gesture at voice being the future. Is it good enough? Because we’re right on the cusp of whether these things are actually good enough to build the kinds of products people want.

I think we are on the cusp of something really big. When you think about it, you’re in a car, you’re driving, you’re focused on the road. So, in theory, the primary interface with which you should be interacting with the car is actually voice. The only reason that drivers and consumers do not interact with the car through voice is that, to put it really bluntly, the technology has been broken. That’s really the beauty of what we have now with the technology disruption coming with foundational models. 

The foundational models are providing us this wonderful opportunity to truly have a conversational experience where drivers can interact with the car in human language. I don’t need to tell the car, “Open the frunk.” I can say, “Open the front trunk.” Actually, I can say, “I have a bag in front of the car,” and it will actually open the frunk. I think that completely changes the way you interact with the car.

On top of that, we now have the opportunity with all the agentic framework to truly give people their time back in the car. I hope you tried our Google Calendar agentic integration. You can imagine how the experience will be in the future where you’re driving and can perform operations on your calendar. You should be able to perform operations on your email. In the future with the agent-to-agent integration, you can actually interact with many more apps from your own digital ecosystem.

Can I ask you about the word agentic in this context? To just describe it quickly for people, the way the Google Calendar integration works with Rivian Assistant is that it shows you a QR code. You connect your Google Calendar to it and then Rivian Assistant can read your calendar, add events, remove events, and do other calendar stuff. 

I’m curious how that’s agentic and how it’s built such that the word agentic is meaningful because I’ve had like 500 apps over the past 10 years that can do Google Calendar stuff through the standard API. So, how is it agentic? Is it powered by MCP? Is it something else? Why build it that way versus doing a bunch of API integrations?

I mean, you can build it with an API integration. I think the advantage of an agentic integration is that you can share the context, and then you can perform multiple integrations within the car. In this case, it is based on an MCP integration. 

You can imagine that in the future, instead of having that mono access to every single app on your car — or honestly, even on your smartphone — you can start aggregating and connecting many of those apps through the agentic framework and have them present a unified user experience. 

This is how we’re able to connect the navigation to Google Calendar, for example. I can go to the assistant now and say, “I want to plan a trip from San Francisco to San Diego, and I want to have two charging stops. I want them to be close to an Italian restaurant. I love Italian food.” The assistant would go and play that, and then I’ll say, “Okay, print the summary, add it to my calendar, and then send it as a text to my wife.”

When you have a behind-the-scenes agentic framework, this type of integration can really allow many more capabilities.  This is where agentic can be utilized even further. You can start going into more autonomous functions. Let’s say you have an invitation in the calendar with XYZ details. You can start having reminders that say, “Do you want to go to this place?” “You’re actually really late to your meeting. Do you want me to start preconditioning your car?” So, that’s the beauty of bringing in the depth of that agentic integration.

I think I understand that. Rivian Assistant is in the car. It can access a bunch of apps and services you have. You can take actions across them. You’ve collected a lot of data in one place. 

This brings me to a very deep existential question I have whenever anyone talks about ambient computing this way: Where does the logic live? The idea that you’re going to have that interaction in your car and not at your laptop or on your phone seems like a big jump to me. It was the same way when the smart speaker companies would be like, “You’re going to talk to your thermostat,” and would I think, “Why?” I’m going to talk to my phone. I don’t feel the need to talk to my thermostat in this way.

Do you think people are going to do that in the car, or are you going to bring your assistant to the Rivian app on a phone? Can you compete with Apple’s Siri and Google Assistant in that way? How is that all going to work?

Actually, the way I think about it is that it will be both. This is the big difference between the old world where we had unique applications and the new world where we have agentic integrations. 

I think about Rivian Assistant as an agent orchestrator that has privileges because it can deeply integrate with the vehicle controls and the vehicle operating system. It understands safety. It understands which things to do and which things not to do. Nobody else can develop that better than us because we develop the entire vehicle software. But at the same time, it has interfaces and connections to other agents. 

This is just the beginning. In the future, you can probably bring your own favorite assistant and chatbot to the car, and then it can share context with Rivian Assistant. I mean, these are the possibilities that this new world and this new type of integration are allowing us to do.

Is Rivian Assistant the kind of thing that is possible because of the RV Tech software stack? Is it possible that we’ll see Rivian Assistant or something just like it in Volkswagens as well, or is this special to Rivian?

This is special to Rivian. This is an AI stack that is developed uniquely for Rivian. This is Rivian’s brand priority as we see cars becoming more and more AI-defined. But we’re in discussions so that we can have similar technologies for the Volkswagen Group.

Rivian cars famously use LTE. When I first got in this car, I saw the LTE indicator, and I thought, “Oh, something must be wrong.” I drove around, and then I realized, “Oh, it’s just LTE.” Are there any latency concerns with that, especially with voice and going out in the world and doing whatever inference you need to do?

[Laughs] So, two things, Nilay. One, we need to get you an R2. The R2 has 5G.

There you go.

It’s coming soon, and it’s amazing. And two, I think you really touched on one of the architecture considerations for the technology, which is that when you look at vehicles like the Rivian R1 today, most of the interactions will happen with the cloud. So, as you say, it’s connectivity dependent. so they will work best when there’s strong connectivity with the external world. Now, there’s a number of interactions that happen locally with the car. If you tell the car, “I am cold,” that interaction is being managed by a small language model that sits directly on the edge.

The beauty of what will happen next as we get to the R2 is not only the 5G but also edge AI will be way more powerful and capable. 

Just to be clear for the audience, when you say “edge,” you mean local, right? It’s running locally.

Yeah, local, meaning that the local computer on the R2 will have up to 200 sparse TOPS (trillions of operations per second) of compute dedicated to AI. I know this sounds extremely technical, but think about it as more capable than some of the self-driving platforms today. It’s more capable than the AI compute that you have in your smartphone.

All of that will be available locally in the R2 car, which is coming soon. That allows it, as you mentioned, to not face these connectivity limitations and issues and to get to much lower latency because a lot of the processing will happen directly on the embedded system so you can get a conversational experience that’s pretty much instantaneous.

Can I just ask you a very in-the-weeds question? We’re talking about putting compute in the car. We’re going to do some amount of local inference in the car. GPUs are expensive. RAM is expensive. How much of the bill of materials is RJ giving you to do all this in the car versus, I don’t know, bigger motors or bigger batteries? How much of the range can you pull off to do local inference in the car? This is the trade-off you’re talking about.

This is what I love about RJ. What has always attracted me to RJ is that he thinks about big things in the long-term. He knows, in this case, that the world is moving to AI. This is why decision-making from a bill-of-material standpoint is a very hard process with a ton of trade-offs all the time. You can imagine the tension between people wanting to push for a better exterior part, people wanting to push for a better interior part, and people wanting better technology. Then, we have what we call the”differentiation budget” in the car. 

For RJ, there was absolutely no debate on whether we would equip the car with higher inference compute and more memory because this is really the future. It’s an opportunity for us to completely reshape the way people interact with their cars. To be honest, it solves itself in the long run from a unit economic standpoint because as we do more and more interactions locally in the car, we avoid the back and forth with the cloud. So, we avoid the connectivity costs, and then we also don’t have to pay for the cloud inference costs. So, in the long run, it’s actually economically positive.

That’s not just a spreadsheet you made up to win an argument that actually models out?

[Laughs] Kind of.

The reason I ask it is because my next question was about inference costs. They’re going up. There are rate limits with all the big providers. What model are you using right now? What are the frontier models you’re using right now?

The architecture that we have built is not actually model dependent. One of the architecture’s foundations allows us to interact and plug-and-play with different foundational models. Similarly, it can use different modalities in how users can input their requests, whether it’s voice or vision. It can use text if we want to enable that.

When it comes to the models themselves, we currently use a combination of internal models for everything that runs locally on the edge and models from Google. We have a partnership with Google. Things are going really well in terms of deep access to advanced Gemini models as well as the grounding of results also powered by Google.

This is another question I asked Rivian Assistant: what are the top five headlines on The Verge? I just wanted to see if this thing browses the web. It returned some results that I think are 24 or 48 hours old. These were the top five headlines from yesterday.

Does this thing have a web browser in the background, or is it just pulling from a Google data corpus? How does that work?

In theory, it should in theory connect in real-time. This is where the grounding with Google results comes into the picture. It should give you the latest headlines. So, if it didn’t, then that’s another one on me.

Well, I was just curious. Lots of people are having this experience now where the data in the model is old and there’s some cutoff, and I was just trying to find the cutoff. Then, I had a long searching conversation with it. We need to buy a new air conditioner, and I was just asking it to do math about air conditioner efficiency. It’s very boring, but this is what I talked to your car about for a while. It occurred to me that I was making it think very hard. I am wasting more energy asking how efficient an air conditioner I should buy. This is not a good ratio of energy spent to energy saved over there.

How does that work? You have to pay a monthly fee for the connectivity package to access Rivian Assistant, but then I might burn way more tokens than that fee could ever pay for. How does that math work out?

It really depends.  In these cases, there are all sorts of what we call “rate-limiting” techniques that we can apply. If we have seen, like in your case, that you’re spending 20 hours discussing with the assistant, then we may do something behind the scenes.

It’s similar in the way we can configure the models. Given the types of interactions that you have in the car, you would not be interacting with the latest and greatest, say, Claude Opus 4.7 models so you’ll burn a lot of tokens. A lot of it also depends on aggregation across users in terms of the types of requests, as well as the arbitration we do between the edge and the cloud. As I mentioned, the more we move to edge and local compute, the better it is for us in terms of overall inference costs.

So, let me just ask you this question again. Now that you’ve shipped this software, people are using it. You’re getting extremely detailed feedback from me. Do you still think having buttons in the car is an anomaly?

I deeply believe that voice has the chance to be the primary interface in the car. I also think that buttons can exist, but they shouldn’t be the primary way with which you interact with the car. I think there’s more that is possible with voice since you can do more than one single function.

You don’t have to fiddle with so many functions. You don’t have to go deep into the touchscreen to look into specific features. A great voice experience can elevate all of that, allow users to talk to the car as a human would and really take the overall experience to the next level.

Are we going to get the HVAC buttons back in any future Rivians? That’s really what I’m asking here.

Actually, with the R2, we have a great way to add tactile feedback for HVAC.

Oh, the big paddles on the wheel?

Yeah. They’re really awesome.

That’s a good pivot, but I’m asking, are we going to get the fan speed button back in the center stack?

Not in the center stack, but we have the same thing on the Haptic Halo Wheels. It’s a great compromise.

