Today, I’m talking with Melanie Perkins, founder and CEO of Canva, a popular online design tool.

I always enjoy talking with Melanie. She was last on the show a couple of years ago, just as the AI revolution was coming to the worlds of art and design. At the time, Canva had escaped a lot of the criticism being leveled at its competitors for adding AI tools. Melanie attributed that both to how much Canva users love the product and also the huge inroads it was making into the business world. Canva is a tool that empowers non-designers to design, and that group of people was just trying to get work done. They didn’t seem nearly as threatened by AI as professionals using other creative software — they may have even felt empowered.

It’s been two years, and it’s safe to say that AI is all over design software now — and a lot more people have a lot more feelings about AI in general. But Melanie and Canva are pushing even more aggressively into integrating AI. The company just announced a big new update that allows people to simply tell Canva what to make and have it go through various data sources like Slack and email to build presentations, documents, and other design materials. Those projects arrive as regular old Canva files, which you can edit at will. You’ll hear Melanie come back to that idea several times — having the output of the AI system be in a format you can edit, so that you can refine it, is a big deal.

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The idea here, as Canva says, is to move “from a design platform with AI tools to an AI platform with design tools.” 

I’ll let you all sit with that for a moment.

Obviously I dug into that with Melanie, as well as how she’s thinking about Canva’s relationship to the AI model providers, the cost of the tokens required to automate an app like Canva in this way, and the kinds of pricing that might lead to for users. These new AI tools are still in beta, so there’s a lot to be worked out, but you’ll hear Melanie say she’s confident that Canva’s growth in enterprise will continue to accelerate as more and more companies look for tools that automate tasks like making presentations.

But that’s the same idea as a lot of other big AI players aiming for corporate dollars, and so Melanie and I talked a lot about whether Canva is the right platform to bring everything all together. Unsurprisingly, she thinks it is — not least because she runs Canva using Canva.

Of course, I also asked Melanie for an updated vibe check on AI and design. Poll after poll shows that people really do not like AI right now, and the fears around job displacement and being overrun by slop all come to a head in a piece of creative software that doesn’t require creatives anymore. Melanie had some thoughts here as well — and I did my best to get her to talk about Adobe, which is also adding AI tools and raising prices, a deadly combination for the biggest player in the space. You tell me if I got her to bite.

There’s a lot in this one — like I said, I always enjoy talking to Melanie.

Okay: Canva CEO Melanie Perkins. Here we go.

This interview has been lightly edited for length and clarity.

Melanie Perkins, you are the founder and CEO of Canva! Welcome back to Decoder.

Thank you so much for having me. It’s great to be here.

I am very excited to talk to you again. It’s been a couple years. You were last on the show in 2024. We talked about AI and design and the feelings people have about AI and design. And I was looking at that interview again just to prepare for this one. And a lot of the themes are all the same. And then the facts surrounding those themes have changed so dramatically in the past two years. And on top of it, you have big news that I really want to dig into.

So let’s just start at the start. The last time you were on the show, I said, “What is Canva?” And you said, “Canva is an online design platform.” And your news this week is, I believe, that the company is changing its own conception of itself. Tell us about that change and what led into it.

There are some things that are changing and there are many things that remain the same. So our mission is still to empower the world to design, and we’re going to be doing that very much over the years to come. But something that we’ve always believed is that we should take the latest and greatest technology. We should build the latest and greatest technology and put that into our community’s hands and enable them to achieve their goals. And what is the latest and greatest technology has certainly changed over the last few years. And so obviously AI is at the center of that change. And so we’re really excited to be bringing the best of technology and putting that into our customers’ hands as we’ve done for the last decade. But obviously the latest and greatest technology today is AI. And so we’re really excited to be doubling down into that space.

All right. But I’m looking at a press release that says, “We’re moving from a design platform with AI tools to an AI platform with design tools.” That seems like more than bringing the latest and greatest technology. It seems like a rethinking of what Canva’s product is. Unpack that a little bit for me.

Let’s get into it. So when we launched Canva for the very first time, one of the huge innovations that we had was moving from pixels where everything was very granular and required deep expertise to be able to move anything around to be able to design anything to objects, where you could lay out a design. You could just have ideas for different objects. You could search our stock photography library, our illustration library, you could drag it onto the page, you start with a template or start from scratch, you could collaborate and design. And now what we’re really excited about is with AI, we’re moving into the concept layer. So you can just take an idea, you can write it in, and then something can get created for you. But very importantly, you can still move into the Canva’s object editor and lay things out, collaborate, edit away.

And so we’re really excited about bringing it to this third tier of concept editing, which we think will be extraordinarily exciting. So it’s our biggest launch ever and becoming the system where work happens end to end. But still very importantly with design at its core, being able to take it … I was going deep the other day into the definition of design and to design is to mock an idea. And really to mock an idea is at the essence of design. So we’re really excited about bringing new tools and capabilities to be able to do exactly that.

I have to ask you: I’m looking at the presentation about all of this. And it was obviously made in Canva. I know you told me last time that the whole company works in Canva. Did you automate the creation of your own deck announcing the AI tools or did you make it all by hand?

What’s really cool about this new product release, it can be one shot generation and that is awesome, but the really exciting thing is it’s actually also iterative. So it can lay out pages. So for example, you can take huge passages of text and then you can just lay that out with Canva AI. So you can actually be your companion, your creative partner as you’re going through the process. So we didn’t do it to just one shot generation for the entire deck, I have to say. But what we were able to do is use it for all the fine grain edits, the laying out of boxes and that sort of thing. So it really, it helped with the deck.

But I think that’s the exciting thing is that I think one shot generation is like AI 1.0 and being able to do iterative, agentic orchestration is really 2.0. So we’re really excited about that. And then turn it into the press release doc. And it’s really great at helping to create that first draft for us. And then we can use that to iterate, to collaborate because I think we both certainly know and everyone knows that that one shot generation might be a helpful starting point, but that really is the draft to then be able to iterate and refine from there.

I’m curious for this. I’m just looking at pictures of the interface. It looks like a chatbot. You can ask it all kinds of questions, as you showed off, make me a content plan, do a bunch of stuff for me out on these platforms. You can connect directly to the platforms and have it published for you.

That feels like, in particular, the cutting edge of marketing is automating the creation of assets and the publishing to platforms and collecting the data and iterating through that. But the interface is still a chatbot and it feels like maybe that’s going to be the interface for everything forever. Did you experiment with other kinds of interfaces or is it just the open end text box as the end all, be all of AI?

I think that’s where I was going through those three tiers of pixels, objects, and concepts. I think that’s what’s really exciting to me is that in most chatbots out there, you’re in a chat and you go backwards and forwards asking for the same thing and it will regenerate the entire thing over and over again. It’s annoying. But with Canva AI, you’ve got the ability to have conversational editing, which is extraordinarily powerful and brings completely new capabilities. But then you have the normal Canva that you know and love, where you can just drag and drop, you can collaborate, you can do all your iterative editing, you can go and change a word here and update that and not having to prompt to do that. So it actually helps to make complex things simple by bringing it all together into one spot.

You’ll see in the interfaces, Canva AI, it’s a brand new tab inside the editor. And so you can go there, you can dictate into your phone, you can do it on the fly, get that first pass, and then it’ll lay it out just in the normal Canva that you know and love, and then you can just edit that as you would typically do. So after a lot of experimentation, that was where we landed, that it’s so powerful to be able to dictate for everyone’s different accessibility needs, even accessibility needs on a day to day basis. Sometimes now I can just be talking to my phone, ask it to generate something and you can just do that on the fly, but then that creates a normal Canva design that you can collaborate, you can edit, you can use our hundred million plus stock photos and illustrations and drag and drop and design that. So really, the huge opportunity is this end to end workflow of being able to take an idea and turn that into a finished, usable work in one seamless platform. Yeah.