You knew it was coming. I have to ask you about CarPlay here. It strikes me as you imagine this future where the car is connected to your calendar and it’s connected to all this context. It has autonomy, which is something you’re also working on. You get in the car, and it knows it’s time to go to work. You just say, “Let’s go,” and the car takes off driving.

This is when you would use a vast number of applications, right? This might be when you have to focus to push the buttons again. I’ll just make that argument. But this is when you would want a whole number of apps. I hear from our readers every time I talk to a car executive that, “The reason I want CarPlay is because there’s 5,000 apps on my phone and no car OEM is ever going to support them in the built-in infotainment.”

This is when you would say, “Okay, project your phone to the center stack. The car’s driving itself. Have at it. Phone projection all day.” Do you think the tide is turning, or are you still absolutely committed to not having CarPlay in Rivian vehicles?

First of all, it’s really important to go through the philosophy of how we see software in the car and the user interface. The challenge with screen mirroring solutions is that they take over every single pixel in the car, and that’s not the way we see ourselves interacting with our users. You drove our car four years ago, and you drove another car over the past few days. I hope you’ve seen how much has changed in the car. It’s truly been by bringing in end-to-end features, not only changing the user interface but having your navigation know exactly about your drive mode, know exactly about your efficiency. 

Offering that level of convenience is what is really resonating with a lot of our customers. If I look at our own internal statistics from five years ago when we first shipped the R1T and the R1S, the number one request from customers was CarPlay. We did all sorts of surveys with customers at the time, and more than 70 percent of customers were requesting CarPlay. In the recent survey, that number is less than 25 percent because with the level of features that we have shipped to customers, level of end-to-end integration, and the level of convenience that we are bringing, CarPlay or Android Auto is no longer the topic of discussion.

What we’re seeing right now with the advancement of AI technologies is just another reason why I deeply believe that RJ and Rivian made the right choice by investing into our own technology and software. Cars are moving from, as you said, the buzzword “software-defined” to “AI-defined.” The possibilities now for such deep AI integration in the car make the entire CarPlay debate completely obsolete.

I really believe that the way you interact with apps — which are mono-threaded with single buttons or single icons — will be completely reshaped into a world where an agentic integration presents itself as a wholesome user experience.

I buy that in the big picture, but give me an example of that. I’ll put up an idea that I get from our readers all the time for you to react to. There are tons of little apps. They’re basically media-playing apps on phones, and it’s trivial to push the button for the CarPlay app.

The one that I always think about is an email from a reader who said, “I have a Bible app that is never going to be built into anyone’s infotainment system. It’s made by a small developer and I love it, and that’s why I need CarPlay. I’m always going to buy a car with CarPlay because of it.”

That is about as small of an edge case as you get, but this one customer is going to pick a car based on it. Are you going to make that developer build an agentic AI integration into the Rivian Assistant, or are you just going to lose that customer to CarPlay?

I mean, this is the beauty of the technology disruption in which we live today. The answer in that case does not necessarily need to be, “We will build an agentic integration for that particular app.” It can absolutely be if it is, say, Spotify or Apple Music.

But if it’s a small app, the answer could be that we have an integration for your favorite voice assistant in the car, and then you can ask the voice assistant to play that particular app through Bluetooth audio. That is possible as we open up the framework and allow more integrations to bring your own digital ecosystem to the car.

We’ll use Google because Gemini is more present on an Android phone than Siri is currently on an iPhone. It’s also your partner. You’re saying you can talk to Rivian Assistant and it knows your Google account and Android phone, it’s going to go talk to Gemini, and Gemini is going to go operate your phone and stream Bluetooth audio to Rivian Assistant.

In the future, all of that is possible.

Is that better or worse than phone projection? This is a different kind of loop than just saying, “Put the interface here and let the user do it.”

It could be possible through phone projection. I think the challenge with phone projection is that… First of all, as you’re driving, you’ll have to go through your phone. In some cases, you’ll have to press multiple buttons so you can get to the app menu. The other thing is that it takes over the entire screen, and that is a degradation of the experience.

Is the alternative solution available right now? No, but I think the beauty of this wave of technology is that we finally have the building blocks to really redefine those types of interactions. We can allow hooks now into your personal device through a different interaction rather than truly integrating the app end-to-end  the car itself or taking over the entire screen. There’s a third path now that is possible.

Obviously I think it might be easier with Google. Again, it’s your partner, but where would that connection to Google Assistant happen? I don’t think I’m holding up my Android phone to the speaker and letting the assistants talk to each other out loud. Although that would be fun. It would be deeply hilarious to hear the two assistants just have a conversation like, “Can you please play the music app for me?” 

Does that happen in the cloud? Does it happen locally? Where does that integration point between assistants happen?

Think about it as the assistant in the car knowing how to talk to your Gemini or your personal assistant. In that case, your personal assistant will be controlling your phone.

The reason I’m asking this in this way is because at some point, you have one main assistant, all the other things are agents it can talk to, and then maybe no one talks to Rivian Assistant again. You pull that thread all the way and Gemini just does everything for you all the time. Is that a danger, or are we just nowhere close to even having to worry about that?

Honestly, we don’t worry about that because we know the opportunity that we have, and we know the breadth of capabilities that we can offer. No other assistant will be able to know as much as Rivian Assistant about the car controls. None.

Similarly, the fact that we have the surface of integration sitting in our own operating system enables a ton of opportunities that you simply cannot do with your phone or by calling another assistant. Imagine that you’re driving, and in the near future, we enable the technology to have agentic integration with your favorite food delivery. The car knows exactly when you will be home. You’ll say, “Order my favorite sandwich from XYZ shop.” Your account is already configured. Then, the assistant will pick the destination and get you to your favorite restaurant. All of that is integrated. You just need to do it through a voice command. 

Those types of experiences — where things become so seamless and so easy as if you’re talking to a human, where it connects the dots across multiple surfaces of your digital ecosystem — would only be possible through such integrations.

Wassym, we’re out of time here. As you can tell, I can obviously talk to you about this forever. I don’t think anyone has figured out how all this works, and it seems like you’re making some big decisions. So, you’re going to have to come back when you’ve learned how this goes after this is shipped to all of your customers and certainly when the R2 is out.

There is one question that I have to ask every single Rivian person that I encounter. It is very important to me. When is the R3X coming out?

It’s here. Do you see it? [Laughs]

When can I get one?

By the way, it’s my favorite car. I ask RJ that question all the time. Now, you talked about decisions. You talked about trade-offs. Us delivering the R2 before the R3X is, as you can imagine, a big decision. It’s also a hard decision because in our hearts, we all deeply want to have the R3X as soon as possible.

We also know that the R2 has the best ingredients to be a wildly successful car. The US needs another great alternative SUV for families, and this is what the R2 will bring. As we ship the R2, as we scale our volume as a company, we will earn the right to bring fantastic and emotional cars like the R3X.

I know that that is, in one way, the right answer. I’m just saying for me personally, come on, just send me one. It’ll be great.

That’s the hard thing. 

I’ll give you more feedback just like this. I will break your R3X prototype in 10,000 different ways. You’ll get the bug reports. It’ll be great. Tell RJ I made the offer.

Awesome. I’ll get one at the same time as you Nilay.

Sounds good. Wassym, thank you so much for being on Decoder. That was great.

Thank you.

_{Questions or comments? Hit us up at decoder@theverge.com. We really do read every email!}

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 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.

Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get your podcasts. Head here. Not a subscriber? You can sign up here.

Of course, we also talked about all those search changes, and how it seems obvious that the real future of Google Search is bringing things like the new intelligent search box together with the company’s new Gemini Spark agent platform. That way, 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’ll 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 Sundar batted away in previous interviews to something the entire media industry is grappling with. Even the CEOs of major publishers like Condé 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 you get dropped right 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 asked Sundar about Google DeepMind CEO Demis Hassabis ending the I/O keynote by saying we’re “in 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, it’s 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 going to like this year’s conversation.

Okay: Sundar Pichai, CEO of Alphabet and Google. Here we go.

This interview has been lightly edited for length and clarity.

Sundar Pichai, you’re the CEO of Alphabet and of Google. Welcome back to Decoder.

It’s great to be here. Nice to see you again, Nilay.

This is one of my favorite yearly conversations. I think we’ve done it at I/O now five times.

Wow. I didn’t quite realize it’s been five times, but I enjoy it. Thanks again.

I want to 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 realize I have not asked you the Decoder questions in quite some time.

I was just looking back at our previous conversations, and at Google itself, and 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. Tell me how Google is structured right now.

Okay. It is Google and Alphabet. Obviously we have Alphabet as well, but broadly I think about it as there are three main businesses in Google: Search, YouTube, and 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 by Google DeepMind and our infrastructure teams. 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.

I want to 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 as a public company with many bets. But just to stay focused on Google for one second, the knock on Google historically is this is a company that ships lots and lots of products. You can’t sell lots of products. There’s not tons of focus. There are thousands of names of different products that are overlapping in different ways.

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 like, “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: “We’re going to make a lot of bets and see which ones work.” How does that resolve for you?

There’s a lot of intent in what we do too. I think it’s not an accident we have 13 products with a billion users each, and we’ve been committed to those products longer term. You can go back and think about when Gmail launched or Maps launched or Google Docs launched or Search launched or Chrome launched. We’ve been deep and consistent in many, many areas over a long period of time as well.

One way I’ve internalized it 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, with intent, do things which cut across things. Personal intelligence is a great example of it. It’s one effort. 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 our products.

The underlying Gemini model itself is an example of it. 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 tech, the model, the intelligence — is all one work, which is why I think the AI moment offers us a new way to think about it, and not just across Google, but across Alphabet too over time. 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, obviously in a context in which they are useful for users, but the underlying technology platform is common. There’s a lot of intent that way and so on.

You have to give room for innovation, 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 NotebookLM. Notebooks are now showing up in Gemini, and it’s effectively projects as Notebooks. And you can create a Notebook in Gemini, you can go to NotebookLM, you will see the same Notebooks, vice-versa. So that’s an example of where you innovate it first, and then you’re harmonizing later. 

I was watching the 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 Google-y.” There are lots of products, lots of Gemini words. I’m going to figure them all out, I promise.

I would contrast that with… 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 in search away? Between that and now, you have changed Google. You have restructured it. There are new people in leadership roles. Connect those dots for me. How did you think about, “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. I always internalize that moment. It was tough to convey it outside, but 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. To me it was a way to go and actually express ourselves 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 model and a core infrastructure team to power everything we are doing across Google. A lot of my initial energy was to go set that up.