Can I ask just a question about the relationship of the AI to the tools in Canva, and I’m going to basically just do personal tech support with you.

Yeah, go for it!

So I used Canva this week. My daughter’s having a detective themed birthday party. And so we took photos of all her friends and we’re going to make wanted posters.

Awesome.

I was like, “I’m going to talk to Melanie and I better use Canva to do this.” It seemed very natural, so I could ask you very weedsy tech support questions. And just in the version of Canva that I was using, it was clear that the AI tools operated in some places and not others. They weren’t seeing the whole Canva tool palette. And very simply it’s background remover, which I believe is one of your most popular tools. It’s everyone’s most popular tool. I could do it in some parts of Canva, not the other. I couldn’t look at my finished layout and say, “Actually, can you just go ahead and remove the background from this photo?” I had to get to where I needed to be and then ask the question. Is the new Canva AI, can it address the whole set of tools? Is it using Canva as a whole or is it still narrowly sliced?

You hit the nail on the head with what we were doing with Canva AI 2.0. You were using Canva AI 1.0. I’m very excited to get your hands on Canva AI 2.0. We’ll have to get you into the million, because it’ll help you with exactly that. And so you can say for your example, for your wanted posters, create me the wanted poster. And you can upload the photos and it can actually orchestrate all of the different tools in Canva to be able to create that on the fly, without you having to go to the different spots. But you can still go and edit the different particular parts, the element editing if you want, but it actually is able to orchestrate it and then create a layered file in Canva’s standard format.

I think I understand how the user will see it. Architecturally, I’m very curious how you build the product that way, because it doesn’t seem like there’s some industry standard way of saying, “Now you can use this software.” About half of the attempts I see are just taking screenshots of everything and very slowly clicking around. And there’s an infinite number of variations on that approach. There’s the MCP approach, which everyone was really high on and seems to have arrived at whatever point it’s going to arrive at, and now maybe half the industry is back at, well, we should just do APIs. What approach did you land on?

I think the reason we’ve been able to make so much progress in this space, firstly was the decade of investment in this interoperable format. So being able to have this design format that spans presentations and whiteboards and docs and videos, the full gamut has been a really powerful part of why, when we launched the foundational model, the design foundational model, it actually is able to create across all of these different formats and is that layered file. Which means that you can operate at a full design level, you can operate on a page level, you can operate on a photo level or text. And so the huge investment in that space is why we’ve been able to bring this to life with Canva AI 2.0. And there’s an extraordinary amount of complexity behind the scenes.

We’ve had hundreds of people working on this project for some years to get to this point in time. But I think that the really important part is one of our engineers described it as an orchestra because there’s so many tools and systems under the hood that need to talk together to be able to bring that thing to life. So when you say, “I want to create a wanted poster for my daughter’s birthday party,” it will then be able to go and use background remover. It will be able to go and use all of the different tools to be able to assemble that. But from a user standpoint, they just get to say what they want and then we go and do the hard work to achieve that goal.

I’m just curious what bet you made there, because it feels like the industry is not coalesced on a strategy. So is it actually clicking around Canva or is there some other way of the AI addressing the tools?

I won’t go into technical detail there, because I think that we have had a few breakthroughs that made this all possible.

The other question I have is who the model providers that you have doing this are. Because we are hearing every single day that token use rates for agentic software through the roof, or watching Anthropic have to modify its pricing. There’s all kinds of stuff happening in that world, and you’re launching an agentic AI product that, just from the interface alone, makes you want to use it a lot.

I’m happy to hear that.

And Anthropic literally has, in Claude, there’s a usage meter and it will tell you, “You’re done now or pay us more money.” Are you going to have a token usage meter in Canva in the same way?

You asked so many questions in that very short space of time. 

There’s more to come, don’t worry.

We have been investing in the areas that we really need to. Becoming domain experts in design has been a really critical part of our research strategy, but then partnering with incredible companies that are spending billions of dollars to build the best in their own areas and then bringing that technology onto Canva is also a key part of the way we’re approaching this, being experts in design, because that’s where we really need to specialize because there isn’t great technology in that space. And then we’ve got a 100-person research team working very specifically on these problems themselves.

On the AI credit front, we have different tiering available for each of the different packages. So in free, you get limited credits and then in pro, we get much more generous. And then in our business package, you get far more generous, then enterprise even more so. But actually for the first million users, we’re giving everyone an AI pass, which we’re really excited about. So it’s a $100 monthly pass. We’re going to be giving everyone in that first million so they can just go completely wild and test out all of these new products. So we’re really excited to see how that is used and see where it takes them.

I want to come back to pricing, because I have a lot of questions about it, but first I just want to understand the product a little bit more. The last time you were on the show, you were making the inroads to enterprise. You would relaunch for enterprise and we talked a lot about how what you needed to do for enterprise was not necessarily product focused, but just workflow focused. You needed user authentication systems and management systems and dashboards and all that stuff, and you built it out. And that seems to be going really well. I think the numbers I have here are you’re at $4 billion in annualized revenue, $500 million of which is enterprise. So in two years you’ve grown. Is that the part of the business that’s growing the most?

The whole company is growing very rapidly, but yes, enterprise has been growing extremely rapidly. We grew by 100% over the last year, 95% of Fortune 500 companies and getting really deep footprints with thousands of people at companies now, which is extraordinary to see. We think that with Canva AI 2.0, we’ll radically change that. It will be a huge step change again, and become the system at the center of work and really bring things together.

I think a lot of people can relate right now. It feels like there are a lot of fragmented systems, things that are in lots of different places. We think being able to have that all on one platform, all of the work and all of the designs and presentations and documents, all in one place and with connectors being able to go even further and pull in context and information from your Gmail or your Slack, is going to be a huge step change for the way work gets done.

That’s the part I’m really interested in, the idea that a company is just a collection of disparate databases that are not well organized or managed and that there’s truth in those databases, if only we could read them all at the same time. That’s a big part of the AI thesis in general. You hear it all over the place. I work with a bunch of cranky reporters. I don’t think they put all their ideas in the databases, but I get it. There’s a sense that there’s a lot of opportunity in the disparate data sources in a company and you can bring them together to platform and then take action on it and achieve some results.

Is Canva the right tool to do that work? You’re right up against Claude. Or you’re right up against, I don’t know, Oracle, whatever big enterprise business process automation vendor is going to say, “AI will connect all your databases,” and then there’s Canva. And I’m wondering if you want the whole opportunity or just the design opportunity.

Well, to me, design, as we’ve just talked about before, is bringing creativity and productivity together and being able to do that in a way that we think is pretty extraordinarily powerful. I had my own experience of this the other day, which blew my mind. I had to answer a whole bunch of questions that were going into all sorts of different questions over the last decade. And then I was able to just type it into Canva AI 2.0 each of the questions and I was able to construct answers based on all of my designs and all of my documents from the last decade.

And it blew my mind that I was like, this is the only place that actually has this information about me. And so being able to have that full visual suite from docs to sheets, whiteboards, presentations, all of that context. And then I guess the other thing is that, when you think about it, most things end up in a design format of some description at the end of the process. And so being able to have all of that context right there beside the AI tools, we think is pretty powerful.

I think that the thing I’m curious about is where the primary interface for that lives. And you’re obviously making the case that it should be Canva. For the CEO of Canva, it clearly is inside of Canva, but I could bring the CEO of Slack on here and they would happily tell you that that is Slack. Or I don’t know, Microsoft will tell you that they’re going to force-feed Copilot to you wherever you are, using a Microsoft product and that’s where that should be. There are a lot of ideas about this.