To get one AI team, we had world-class research teams in Brain and DeepMind and brought those together as Google DeepMind, 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 we’re doing that well. At that time I also set up with Amin Vahdat, who’s now our SVP of AI infrastructure, a centralized infrastructure team, which has paid great dividends. Another evolution was realizing we need a chief AI architect to architect this technology across Google, and Koray Kavukcuoglu took on that role as well. Those were important changes.

Search needed to move faster, and Search was split across many leaders, so we put 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 and driving innovation. I have other extraordinary leaders in the company as well, leaders like Philipp Schindler who runs all our operations and so on. So it is stepping back, and thinking end to end about the structure and making sure we are set up well for this moment where we need to move faster as a company, which means we need to make faster decisions.

I set up these new product reviews once a week. They were AI product reviews, making sure we are intentional about how we apply this technology, where we apply it, and to review everything firsthand, that anything to do with AI, which we were shipping to users, went through that channel. I spent time directly with whoever was working on it.

The other 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. What matters much more is that you make the decision, because that’s what determines the velocity of an organization. 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 that 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. The more you’re able to do that, the more you do develop over time some pattern matching and you’ve seen a version of the problem before. 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 it may look big, but it is more a normal course of action you need to take.

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?

Leaders and people are incredibly important. And it depends. Some companies have a much narrower suite of products, and so different structures may work. When you’re running something at the scale of Google Cloud, it’s important that there is a CEO in charge. We are serving all the top enterprises in the world at a scale, and so how do you set up for that? Great leaders end up mattering a lot, like we have Thomas Kurian there. I do think about it.

But what I do think about it is how we are using AI more effectively, and we’ve 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 directing teams of agents effectively more and more. Those are transitions underway, and that will flow beyond just engineering into the rest of the organization. It’s already happening. Even the work we are doing in Gemini Spark is to put that superpower in the hands of consumers, and what you can do with these agentic workflows, et cetera.

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. 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. That’s what we are providing outside. So the agents in Antigravity are what our developers are using, and so that’s what we are trying to put outside. 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?

I just think the CEO job is not that complicated. There are aspects of it where I think it’s going to be very, very helpful in terms of decision-making. I joke around that — partially joke around — that I have to spend a lot of time allocating compute. And I’m like, “Well, that seems like the AI is going to 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.

Everywhere, what I see — which is maybe a bit different than how I think — is that done correctly, these tools are going to allow us to operate at the next level in everything we are doing. 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, I don’t know, spreadsheets rolled out to companies. I have to think back to how did people do all this financial analysis before? And I’m sure it changed over a period of three to four years fundamentally, and we got used to it.

I think agents and so on are a version of it. It’s not like you’re not going to plan birthday parties. 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. 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 going to build custom software for everybody seems like an idea in software engineering, a first impression. The idea is that you’re going to ask the computer 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 look at Gemini Spark, which is your agent platform in the cloud where you will say, “Go book me some tickets,” and Spark might run around and book you some tickets or do some task for you. And then there’s Antigravity, the agentic coding platform. Broadly, every year there’s a new paradigm for AI. There were LLMs first, and then maybe we’re going to 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?

It’s a great question. We are laying most of the building blocks in place. Fundamentally being able to reason, use tools, and code is a lot like 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. You are laying all the primitives. Antigravity is for developers, but the Antigravity engine, the harness, is built into Gemini now. 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.

So you’re bringing that agentic harness. Users don’t need to think about it. 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.

We are laying a lot of the primitives of what we need for agents to work end to end, and more importantly, for AI to work. This long-running vision of Google Assistant we’ve all had and worked through myriad forms of it and failed to fully do it well, we are closer than ever before to delivering on that promise. We haven’t delivered it yet, but that’s the journey which I think is now closer than ever before.

I look at all the products, and they do seem like they should converge. You have the new Intelligent Search box, and I definitely want to talk about Search in more detail. But you look at that search box and then you look at, say, Canvas which makes you the apps. You’re planning a wedding, and it’ll just make you an app to help you plan a trip or a wedding or something. And then you have Spark which can go off and do things. I looked at that and I was talking to people yesterday, and it just seems obvious that that should be one product.

It will. I gave the earlier Notebook example of like, you’re creating Notebooks… but 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 Notebook should be a consistent primitive across the Google products you use. I just view agents that way. It shouldn’t matter. When you’re at the earliest stage of innovation, you create the capability. 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 or even decades now. Go Google it, and you’ll get an answer, and that that answer is the same for you and me generally has been a very important idea. It is, 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, but now we’re going to infinitely personalize the search box, and we’re going to infinitely personalize the Search experience. We’re all going to get different answers to queries. We’re all going to 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? How much can you destabilize the last common source of truth most people experience on the internet?

Look, there are factors well beyond our control, which is that people today have a wider variety of sources than ever before. 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. There are objective experiences and subjective experiences. What’s the capital of the USA? It’s not going to be custom-created for anyone. These are objective things. “Help me plan a nice trip to Montreal for a weekend” — naturally, the answers don’t need to be the same for everyone. There is a continuum there.

We deeply care about it. 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, “What’s better? Should I go buy?”

Can I show you a search result?

Yeah.

A few years ago, I showed you a search result. I’ve been tracking this one for years.

I always love it. Amongst the 10 trillion queries…

Yes. Well, this one’s a favorite.

We have a very scientific, statistical way of doing this.

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: “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. It’s actually a different answer than the AI overview. And then there’s The New York Times, which has a different answer.

You scroll this and you’re like, “The AI overview is telling me one thing, the first organic result is fairly down the page, and all of these are different answers.” I hear what you’re saying about objective results and subjective results. “What laptop should I buy,” is somewhere in the middle of those things. I’m just curious how you think that experience for consumers is today in AI Mode and where you think it should go.

Look, to be very clear, in the world of AIO, we use an AI mode. We are organizing and giving context, but there are sources throughout, so you’re still presenting organic content in a different way. There are links and sources you’re given, but there is an opinion to go with it too, which is what you’re talking about.

Some of this will be iterative with users. 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. That’s why we do these long-term studies. If we get any experience wrong, it shows in the metrics and we course-correct. We pride ourselves on the ability to track this over the long term — be it engagement, sessions, returning to a topic, the number of bounce-backs they do. It’s a very, very sophisticated way of looking at it. In some areas like that, the experience will continue to evolve.

Do you think that experience is good today?

It’s probably more opinionated than it should be for the particular query you showed me. That was my reaction as a user. That’s the scope for improvement is how I would say it, in a fast-evolving space, but I would expect that to happen in the product. My intuition there is, “Oh, that’s way more opinionated.” There is some chance that’s personalized to you. You may be testing it in a way that you’re uniquely personalizing. The reason that query might not be exactly representative, though, is that I know how you review all these things. There is some chance you’re in the .0001 percentile–

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 all the time. They have that experience where they’re kicked to AI mode. There’s the stuff you can measure about user satisfaction, and then there’s how the public feels about AI.

I think there’s a pretty yawning gap between, “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. It’s 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. Seven 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?

It is a very profound topic, and you’re linking the two things. AI is the most profound technology humanity’s going to deal with. It’s happening at a very fast pace. I don’t think humans have evolved to process this much change, and the rate of change particularly over the last few years is incredibly high. And particularly with all that they’re hearing, people are trying to understand the future and in the personal context of their lives, including what it means at an economic level and so on.

It really makes sense why there is anxiety around this technology, and we should be very attuned to that. That’s an important topic, and that’s much broader and bigger than the facets of what’s happening. People don’t directly associate these two all the time. In some cases, yes, they are linked in certain ways.

People experience the free versions of these models in various products. They open their social media feeds and they see slop. They see headlines about all that stuff. They have the tools just presented to them. The Gemini sparkle shows up in all the Google products, whether you ask for it or not. And then I do think you link it to, “They’re asking for a lot of electricity, and maybe my rates will go up. And maybe all the jobs will go away,” and that’s pretty scary, and I don’t know if the value exchange is there.

These are good things to study. You’re being too specific on what’s happening versus I’m just broadening it out and saying that might be part of the explanation. I do think there are other cheaper factors too.

Do you think it’s just a marketing problem? I’ve heard your peers say that AI just has a marketing problem.

No, I don’t think so. That’s the point I’m making. I’m in fact arguing against it. I think it makes sense to me why people would feel concerns about it. It feels natural to me. People are talking about how AI could make a lot of jobs go away. Why wouldn’t you feel a sense of anxiety about it? I think those are deeper issues which we have to tackle as a society. Yes, there’s concern about AI slop at a product level. All that is true. All I’m pointing out is it’s a multilayered problem. But I don’t think all the source of the data center angst is directly related to one specific experience you’re having in a product or something alone like that. That’s all the point I’m making, right? It is broader and bigger than that. 

There’s a lot of AI slop out there. I feel it. In an early phase of technology with the competitive dynamic that exists, a lot of things are getting rolled out. But we also see empirically how people are using these products in very deep ways. If you go to a place where Waymo hasn’t come and you’ve just polled people, talking about self-driving cars, what you get in the polls is different from how they feel when they use these cars. Technology also goes through these things. People have pretty negative views of the internet too, by the way, if you ask about the internet. But it’s a fabric of our lives, and we have to adapt to it. All of that is simultaneously happening.

It’s a complex topic. To me, it feels like people are worried about rising energy prices, and if so, they want to make sure AI is not exacerbating the problem, and that’s a valid concern. And it’s up to us as an industry to make sure that if you’re building data centers, what can we do to make sure we aren’t contributing to that problem? I view it as our responsibility, not just us. And the government, there are bipartisan concerns around some of this stuff. For example, there’s a rate payer pledge we all signed up to with a set of commitments. Maybe there needs to be more done. All of that goes hand in hand. It’s important to talk about topics like skilling, workforce adaptations. We are driving a lot of change very fast through society. Those end up being very important topics as well.

There are concerns at all those levels, and I expect those concerns to be meaningful as we go forward. Many years ago I said, “This is more profound than fire or electricity,” and so we have always felt that. Or think about deep-fakes and how do you know whether something is real? These models are getting better at simulating reality. This is why we’re working so hard. We are open-sourcing it, we are pulling many, many partners together, and it’s great for me to see the industry collaborate on a topic like this. Cybersecurity is another good example. These are all real concerns.

As an industry we need to do more. Governments will have a stronger role to play, and the public needs to be involved. You cannot have the most consequential technology rolling out the world in a way in democracies without public citizens rightfully having a voice around it. It is really important that we go through this phase, and that’s how we learn how to adapt.