One of the things that makes that messy, in my mind, is that all of these products can now talk to each other in very specific ways. So Canva itself is a plugin for the other chatbots and it seems like the usage of that plugin is very high. How do you think about who owns the interface in a world where the core tool set might be usable somewhere else entirely that also has access to all that data and all that information that the company might have generated?

The key focus for us is always: How do we empower our community the most? How do we help them to achieve their goals? So we’re already embedded in organizations and businesses all around the world. And when they’re creating a design today in Canva, it’s quite a manual process. You have to go to all these different fragmented tools, collect all the information. And so being able to have that just inside the design tools, we think, will make a great deal of sense because it means that you’re not… It’s just cutting down manual and busy work, which is always the thing that we’re doing for our customers. Like in 2019, we launched background remover and the whole point of that was you click the background remove button and then the background was removed, and that reduced a lot of manual work.

Again, with this release, it’s the same thing. There’s a lot of manual work to go and collect all the information, collect all of the context, all in different places. And so having that just there where you’re designing, we think, makes a lot of sense, where you’ve already got huge repositories of your images across your company, where you’ve already got all your brand templates, where you’re already doing the collaboration. We think that makes a lot of sense. But really, we just want to be putting the tools that help to reduce busy work in the hands of our community and helping them to achieve their goals with less clicks.

A few weeks ago, we had the CEO of Okta on the show, Todd McKinnon, and he was like, “The future of Okta is managing agent permissions because this is a security nightmare and I will sell kill switches to every enterprise that has agents running rampant over its networks and databases.” And so I hear what you’re saying. It’s like, okay, Slack is going to have a bunch of agents that can go talk to Canva’s database of images. Canva will have a bunch of agents that can go talk to Slack’s database of conversations, something else is going to happen over here. Does that seem like a workable picture of a company of the future, where all of these tools are accessing one another independently or do you think it will naturally land on just one?

I think the cool thing is, for consumers, there’s going to be choice about how they want to have their work stack set up. And I think it’s a really exciting time in technology because there’s just so many new possibilities for the way work gets done to reduce fragmentation. We’ve got a quarter of a billion people using Canva today, so we think there’s a huge opportunity to make AI simple and accessible, just like we did with design, but very importantly, helping to empower people to achieve their goals and to communicate their ideas. So we think we’re pretty excited about what we’re going to be able to bring out into the world.

How does it work for you? What’s the dynamic inside of Canva? Obviously you’re on the bleeding edge of this technology and you obviously have your own tool. How does it work for you? Do all of your tools have AI access to all the other tools? Or do you work only in Canva and let Canva AI go talk to all the other tools? What’s your setup?

Obviously Canva’s always had all my designs and my presentations and my documents, but being able to get connectors and being able to pull in information has been pretty astonishing. So for example, being able to say, “Hey, create me a plan for my next week and how I can optimize my time.” And it being able to go and read my calendar and then create me a document about my upcoming week, it was like, “There’s a lot going on.” It told me I had a massage booked and I was really surprised about that because I didn’t actually know until I read that in my Canva doc. And then I was like, “Oh, I think there’s a bug here,” and then I realized that my partner had organized that.

The bug is, it’s booking self-care for you whenever it wants.

And so I think it’s really cool because there’s a lot of things that would be very manual, like going and doing a calendar audit, and that all of a sudden can actually just happen inside the one thing and it can actually create the presentation or it can create the document and then you can have people collaborating on that as you go.

People talk about AI slop, and I think the AI slop is often one shot generation, you just take that and you put it somewhere else. I think what’s really exciting with Canva is that that’s really just the draft. That’s the starting point. And then you can use it to iterate, you can use that through manual editing or you can use that through being able to iteratively edit through Canva AI inside the editor itself and to refine it to really be able to clearly articulate your idea. So we’re pretty excited about the possibilities that it unlocks.

I feel like it’s time for the Decoder questions, because you’ve talked about how much you use Canva internally. The last time I asked you how you make decisions. You said you had a process called decision decks, where you literally made Canva documents with all the pros and cons and you mocked up the products. Is that still the process?