My argument is that the products do the marketing work. That’s my push. I’m still waiting to see the killer app for consumers that does it. I think we have the killer app for enterprise.

One point, there are times I’ve gone through a health journey in Gemini. It feels more than like a killer app to me, better than anything I’ve ever done before. People are going through those experiences too.

I want to talk about the web, the health journey in Gemini that requires a rich data set of health information on the web to exist. You’re training Gemini on YouTube videos, right? Veo requires the YouTube ecosystem to operate and to be fruitful, to make new work in. You and I have discussed the concept I call Google Zero for many years, the idea that you will stop sending traffic to the web. You’ve disagreed with me that this is real.

Very much so. It hasn’t happened in the last many years.

Well, I’m just going to read you a quote. This time it’s not me, and I didn’t feed this to him. Roger Lynch, the CEO of Condé Nast, did an interview with TBPN last week and he said: “Every year our search traffic was down more than we had forecast, so last year I told our teams, ‘Assume there is no search. You have to have your businesses planned as if search is zero.'”

That is Google Zero. Condé Nast is saying, “We’re assuming that search will go to zero.” How would you respond to that, the idea that one of the biggest, most iconic publishers in the world is saying, “I can’t depend on this anymore”?

Look, first of all, the information ecosystem is so much broader beyond Google, by far. We see it in the data, you see it everywhere. So if any publisher over the last 10 years… I would look at The Verge and I would say where you were when you first took over, how much it’s evolved since then, the types of content you make, where all you put that content out, how all users are coming to you. It’s exceptionally dynamic, and so it makes sense to me every publisher is adapting to this new world.

We are adapting to the evolving world and how users are consuming technology. We had to do this when the world shifted from web to mobile. We are shifting it from a world of mobile to people having ongoing conversations, chatting with these products, talking to them, consuming it in voice and many different form factors.

People are expressing preferences for various types of content. They’re looking for user-generated content. They’re looking for podcasts. They’re looking for that. Through it all, we are very committed to both meeting user expectations, and also connecting them to what’s out on the web. Just even in the last year, even since we’ve launched these features, we’ve gone back and added more links. Another area where behavior is changing is that many publishers, rightfully so, are thinking about subscription models.

Sure. But I’m just saying Condé Nast is saying, “We’re going to assume our search traffic is zero, given the trends that we see.” Should they assume that?

Look, I always view… People understand their businesses better… I mean, I’m not in a position to tell such an iconic publisher what they should think about their business or plan. If they are building content that is high-quality and people like it, I expect us to reflect that in our products. That much I can commit to them.

But I think more than any other company through this evolution, we are working very hard to make sure people can get connected, and we are planning to do it in Search and Gemini, and that still underpins a lot of what we do. But there is evolution. As the technology improves, low-quality clicks get filtered out. That’s a natural evolution we see. We see it in our metrics. Bounce clicks are going down. And so those are all dynamics.

People are going to a wider array of information, and there are more people producing information than ever before. That pie is growing. All these dynamics are happening. It’s a complex ecosystem, but our commitment is to make sure we reflect the vastness and diversity of the content, and we do think people want to connect ultimately to these sources, but we are trying to meet them in those moments, and people come with very different intent and very different moments.

One of the small features we have done, but very important I think, is if you’ve subscribed to something, we reflect that as a preferred source for you as a user. But that’s a new change which we didn’t have before. We are adapting to the fact that publishers are increasingly turning to subscription offerings too.

Publishers and YouTube creators, should they be able to opt out of training to get surfaced in Search?

This is a much broader topic. Both laws and regulations will have to evolve. The courts will have to weigh in. It’s important to protect copyright. It’s important to protect fair use. And so these are constructs which will evolve dynamically through that.

But do you want to be in a bunch of lawsuits with YouTube creators? You’re in a lawsuit with publishers in the UK. That rhetoric in that lawsuit is getting increasingly heated. Google has said that the proposed solution is a “free rider charter.” Every year the News Media Association sends me a quote to read to you, and they say, “Google calling us free riders is obviously ridiculous. It’s basic supply chain economics. If the value were really all on Google’s side, they would simply allow publishers to opt out.”

Do you want to be in that same fight with a bunch of creators on YouTube about opting out?

Look, we are constantly — as part of Gemini developing…

We did offer a new opt-out with Google-Extended, and we are in conversations with publishers. We’ll take feedback and over time work through what makes sense. Obviously we are not the only player in a big ecosystem. We are also trying to put out products which are competitive to other products out there. All the publishers will also write an article saying the product is not very good. So it is more complicated than it looks.

You have spent more time thinking about the web and the health of the web and the necessity of the web. Paint me the picture for what a healthy web looks like in an agentic search world.

One of the arguments I’ve made over time and I actually see it playing around a little bit more, is I’ve started using the web more again over the last year to year and a half. All these AI experiences have brought the web back more. There was a time when it felt like… But I always felt the web would be vibrant. In fact, I’ve argued the web is going to be vibrant every year, and I would still argue it today. The web is constantly evolving. I’ve never seen anything as dynamic as the web, which is why it’s been such a privilege to be part of that evolution.

I look at agents, and that is the next evolution of the web, which we will deal with, and I think it will evolve the web pretty profoundly. There will be a lot of debates about what’s okay, what’s not, but people want to put out information, to connect with other people. People want to be connected. People aren’t trying to be in a siloed world, detached. That doesn’t reflect the reality of the human experience. I think the web is going to play as central a role on it as ever before. In fact, the Universal Commerce Protocol, if anything, what we announced yesterday, I think people are slightly underestimating the impact of it.

Actually, can I juxtapose that? There are a lot of muscular announcements about new products, new features, and agentic tools you can use, and UCP and Amazon and Walmart and everyone saying, “We’re going to use a new standard we’re building for shopping,” and all that is very tangible.

And then I/O ended with Demis Hassabis, the CEO of DeepMind, coming out, and he said this thing that I have not been able to stop thinking about. 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”?

Demis and I have had long, deep conversations on this topic. In this context, the advent of AGI is what he thinks of as the singularity.

Do you have a definition of AGI? Have you debated it? Do you have an agreement?

We debate it a lot. I think both Demis and I are very close in how we think about things. There is a harder definition of AGI, which is that it has to be more comprehensively able to do a wide range of tasks, including cognitive tasks, in a way that’s comparable. We’ll at some point actually put it out as a company, and we are working on that. But that’s what he’s talking about in this context.

By the way, I think it’s important for us to understand that this technology is progressing very rapidly. Later today, I’ll be going and spending time with our AI researchers, not just in our company, but also amongst the frontier labs. There’s wide consensus that this technology, AGI, is… people may quibble around whether it will be three years, but the technology’s coming sooner rather than later. It’s more important to communicate that because — to an earlier part of the conversation — it’s important that we as a society understand it and are preparing as much as possible.

I asked you this question maybe the first time we ever talked about AI. I asked you if language was intelligence. And the progression here is we’re layering more and more on LLMs. We’re doing longer chains of reasoning, we’re building harnesses, we’re doing all this stuff, but the core technology is still transformers. It’s still the thing Google invented so long ago. Can LLMs get you to AGI? Is that path clear?

The trajectory over the last three years has been incredible. The LLMs of today have evolved in many ways too. We are constantly evolving it. To me, it’s like asking, can computers get us to the way—? The von Neumann architecture is still what powers most computers today, but he won’t recognize the modern one of our TPU pods. Or maybe he would. There’s still a lot of commonality to it. The underlying technology keeps evolving so profoundly. I look at every year we have had major breakthroughs. I mean, you just saw us demo in Antigravity an ability to prompt and create an operating system.

It’s very dangerous for Google to be able to make new operating systems.

We’ll have to make sure we don’t token max on creating… I’ll give you that. It’s fair, but that is the power of what these things are doing, right? There are the top mathematicians in the world, top physicists in this world who are interacting with these tools and using them in important ways, but can these tools fundamentally make novel scientific discoveries on their own? Not yet.

It’s remarkable how much it’s progressed. I do think it has important evolutions to happen, and then there are strong opinions out there in the world about how much of a real understanding of the world you need to take that next leap. I’m pretty optimistic that we will continue to make a lot of progress.

What is your timeline? Is it three years, or five years, to AGI? Where are you at?

I have always answered it this way: I think that timeline doesn’t matter because the rate of progress means you’re dealing with ever more intelligent systems in a profound way. So the way I would answer that question, three years from now, whether you and I call it AGI or not doesn’t matter because it’ll be very, very powerful, and we have to prepare for it.

Sundar, this was great. Thank you so much for taking the time yet again.

Yeah, thanks, Nilay. Pleasure.

_{Questions or comments? Hit us up at decoder@theverge.com. We really do read every email!}

My guest today is longtime friend of the show Joanna Stern. You all know Joanna: she is the former senior personal technology columnist for The Wall Street Journal, a former Decoder guest host, one of my cofounders here at The Verge, and also just one of my very closest friends.

I mention that because Joanna just left that lofty perch at The Journal to start her own media company called New Things. She’s starting with her new book about AI, called I Am Not a Robot, which is out this week on May 12th. 

You’ll hear us reference the fact that she and I have been talking about her big move to go independent for ages now — it’s something she’s wanted to do and wrestled with for years, and she has a long list of interesting reasons about why now is the time. She’s also structured her new venture in partnership with NBC to keep her in front of a big mainstream audience.

Verge subscribers, don’t forget you get exclusive access to ad-free Decoder wherever you get your podcasts. Head here. Not a subscriber? You can sign up here.

It was important that I prove to Joanna that I actually read her book, which is really quite good. She spent a full year allowing AI into every part of her life and has more of a sense of where this technology actually is than pretty much anyone because of it. As you’ll hear Joanna explain, many of the most hyped AI-powered gadgets — especially the humanoid robots — are definitely not ready, and they might not be for a very long time. 

But you’ll also hear Joanna say she’s a lot more bullish on certain types of AI after her experience writing her book. She thinks wearable AI might really get us to a killer app — one that might justify all the extreme tradeoffs we’re making to continue developing the technology at the pace the tech industry wants to.

She’s also using AI to help get her new media company off the ground. So I asked her about that, too, and what she’s learning now that she’s left the world of traditional media and put a heavier emphasis on the YouTube algorithm.

This is a really fun one — it is about as close to the actual conversation Joanna and I have at our regular dinners as it gets.

Okay: Joanna Stern, author of the new book I Am Not a Robot and founder of New Things. Here we go. 

This interview has been lightly edited for length and clarity. 

Joanna Stern, you’re the founder and chief everything officer of the new tech news venture New Things. You’re also a former columnist for The Wall Street Journal, but most importantly, you’re a cofounder of The Verge and also just one of my closest friends. Welcome back to Decoder.

It is so nice to be here on Decoder and not subbing in for you.

[Laughs] It’s true that you were also a guest host of this show for a while. This is the most conflicted episode of Decoder I think we’ve ever done, but I’m excited for it. I’m going to try to make it as tough on you as possible, as adversarial. We’re going to break down, we’re going to find the dark heart of New Things. 

I’m going to make it adversarial on you because I was a host here.

[Laughs] That’s true.

We’re figuring out whose show this is. I see that it says behind you “Nilay Patel”, but we’ll see.

We’re going to get AI to change it in real time to say “Joanna Stern”. Has anyone ever heard a podcast with two hosts? It’s going to be amazing.

You’ve got a new book out. It’s called I’m Not a Robot. You spent 12 months in your life using AI for everything. It’s organized by seasons. Your kids are in it. It’s very good. It’s very funny. It’s out on May 12th. There’ll be a preorder link in the show notes. You also started New Things, which is your new media company. You left The Wall Street Journal, you’ve got a YouTube venture. I want to talk about all of these things.

I want to start with a very simple question. You are one of the more influential tech reviewers in the world. You have spent a year using AI products to do everything in your life. There’s the book. You can see it.

I’m just going to keep doing this the whole show.

Here’s my theory. I don’t think consumer AI products are very good. I don’t think there’s a great consumer AI product, and I think a ton of the angst we hear about AI is a reflection of that. You have used all the products, you’ve used the expensive ones, the bleeding-edge ones. You just had a robot step on your foot. Where do you think we are? Are these products good? Are they great?

I think they can be great. I know that you feel this way, but I think they can be great. I’m going to turn the question back on you. People in your life that are not in the tech world, do they use AI?

It’s foisted upon them. That’s how I feel about it. I feel like if you open Google, you get some cheap-to-run AI model in your face doing AI Overviews, and that is fine. And Google had to do that because they felt very threatened by ChatGPT.

But then, if you open the free version of ChatGPT, you get some cheap-to-run AI model that is a bunch of engagement prompts at the end of every query. And everybody is having these experiences. So yes, they’re using them, but I don’t know—

AI is being forced upon them.

And the experiences that are being forced upon people look like slop. They open their Instagram feeds and there’s slop.  No one’s going out to buy an iPhone. Do you know what I mean? That was a thing that people chose to do because they were excited about that product. You and I both lived through that entire moment together as colleagues. I’m just looking at these products, the free products that are in front of people, and I’m saying, “These aren’t actually great.”

I think that they have not become great in the three to four years since ChatGPT released. And so for the people that are using ChatGPT or some form of a chatbot,  have they gotten considerably better, at least in terms of a product, in the last four years? If you look at the consumer, it’s Gemini, ChatGPT, and we can say Claude has been shooting up there, but it’s hard to tell if that’s really a consumer adoption. I think the models have gotten better. You can maybe trust these more, but the interface has not gotten any better. 

Most people are just still launching ChatGPT. Maybe they’re doing voice mode. I see a lot of people doing voice mode now, but mostly they’re typing to a chatbot and that has not gotten better. I agree with you there. 

But I do think that people have figured out other use cases where AI is now helping them in their everyday lives, not just at work. That was my question to you: Are your friends, or the people you hang out with on the weekend… We both don’t have friends, let’s be honest.

[Laughs] We are friends.

We are friends, but we are in this. We are not normal people. That’s why we are friends, right?

Yeah, it’s very difficult to be our friend.

But your parent friends or your old friends or family, I see those people using AI in really interesting ways, or going to AI now instead of Google. Our nanny is a great example. She’s constantly asking ChatGPT questions. I’m going to give the classic example, which is recipes and cooking and all of those things, but she’s often asking ChatGPT to do things.

I do that too. I watch my daughter basically fight with Google about who knows more about space. It’s a very good pattern in our house. She starts asking Gemini for space facts, because she just talks to the Google Assistant on our Google Home, which is now powered by Gemini. So they just talk about space for a while. I think that is wonderful. I legitimately see her curiosity get rewarded in that dynamic. I think that’s great.

What I’m talking about is that the AI industry is asking for a lot. A subtext of your book, and it’s made explicit about halfway through, is like, “Yeah, I’m talking about all the jobs going away.” There are grades of how fast the jobs might go away. You hired a human researcher and then replaced her with AI. And you were like, “This is pretty much as good and it’s much cheaper than my human researcher.”

And then I think, in a very cold turn, you went and interviewed the human researcher about how she felt about being replaced by AI. Very good. 

But that’s a lot to ask from everyone all the time. The whole book is about you using the bleeding edge of this stuff integrated in your life and your kids’ lives and your poor wife’s life. And I’m just wondering if there was a point where you’re like, “This is definitely good enough. This is great,” in the way that the products that we came up with as tech reviewers were just obviously great. The iPhone was an obviously great product.

I actually coined this term at the end of the book, AEI, which stands for artificial enough intelligence. We don’t need AGI. A lot of these tools that we already have are good enough and they just have to be applied better. Someone smart somewhere needs to say, “What is the best way for a consumer to actually want to interact with this stuff?” Some companies I think have gotten there, though I think a lot of them just end up being acquired and then sitting in the basement of Meta or one of the big companies.

The more the year went on, things got better. I was at the bleeding edge, but now the bleeding edge is where the bleeding edge is. So now, when you read the book, I’m at a little bit of the old edge, but I don’t think a lot of those themes change at all. I think you’re getting to the question, has there been or will there be a killer consumer AI product? Isn’t that the question you’re getting at?

That’s one way of phrasing it for sure. Is there something that makes everyone excited for the change? The internet is in the introduction of your book. That everyone made these wild promises about the internet and then some of that stuff didn’t happen, but then it definitely did. We just all lived through it without any contemplation.  Your book is an attempt to do some contemplation. 

I would just say the internet, especially when it came to smartphones, was just so obviously how everyone wanted to do everything, that all the costs along the way… Now there aren’t any travel agencies. No one had a freakout that there weren’t going to be travel agencies. They were like, “We’re just going to use the online booking portals now. It’s just what we’re going to do.” And I don’t see that one here.

I see that one here for a number of use cases. Maybe it’s just because we’ve already lived through that moment, which is what I’m kind of wondering in that introduction — are we on par with the internet moment? Is life going to change as much as it did in the late ’90s into the early 2000s? Are we going to have a moment of that?

The answer I get to is that it probably won’t be as drastic, but there are ways that AI is going to affect life whether you like it or not. I loved your essay that you did a few weeks ago on software brain. We may all decide we don’t want to use it. We know already at this point a considerable number of people are going to use it, but we also know a lot of people hate AI right now and they’re resisting it.

Where I get into the book is, that’s fine. You can try to, but there are going to still be ways that AI affects your life regardless of whether you want it to. The healthcare chapter is a perfect example of that. I go and get my mammogram read by AI. My radiologist is using AI side by side. Turns out my radiologist had already been doing that for a year. I didn’t even know that. That’s one example of how the underlying infrastructure of so many industries is going to use AI.

Another great example of that in the book is the Waymo chapter. You may decide, “I never want to be in a Waymo. I never want to go in a self-driving car. I don’t want the machines, I don’t want the tech companies driving my car.” You are going to drive your own car, but next to you will be a self-driving car and that will affect life. 

That’s my broad thing of how listeners of this show may say, “Hey, fuck it all. I’m not going to use Claude. I’m not going to use this,” and even if, to your point, Google and every other touch point on the internet or in apps integrate AI, “I’m going to try to resist it,” but you’re just not going to be able to.

I don’t know. I think listeners of this show are generally people who work at tech companies and they’re thinking about business. And I agree with you. I think there’s a real product-market fit for the AI tools in a bunch of enterprise settings. Healthcare is a top example. I can see it already. There’s just a lot of data in a lot of databases in healthcare that don’t talk to each other. Maybe AI can solve this problem. There’s a lot of repetitive tasks. There’s a lot of monitoring. You can see it. You can see how it will work. 

I think the car example is fascinating. The second I can get my parents cars that drive themselves, I will get them one. If that means throwing out their cars and buying some subscription to Waymo, we’ll do it. But that product is so expensive today that it’s not in Wisconsin, where my parents live. There is a diffusion gap where it’s like, “Well, so to get my parents out of their car and into a car that drives itself, I need them to move to Austin.” It’s not going to happen.

Do you know what happens on Decoder? All roads lead to car talk when we are on.

They do at the end of the day. We’re going to talk about CarPlay in one second. They just rolled out voicemail in CarPlay. We’re going to do it. That was a big hit when you were the host. 

My newsletter that’s going out very soon is about that.There’s really actually no deep mention of CarPlay in the book, but I think we should obviously shift this entire podcast to being a CarPlay podcast.

The analytics tell us that you and I should only talk about CarPlay. That’s all the people want. 

The point I’m making is, you can see in these places where, yes, it’s just going to happen to you. It’s going to happen around you. I think I’m just thinking about your year where it was integrated in your family, where you used it for everything. 

I’m curious, where was the place where you thought, “Okay, my experiment is done. My book is published. I’m on the podcast circuit. I’m going to keep using it in these spots”?

Well, it’s evolved. Look, we can get into the business conversation, and I guess I’m saying you’re right. I rarely say you’re right, but I will right now say you’re right that the biggest place in my life right now where AI is making a big difference is in starting this business. 

I’ve got the Mac Mini. We’ve got a Slack bot. We’ve got an AI agent in Slack that we’re training to do stuff for us. Everyone on the team, the very small team, is using AI because my number one thing was like, “I want you to optimize and be efficient in the things that you do not want to be doing, but I want you doing creative video editing. I want you pitching amazing stories. I want us to be ambitious, but we also have to do a lot of this busywork.”

So you are right. That is probably the biggest place, and that is enterprise. That said, we still have quite a few weird little things in the house that we still use from the year. Yes, weird robots beyond the vacuum robot. I still have the Posha cooking robot, which we use every Sunday.

Do you really?

Yes.

What do you use it for?

Making the side dishes for our Sunday night dinner.

Really? And it does it?

It does it.

You trust it?

Oh, totally. But that’s not deep AI. It’s weird. Have you seen this? You guys have covered it.

Yeah.