That is still the process. Prototyping has become a very key part of it. So often now there’s a workable prototype before anything gets launched. I think the really fun thing about, I don’t know if I talked to you about the complex decision making framework.

No, this is new. 

Okay. Well, this, for anyone that needs to make complex decisions, I find this extremely helpful plitting it out into like, what are the goals, then what are the options, what are the pros and cons for each of the options? But it’s really fun because now we have a template inside Canva, which is the complex decision making framework doc. And you can literally just dictate using dictation through Canva AI and it will actually go and fill out this template. So there’s a lot of really exciting ways you can take your ideas and the thoughts in your head and then have that distilled in a way that other people can see and understand, which I guess is the essence of design.

If you think about design in the sense that previously, design can sometimes be thought of as making things look pretty, but really design is about expressing ideas and being able to communicate that effectively and being able to turn something from an idea into reality. And so we think all these new tools really help to facilitate that. I use Canva Code all the time. I used to do a lot of mockups and now I use Canva Code to create prototypes all the time for every idea that I have, which is pretty powerful because it takes the idea far further than it could before.

The other Decoder question is how the companies are structured. Last time, you were about 4,500 people and you described your structure as a very centralized product team and then lots and lots of local teams. And the metaphor you used was a cupcake and you said, “We work on the cupcake and we make the cupcake bigger and all the local teams work on the icing.” Is that still the metaphor?

Yeah, that’s a fair metaphor. That one’s been around for… The cupcake and the icing is actually so applicable in so many different ways. Small empowered teams are really the essence of how we get things done. And we’re very much a goal-oriented structure.

So for example, with Canva AI 2.0, we really brought everyone together across the company to achieve that goal and bring Canva AI 2.0 out into the world. We do show and tells every week so everyone can share and get deep context on what’s happening. I think that “goal” has really been the essence of how we’ve achieved anything over the last decade, being able to rally around goals and have different team formations in order to achieve that.

How many people is Canva now?

Latest stat, about 5,000.

So you’ve been growing. I’m really curious about, just in that context, decisions and structure, how you made the decision to say, “Okay, we’re going to do Canva 2.0 and we’re going to lean heavily into AI the way that we’re going to lean into AI.” That’s a lot of people. It’s a big decision. I imagine that there was a decision making slide or a deck and then this feels like it inherently is a top-down decision. We’re all doing this. Melanie says we’re all doing this, we’re all doing this. Walk me through that decision and walk me through any structure changes you had to make in order to accomplish it.

Yeah, absolutely. So I’m going to take us back to 2011 and to a deck that we had, which was called Canva’s Chef, before Canva was even called Canva. And the first slide, when you go onto it, it’s like, “What do you want to chef up today?” And then you could type into a search box and the idea was you could type whatever you wanted and then you’d pop into the editor and you could collaborate and you could have the editing tools. If we shared it with you after this, you’d see it’s bizarrely similar to what we’re launching today. So I guess this has been the dream for a really long time, but the technical ability to do this has been… hard. I’d say in 2017, we had this document. We called it Getting Smart and we’re like, “In the future, future, future, there’s going to be search-driven design. Rather than going to the buffet and getting something, it’ll be able to happen on the fly, like a chef cooking something up from the raw ingredients.”

And now it feels like we can actually do that. Back in October, we’d been researching this space for some years with the foundational model that was a huge step, the design foundational model, that was a huge key piece. But then in October, there was a significant breakthrough in the company that meant that we could actually do it. So as soon as we saw that, we were all like, “Oh my goodness, this is really exciting and groundbreaking for what Canva can unlock.” And so that was when we really started to go all-in and realize that that technology needed to be pushed as far as it could go, which is what we’re launching today.

Did you send out an email? Did you send out a Canva deck saying, “We’re doing this now, decision made?” How did that work?