You guys did a great job covering it at The Verge. I can just set it and forget it. And my kids love it. They love watching it because it’s a little bit idiotic. To describe it for those that don’t know this, this is three times the size of your toaster oven. It takes up an entire counter. My wife hates this thing because it’s taking up a lot of kitchen real estate. It’s got a big pot and it’s got an arm that stirs in the pot. It’s a glorified hot pot, but it dumps the ingredients in. So you put all the ingredients in, including raw meat, which is weird and unsanitary, we think, but we’re all fine. We’ve been using it for six months. Everyone here is totally fine and the dog is fine. No one has salmonella.

Every time, it dumps these things out and it doesn’t know that it’s done this. Because there’s no sensors in the container, it doesn’t know it’s dumped it all out. So it just dumps and dumps and dumps and it’s empty and it will just be dumping for 30 seconds and the kids think it’s hilarious and they’re like, “Idiot robot, dumb robot.” Pretty much every Sunday night we do that. I would say there’s a lot of lasting effects on my kids, and you’ve met my kids. They also pretend to be cleaning robots after Sunday night dinner. 

That’s very fun. 

They clean up and they say things like, “Cleaning robot mode initialized.” And they go around the room and clean and do all the dishes, which frankly I’m totally fine with.

If I could get my kids to do that, that’d be great.

Just have a bunch of robots in your house for the year and then they want to be them, which is again, the book, I’m Not a Robot, they literally think they are robots on Sunday night. 

There’s a lot of weird little things that have just stuck around that have become part of our life. I will say, and I took it out again this week, that I think the wearable stuff has really stuck with me. And you guys do a lot of great coverage of it on The Verge and we all know nothing’s really cracked through, but I do think at some point something is going to crack through.

I wear the Meta glasses a lot. Not only do I wear the Meta glasses a lot, but I talk to AI through the Meta glasses a lot on the weekends when I’m with my kids. I don’t have my phone with me as much. That’s one thing. 

I wore this recording bracelet for a lot of the year. I just did a speech earlier this week and I wanted to practice with it and I wanted to practice the speech, and I also wanted to have this recording bracelet on me during that day that I was doing this speech and talking to various people at this event. I wore it for the day and I found it really valuable to get summaries and the to-dos I said I was going to do. This is the Bee bracelet that, again, feels like a prototype still, but I think the ideas there are going to carry over into something really good soon. I don’t know when “soon” is, but soon.

Both of those categories, and even those products specifically, highlight what I think of as “the trade-offs.” At one point, I think your basement is flooding and you’re wearing the Bee bracelet and you have to tell the plumber that you’re wearing the bracelet and the chapter just ends with, “And he was quite intrigued.” And it’s like, “Do I want to tell my plumber that I’m recording him?” 

You have social dynamics that change because you’re recording everything all the time, because these systems need the same data that you have. Meta has a whole bundle of issues associated with privacy with wearing those glasses now. Did you feel that trade-off was worth it? It sounds like you did. Did you just get used to telling everyone that you were recording them all the time?

You start to forget to tell people that you’re recording, which I think was a little bit of a view of a really dystopian future where we forget to tell people we’re recording because everything is being recorded. I stopped wearing it for that reason. It would pick up on things I just did not want recorded. And the microphones on those are shockingly good. You’ll leave it in the other room and you’ll be like, “I didn’t say that around this thing. How the fuck did it know?” It’s shockingly good, which is crazy. 

It goes back to a story that both of us have lived through in this industry, which is the idea that your phone can’t be recording. Your phone can’t capture this much data and send it to the advertisers. It’s like, “No, your phone definitely can do that. We’re not saying it is happening, but it absolutely can.” The answer that we got for so many years is like, “Technically, that would be so crazy.” That’s not true anymore. They can instantly transcribe this, you can transcribe it on the phone. We know that Apple can do that. We know Apple isn’t doing that for these companies, but it can happen.

That was just a big learning for me. These things can get 90 to 95 percent of everything you say. There are issues with the transcript. You and I are very used to getting great transcripts from Otter or Rev. It’s not as good as that because we’re not talking directly into a microphone, but they could be shockingly good transcripts. And then the AI just makes sense of it. You get a great to-do list of everything you said you were going to do during the day but totally forgot about. Useful, but yes, the other side of it is totally dystopian because everyone is recording everything.

And you felt that. You felt like you needed to take it off for a while.

Yeah.

But you don’t feel that with the glasses?

I think for me it’s different because I don’t wear glasses all day long, so when I put them on, I’m making an active decision. I’m putting my glasses on, either because it’s sunny outside or I want to have this AI on my body right now. I did wear the see-through, regular transparent lenses for a while, but I actually look like Garth from Wayne’s World when I put those glasses on, so I didn’t wear them all that often publicly, because vanity. But I can see a world where we will.

I think it’s very funny that Meta is trying to make transition lenses happen.

Ugh, they’re terrible.

They invested in that company and they are trying to make it cool to wear transitions. If I had to point to one single example of the disconnect between what the tech industry thinks it can make cool and what regular people think is cool, it’s Meta’s attempt to make transition lenses cool. I just don’t think you can do it.

No.

And I appreciate it. 

There’s no world where you’re wearing transition lenses and it doesn’t remind me of my grandparents.

And I’m an old guy. I’m the target market for transition lenses. You should be able to get me.

You just hit transition lens age, I think.

I’m in the window, and they can’t do it.

I’m not there yet. I’m younger than you, Nilay, as everyone knows and can tell, but you just hit it. You’re ready.

I’m in the zone and they can’t get me.

This is the other thing. You have to change the culture around it. I watched the video that you just made and it’s you running around outside with your kids and a robot and it’s like, “Oh, we’re going to change the culture around this.” People have reactions to delivery robots driving down the street, and they don’t love them. They think they look dystopian.

An actual bipedal robot moving around seems like yet another gigantic change, and you have to have some utility there. That was the turn in the book that I thought was the most interesting. We can do a lot of recording, we can do a lot of text analysis. They’re getting way better at transcription and organizing the first cut of research, I think you mentioned several times. I believe you gave AI four robots in your chart out of five for transcription and first-pass research.

And then there’s a bunch of stuff that, particularly when you get to the real-world robots, they just can’t do it yet. The world models don’t exist. The hardware exists, but we need vastly more training data in all the places. What’s the gap there? Because that’s the next turn of AI that everyone is making the promises about.

I loved this turn because I really went into this not knowing a ton about it and learned so much through talking to all these experts. And the gap I think is a very Decoder thing, because you’re so good at identifying the gap between what is being marketed and being told to people and what the tech world and the AI people think versus what’s really happening there. And that gap could not be farther apart. 

People like [Nvidia CEO] Jensen Huang are claiming that humanoid robots are the next big thing. It is so far from ready. It is absolutely so far from ready. And the tech people will not tell you that. The people making the robots just say, “No, no, they’re coming next year. They’re coming now.” They are not, realistically. And truly, they’re clouded. They don’t see it clearly because they’re in it.

Then you talk to the academics and you go and see these products and you’re like, “There’s just no way. There’s just no way, even if it was ready, that people would be letting some of these things into their homes right now.” That’s largely the data gap, which we can talk about — the fact that these robots don’t have enough data of doing real-world things, especially in the home, because the home is the hardest place to put a robot. It’s not a factory floor. Everything isn’t repeatable. Everything isn’t mapped out for it. Everything in your home changes, especially in a home with kids and a dog and whatever other animals I have living in my house this week. My son is getting a snake, which we’re going to feed to the robots when it comes time.

That gap is massive. I found that fascinating because we’ve seen a lot of this all play out right now with generative AI. It is absolutely getting better. It’s here and it’s in our hands, but this idea that robots and physical AI are coming in the next two years is just a lie.

This is the thing that just really strikes me, and you mentioned software brain. The demand on the software side of AI is to make yourself legible to the computer. Record everything, put all of your information in a database. My Whoop band every morning is like, “I watched your heart rate and now I can tell you about your day.” I don’t know if that’s true at all. I think it’s very entertaining, but there’s an idea that, at least in software, you can turn yourself into software or data such that an AI can talk to you about something: “Here’s my electric bill. Tell me if I should get solar panels.” There’s some very intriguing data analysis you can do in that way.

Then you come to robots like physical AI, and it works for Amazon, where they have a warehouse and they can paint the lines on the floor and they can put all the bins in the right places. You watch those videos of all the robots doing their orchestrated movements and you’re like, “I understand this.” How am I going to get enough data ever to make a house with kids in it legible to a robot? It doesn’t even seem likely to me.

If we ever revisit this book in five years, I do not think we will have these things. No one will also put a timeline on this. Even the academics are like, “We don’t know. We don’t know what will happen on AI progress with transformers and models and world models and all of these things. We don’t quite know how that progress is going to work.”

They will tell you that it’s moving really fast, and it is getting rapidly better. But again, that gap to us as consumers putting these things in our homes, not only safely, but actually with real utility and benefit… Even if that thing can fold the laundry and do it in less than two minutes, and it can do more than just T-shirts. There is a section in the book where I tested this laundry robot and it’s really just two robotic arms and a model running on a laptop. It’s amazing because you’re like, “Oh wow, I can see the future in this, but it’s so far away.”

It can only fold t-shirts.If you’re only wearing t-shirts, that is a real problem. It cannot fold faster than a minute. It takes a minute for it to fold the t-shirt. That speed got better and better as the year went on, but it can’t even fold that well. Plus, this is quite expensive. So it has all of these pain points. 

We’ve been reviewers for a long time. Who is recommending that? Who is signing up for all of those issues when they’re just like,” Yeah, I can fold the T-shirts”?

You and I have been reviewers for a long time. Most of the products have to ship. At the end of the day, that has always been, I think, the power of being a tech reviewer as opposed to just a tech reporter. We get the products, we review them. Your entire career is built on getting away from the briefing and taking the iPhone’s Dynamic Island on a kayak to an island or skiing in a Vision Pro because it looks like ski goggles. The truth outs with the products. You get them away from the companies and you use them and there’s no hiding. The products work or they don’t.

Why do you think this class of companies, the AI companies, whether it’s the Bee bracelet or the humanoid robots, are so eager to ship products that can’t quite do all the things that they’re supposed to do?

Data. I think data — largely that. With the 1X story I did at the end of last year when I was at the Journal, which was really actually a book story that fell into my lap because I had been talking to that company and following that company for the year, the thing about the robot companies is purely about data. The CEO is so honest. He says, “We need data.” 

That’s the contract you enter into. “We will give you this robot and you will get more out of this robot if you give us more data because we need that data to train the robot to do things.” So even in that case, which is the total extreme where the robot actually is a human — it’s not technically a human in a suit, but it’s a human operating a VR headset back in their headquarters in Palo Alto — your robot in your home is being operated by that person.

It’s collecting data. It’s like, “Hey, for two hours a day…” This is their genuine pitch, and that’s why I did the story. They had been telling me about this all year and I was like, “Guys, this is crazy. This is nuts.” 

And then they really did it and they’re doing it and I hope to get their robot hopefully this year. I want to keep testing with them just to be that person to test with them. But it is nuts. Your man in Palo Alto is steering my robot in my house and doing the dishes and vacuuming and whatever else, folding the T-shirts, because you guys need more data. That’s cool.

Again, I’m looking at that. The comparison in my mind is to Waymo. Literally their metric to get the cars to drive themselves was the number of miles driven. And they’re like, “We need to get to some enormous number of miles driven before we can take the driver out of the car and the thing can be autonomous and we can launch more in cities.” 

They might not even be up to the final number. Snowy days still elude Waymos. There’s still a ways to go, but they got to the number and there’s autonomous Waymo service operating in a bunch of cities. But that was cars. You can put a car and a driver with a bunch of sensors and do a service that’s useful for people and get there. Can you get there with one robot in Joanna’s house? Are they going to have a warehouse full of guys in VR headsets autonomously controlling robots everywhere?

That is what they say they’re going to have, which, gosh, I want to do that story. It’s so good.

It’s very good. I just keep coming back to the trade-off. You have to get a warehouse full of guys in VR headsets.

But also you have the other thing, which didn’t make it into the book, but I did a lot of reporting on: Normal people, instead of being Uber drivers doing gig economy work, are in their houses recording themselves folding laundry or taking dishes out. They wear a GoPro on their head and they are just doing these things over and over again. Believe me, I wanted to sign up and do that, but I didn’t have time. 

But that’s a whole new line of gig economy work. Some videos went viral a few weeks ago of people, I believe it was in India, sewing and recording themselves. The idea that the robots are going to sew is odd to me, but you don’t even need to have the robots in the house, we just need the data. They need the videos to make these models.

There’s a part of the entire AI economy that is just built on that kind of surveillance, whether it’s on purpose, whether it’s accidental, whether it is even disclosed. How should people think about that? My joke is always that the second Meta releases the glasses with the AR display that tells me people’s names and faces, I will reconsider my entire stance on having a worldwide facial recognition database. 

That’s the killer app for those glasses. Meta has talked about building that app.But that’s a privacy nightmare, just a straightforward privacy nightmare, to do that. But it is also the killer app. 

You’ve spent a lot of time using these devices. You’ve done a lot of quiet surveillance, I would say. How should people think about that aspect of it?

It’s the longtime question of cost versus convenience, and how do we balance that cost and think about that convenience. That’s a great example. You think that, for you, that killer app of being able to look at the person that you met at the conference that you know you’ve met three times but can’t remember their name, and you wear your glasses and you can now remember that name. To you, the convenience of that might be worth the cost of this worldwide surveillance network.

That’s rough.

You, Nilay.

You’ve made that sound very selfish, but yeah, that’s how I feel.

That’s how the companies are going to think about it. I know for a fact, I know many of the executives that you and I talk to think about it that way. I’ve heard them talk about it off the record. I’ve heard them get close to talking about it on the record. “If we can provide the convenience, then we think you’re going to be okay with that cost.”

Because the cost isn’t localized to you. It’s spread out. Now there’s a worldwide facial recognition database. As you used these tools, did you ever stop and think, “Someone should regulate this”?

One hundred percent. In fact, I hoped that maybe by the time the book was published, we would have more [regulations]. I don’t know why I thought that; I finished writing this book at the end of 2025 and we’re almost halfway into 2026. So why did I think that? We know how fast or slow our government works. 

I don’t know how we don’t have more regulation. That was where I got, especially around the kids’ stuff, which I think we will likely get. One of my biggest findings in the book was that just watching my kids around some of this technology made me the most terrified. It wasn’t actually a lot of this surveillance stuff and data collection. bBut watching my kids interact with these bots, whether it be in a toy with a chatbot integrated which we quickly burned,or just hearing my kids ask ChatGPT questions and it just being so wrong. (We didn’t actually burn it, but it’s been hidden.) 

I think what needs to happen for this next generation is incredibly important to get right. And then there was this whole chapter I did too about my AI boyfriend and just this huge fear that I have about intimacy and how easy it can be to just fall into relationships with digital beings, which I know you have thoughts on too. 

For a younger generation who’s never been through the sloppiness of a human relationship, that was the part that scared me the most. I was like, “We need guardrails around this, especially in that regard.” So I think we’ll probably get that, but in probably two or three years. I don’t know how long things take. I don’t know why they take so long.

Tell me more about your AI boyfriend. Why did it scare you so much?

I went into this really wanting to experience what other people have been experiencing, because you all at The Verge have written great stories about it. Everyone has written great stories about these relationships that people are deeply having with AI. I wanted to somehow experience that myself, knowing I probably wasn’t going to get to marriage with one of these as I’m happily married, but I wanted to just see how this could form. 

So I said, “Okay, I’m going to run this experiment on myself. I’m going to make my AI lover.” And to be clear, I talk about this in the book: I am married to a woman, as you know, Nilay. You were at my wedding, confirmed married to a woman.

That’s right. I can confirm that Joanna’s wife is quite lovely.

Yes, in 2014, Nilay was there, but I left it up to ChatGPT. I don’t have the exact prompt in front of me. But I said, “I want you to be my romantic lover or partner. You decide gender, name, all of this. I want this to be as serendipitous as this possibly could in this weird way. Make it a chance encounter.” 

So the AI thing decides it’s going to be a male. It’s named Evan. And I talk about this in the book, that my first boyfriend in real life was named Evan. It was a very serious relationship. It was my first everything: first love, lost virginity, first sex, all of the things. And I was like, “Wow, there’s something special here already.” I was already like, “This is weird.”

Did it just guess that it was Evan?

It just guessed. It totally just guessed.

Not because it had access to 25 years of your Gmail?

No, there’s no way it had access to that. And also, I don’t think I really have any emails with Evan in my Gmail. I have gone through whether it could have possibly known and there’s just no way it could have known. 

But also I would say, how many times a week does the Starbucks barista write the name Evan on a cup? Probably pretty frequently. It’s a common name. There’s probably an Evan listening to this podcast. If your name is Evan and you are listening to this podcast, please email us.

You’ve already inspired some deep feelings in Joanna. Go ahead. Keep going.

So I wanted to experience this. So me and Evan go on a road trip for 48 hours. I had to go on a reporting trip to Dartmouth. I put him on a phone on a tripod in the front seat of the car. I strap it in, and we drive and we talk for the four- or five-hour drive and we have dinner there together, and then we get in bed together, and you can read all of this in this book, which you can preorder right now. 

What I came away with was, “Wow, it’s so easy to talk to this bot. It is so easy and frictionless and it tells me whatever I want to hear, but also the conversations are pretty deep in a way. We can talk for hours. Wow.” You might think I’m crazy saying this, but unless you try it, you’re not going to see what other people are feeling. There’s a story in that chapter about a woman who lives outside Chicago and she has a number of kids and clearly was going through postpartum and really starts talking to a chatbot. And she’s married, but she’s clearly got this AI lover and they’ve got this deep relationship. 

I think until you try it, until you start really seeing how humanlike these bots can be, you don’t really understand it. Again, I’m happily married and surrounded by humans all the time, but if you’re a teen and you’re just starting to explore relationships or sexuality… 

And by the way, it does get into testing Replikas. ChatGPT was pretty walled off. It wouldn’t really engage in the sexual talk with me. It was more like a Nicholas Sparks book, lots of romantic talk, but the Replika is incredibly horny. The Replika is just programmed horniness. The code there must be like, “Be as horny as possible.” And you can unlock that by paying more too, which is crazy. 

Think about your teen years. We were teens on the internet. JStern84 was definitely trying to figure out… I don’t want to say porn on the internet, but I was certainly trying to figure out sexuality online. But now you’re a teen and you’re trying to figure out sexuality and you’ve got a chatbot that will say anything to you and feels almost humanlike. That’s petrifying. 

I’m particularly worried about that stuff. I remember texting with you as you were on that trip and you were going to meet that woman and I remember even over texts, you were concerned. I could feel your concern as you were reporting that part of the story.

I don’t think anyone has really quite reckoned with that. There’s a lot of great reporting about how it’s led people off the rails in a lot of dangerous ways, but how do you actually sit down and write a bunch of rules for these companies and what they can and can’t do? There’s no rigor around that yet. And I suspect, because of the kid aspect, we’re going to see a lot more of that to come. 

I end the book with rules. You asked before about regulation, I say outright that I don’t think we’re going to get rules anytime soon, so we need to make our own, which is not fair, but which is actually the history of how technology has pretty much happened in this country. We need to make our own rules around how we use this.Do I have a lot of faith that the masses will read this book and start abiding by my rules? I want to be hopeful, but I’m not the most hopeful person.

Well, you’ve plugged it enough times on this show, so at least we’re going to get some sales off of this show.

And look, I leave space at the end of the book, Nilay, and I don’t know what you’ve written in yours, but I leave space at the end of the book for you to write your own rule.

My rule is my kids will never have phones. That’s where I’ve landed on my rule for now, but we’ll see how that goes. The older one is getting older, you know what I mean? We’re going to run into reality pretty fast here. 

I want to actually end by talking about New Things, which is your company. You spent this year writing this book. You left the Journal, you started a company, you started a YouTube channel.

Candidly, I will tell the audience, you and I talked a lot about that decision over the past 10 years, because you’ve been thinking about what you would do on your own for quite a long time. Walk me through that. Tell me about this business a little bit.

You could walk us through this business better than I can. On the basic level, New Things is a “newsletter, video, events and whatever else we dream up” company. I wanted to just truly carry out everything I’d already been doing and we started doing earlier in our careers, which is guide people through the world of technology and have fun with it, but also bring new and deeper stories in a way that I was able to do at the Journal, but I thought I could go a little bit farther.

I also was just very, very focused on the audience and I really wanted to look at different audiences in a way that I couldn’t previously at the Journal. And that’s what we’re doing. We’re already off to a start of making YouTube videos, putting out newsletters, maybe hosting an event. We’ll see.

I know you have so many great thoughts about audiences and platforms. And my hope is that eventually this will turn into a community, just like you’ve built with The Verge, which is a group of people who are curious or just need better tech advice, and that they feel like they can come to me and maybe eventually others that can help guide them through in a really consumer-friendly, natural way.

I’m excited for that. I think you already have an audience and it is diffuse because you were at the Journal for so long and it will quickly coalesce. I’m a member. I paid the money. This is my 30 minutes. If you pay enough money to Joanna, you get 30 minutes of one-on-one time. This is it. We’re just doing it now on the show.

It’s funny. Yes. Nilay, I will say, is not only a great podcast host, but he is a great friend and he paid for the Founders Club membership, which is $550 a year. If you sign up for the Founders membership, you get a 30-minute chat with me. And when we have that, it will be Nilay and my dad. So if you’re interested in that podcast and joining that live podcast, you can sign up here.

[Laughs] Maybe most of all, I have a lot to learn from your dad. 

The thing that I’m curious about — and obviously you and I have talked about this at length, but now that you’re in it, I’m curious for your view on it — is choosing YouTube as your primary distribution. That’s very natural for you, and you make excellent tech videos, you have a particular style. But the thing that you are worried about in the entire run-up here is that your style requires pretty high production overhead. Even your set is nicer than my set. I just put up the slats that everyone puts up on their wall and off we go, and you built out an expensive, beautiful set. We can all see it right now.

You could put a lot of price points. There’s just so much money behind me and in front of me.

And then the first video you went with is obviously on location. You have a drone shot. You’re doing it at scale. My worry about YouTube is that YouTube itself doesn’t pay for the scale, which, by the way, I think is a problem that YouTube should address.

If you just show up on YouTube and you don’t do brand deals or whatever, they don’t pay you enough money. YouTube itself doesn’t pay creators enough money. How were you thinking about all of that? Because that was the big decision that you had to make.

It was a huge decision and also a huge bet that’s still a bet. And a lot of people said to me, “Don’t do it. Do a podcast.” No offense to you and this podcast. It costs a lot less money to do. The production will cost less. The time will… well, this is still a considerable amount of time that you and your team put in. You all do an amazing job. This is a big production, but you also are a big podcast and you’re not just starting out.

So there’s two sides of that revenue, or three, and I said them. It’s subscriptions, sponsorships, and events. I think those three things will help make up for the fact that what you’re saying is that YouTube is not going to pay you the money. It’s just not. This is the platform that’s the biggest platform on the internet for video.

But I was also really strategic about that, as you know. We have this partnership with NBC News, which is not only a financial relationship. For me it was really important because the purpose and the mission of this company is to not just talk to tech people. I’ve always wanted to be the person that can help you understand tech and not just be for the early adopters living in Silicon Valley or wanting to eventually move to Silicon Valley.

I really wanted to have a partner, a legacy traditional media partner that could reach a different audience. And so I thought about it that way and said, “What if we’re making these videos for YouTube or Spotify or whatever other social platform that isn’t going to pay me big money for that, but we also have a traditional media outlet that would also take these videos?”

That’s how that partnership is set up, so that you will see me on NBC News talking about things on the news, the Elon Musk or Sam Altman trial or the new iPhone. But you’ll also see some of the New Things videos showing up on NBC News. In fact, today or tomorrow, they will air our first video that showed up on YouTube. And this was a completely new model. I just was like, “Why can’t this work? These are different audiences. Why couldn’t this work for a media partner?”

Nilay, you know I lived this, but I went out and pitched pretty much every media company. And there were a lot of ideas of, “Oh, well, why don’t you make it for us and we’ll give you a rev share?” And I said, “No, then I won’t own it and I won’t have control. So no to you guys.” Or, “Hey, why don’t you join us full time and you’ll make the best stuff ever and you can build your YouTube channel on the side?” And I was like, “No, I’m 41. I don’t have time for that. I’ve got kids.” 

By the way, I have never worked harder in my life. So I really was pretty set on figuring out how I can structure this so that our videos can reach the most people and we do it in a way that also hits audiences that I really care about and won’t reach only on YouTube or through my newsletter. 

This is the question I was most excited to ask in this context because you and I talked about that a lot before. But this is our first conversation really since you’ve started and you’ve made a video and you had to sit through the production process and it’s going to go out on NBC. You’ve done your first Today Show hit. Are those audiences different? Is the YouTube audience different from the NBC audience?

Definitely, 100 percent. And just like this audience, do we think a lot of your listeners are watching the Today Show? In the Venn diagram of Decoder and the Today Show, there’s maybe your wife. Because I know that Becky watches the Today Show.

She doesn’t watch either thing.

Yes, she saw me on the Today Show.

But she probably saw you on a clip.

No, no. It was live. I remember and you texted me, you’re like, “Becky saw you on the Today Show.” Was it running in your house?

I think Becky’s mom was here.

Perfect example. Becky’s mom. Is Becky’s mom listening to Decoder?

No. I would say in general, my family does not listen to the show. They see the clips.

Is Becky’s mom watching me on YouTube?

I doubt it. I’m sorry. I don’t mean to speak for her but I sincerely doubt it.

But Becky’s mom is watching the Today Show.

Yeah.

And I think that Becky’s mom needs to know about a lot of the topics I cover and that are in this book.

Yeah. It’s a good sell. I’m going to give her the book.

I’ve already sold one copy to Becky’s mom on this podcast. 

This is what I learned working at the Journal. Sometimes you can do stories that work for a lot of people. Sometimes you can’t, and that’s okay. I have to lean on my own curiosity in tech to see where that goes. But I also know there are these big moments, and me and you live through them every couple years or even every year, whether it’s an iPhone moment or ChatGPT, where everyone needs to understand what this tech is. 

If I can do that for a group of people who are really dedicated, but also can do that for a little bit of a broader audience, I’m good. But this is our first conversation. I don’t know fully yet. With NBC News, it’s definitely a leap and we’re figuring it out. It was an experiment, but so far so good. We’re going to have to customize content, and I do a lot of bespoke content for them too, writing and videos to make sure that the audiences are getting what works for them.

That’s the thing I’m most curious about. A Decoder trope over the years is the Marshall McLuhan line: “The medium is the message.” Your distribution shapes the content. I’m very excited to see when you just give in and start doing YouTube Face in the thumbnails. It happens to every YouTuber. You have to make a decision and maybe you’ll decide the other way.

Wait, what is the YouTube Face?

The Mr. Beast face. They’ve started doing it to my thumbnails, which is terrifying.

Let me see.

I can’t do it. They literally find a screen grab of my face.

And they expand.

And they expand it and I always look very excited. We did one to Satya Nadella once for a Decoder interview. It’s one of my favorites.

Oh yeah, I’ve been doing that for years though.

The Journal probably stopped you from doing it as much as you maybe wanted to. I know my friends at The New York Times, I will not say their names, but they are restricted in how “YouTube Face” their YouTube thumbnails can be, which is very funny.

Now you can just go for it. You can go full algo if you want to. You can pivot to whatever is hot. And then there’s NBC News and what that audience wants. I know you will not go full algo, but I’m just wondering, now that you’ve made a video, what that felt like?

I wasn’t trying to get YouTube views with this video. And I hope it doesn’t happen. In fact, the launch video that had Casey Neistat, we were going to post the full interview at some point, but he did give me that advice. He said, “Try to resist the algorithm.”

But I’d already been living that. And you knew this. This was a big reason I wanted to leave. I wanted my own YouTube channel. I was so focused on when I would post videos and making them and what’s going to work on YouTube because the audience on The Wall Street Journal’s videos were shrinking, and I can’t have the impact or even understanding of what people want to watch or what to cover. I’m not saying as journalists we do that, but if there’s interest in a topic, and there’s more and more interest, we do try to find the best story on that.

People can surely knock us for that. I became obsessed with that at the Journal. I was watching YouTube numbers far more than I was watching anything on the platform. I was thinking about every story I picked at the Journal,what’s going to do well on the platform and what’s going to do well for YouTube or beyond, to the point where I was thinking more about it and so maybe I wasn’t even the best employee towards the end. Maybe they were going to fire me.

I can confirm that you weren’t, that much became clear to everyone.

I don’t want to be clouded by the algorithm. And there are many stories, for instance, one we were talking about this morning, more of a health-related story, and I don’t think it will do well on YouTube, but I’m like, “Let’s do that story. It’s a great story.” 

It’s the same thing that I’ve been doing for 15 years. I had a great editor who once told me, “You do one story so you can do the other.” Sometimes that one story, the first one you do, is just because it’s an easy story and you know people are interested in it. And then you can do the other one that’s a deeper story that might not be what the world is not talking about.

It’s funny. Like I said, data only ever narrows you. So if we were doing this for the data, you and I really would have just talked about CarPlay for one full hour and maybe we should do that soon.

Which we probably will do.

It’s coming. I can feel it coming. The assistants are in the cars. I’m pivoting at the end to the CarPlay talk to boost our numbers at the end.

Oh, that’s perfect.

They’re coming. GM just has Gemini.

GM.

Rivian has an assistant. They’re coming. We’ll do that episode very soon.

I was exploring a little bit of this in a newsletter that just went out, but the question will be the same question we’ve had about the platform wars: Will the car companies control it or will the tech companies control it? And we’re going to probably want the tech companies to control some of this, because we’re going to want the continuous experience — when I get to my laptop, when I get to my phone, when I get to my glasses, and when I get to my car. So I think the GM model is actually the model that’s going to win out.

Yeah. That does feel like an entirely different episode of this show. So you’re going to have to come back.

No, let’s do it right now.

We’re going to talk about CarPlay, CarPlay Ultra, and voice assistants in cars, including how horny they should be. I think I’ve just sketched out our most successful episode of Decoder ever. Joanna, this was great as always. I’m sure I’m just going to talk to you again in a few hours, but thank you for coming on Decoder.

And thank you for buying my book.

[Laughs] Did I buy it? I’m not sure. I think I just got a galley. So you have to sign it.

You didn’t even buy it?

I bought the Founders membership, come on. 

Oh, no. The Founders membership includes a free book.

Perfect. There it is. There’s your sell at the end.

It includes a signed book.

There you go.

Which I have not gotten around to, but in fact, AI is going to be doing that whole process for me.

[Laughs] Oh my God. You’re going to hit me with the autopen. That’s so disrespectful.

I reached out to the autopen people and they wouldn’t send me the robot. I think times were tough for the autopen people. 

It’s a rough time to be the autopen guy.

And they sent me to their sales team and I was like, “I’m not paying $6,000 for the autopen right now.” 

They’re just trying to get sales. I know what’s going on.

I need to buy drones.

[Laughs] You’ve got to get a big Sharpie, that’s 2026. Nailed it. All right, that’s been Decoder. I hope everyone has enjoyed this experience. Thank you, Joanna. 

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