That is a great question. So there was a team working on it already, and then we really bolstered up that team. So then we said, “Okay, we need to get every single person that can possibly help bring this to life onto the project.” We started the weekly show-and-tell’s, and we turned it into a more of a centralized AI team with hundreds of people. It went from a smaller team to then many hundreds of people to bring it to life, with everyone working on the different parts that needed to become part of this orchestra.

I’m curious. That structure part seems really interesting to me: “We have a software tool, a standard deterministic software tool with a select box and all that stuff, and we’re going to build an AI that can use that tool. Now we’ve got to take all the engineers we had and point them at that problem.”

Did you have to rethink your product team, or did you just make the team that was working on that part larger?

I think a little bit of both. Once the team had this big breakthrough, and we all saw it in action, we said, “My goodness, this is the coolest thing ever.” We then had to figure out who could actually help from across the company. I think that’s the goal-oriented structure I was mentioning before: when there’s a goal, you need to figure out who are the people that can help bring this to life. And then we were doing a weekly show-and-tell so everyone could get a really clear understanding of where everything was at and all the pieces that needed to be orchestrated to come together.

I think Canva already being interoperable meant that there were a lot of these things that had already been built and that then could just come together in an exciting way. We do something called the Canva jigsaw. We’ve been doing different variations of the Canva jigsaw since the earliest days, which is often a goal and then all the pieces that need to be worked on independently to be able to bring that to life. That was exactly what we had at the center of this project again.

You’re fundamentally a software CEO. I think that’s a fair description. I think you make software. The nature of software development itself seems to be undergoing some kind of existential crisis. One of our designers here at The Verge and Vox Media described all software development now as calibrating yourself to a database and just talking and seeing what happens and maybe that’ll turn your brain to mush. 

Are you using as much Claude Code or Codex to make Canva, as it seems like every other company is racing to do?

Yeah, I use Canva Code really extensively from the perspective of–

When you say Canva Code, that’s your own coding product? You’re not using Claude Code or Codex?

Yeah, because it’s so cool. I used to create mockups all the time. Anytime I had an idea, I would create a mockup. And now anytime I have an idea, I can use Canva Code. But with this latest release, you can actually go in and edit the text. So you can actually code something, you can edit the text, you can drag and drop, you can move things around. We’ve been really investing heavily on the AI front and upskilling our team.

So can you make Canva with Canva Code?

Yeah, we do make Canva with Canva Code, not deployed. We have many incredible engineers that actually make it sound to go out to hundreds of millions of people, but we use it for prototyping all the time.

Yeah, I think the question I’m asking is more about those folks and how you think about the costs associated with those folks. The nature of software engineering is changing in some big, meaningful way due, in particular, to the coding tools that are available. 

Are you rethinking how that works inside of Canva, as you ship new versions of Canva? Because for every other software CEO I talk to, their minds are exploding. They don’t quite know how it’s going to go, but they know it’s definitely going to change forever.

I think one of the things that we’ve invested really heavily in is continuously upskilling our team and systems. So we’ve taken a very intentional approach to give all of our team access to all of the latest and greatest tools. So we actually have not selected a winner. We have just given them everything. And it’s been very intentional because we want everyone to be playing with the latest and greatest and to be upskilling all the time. We need to be upskilling every one of our systems.

We need to be upskilling because the way we build product is completely different today. The way we do [quality assurance] is completely different today. The way we do actually every system and process inside the companies had to have an AI-native transformation. And so every specialty inside the company has had to have an AI-native transformation — what a designer does today, what an engineer does today, across every single part of the company.

So it’s been a huge area of investment on the tooling, on giving our team time, and on the specialties. We’ve had this focus on AI everywhere and then AI impact and now AI-native because we really want to be rethinking everything in this AI era.

There’s some rebalancing of power between product managers, designers, and engineers because AI lets them all do each other’s jobs. Where have you landed on that inside of Canva?

I think we’re all here to build the best experience we can. I think having really solid expertise has never been the best way to build product. In fact, great PMs often think about things from a design perspective. Great engineers often think about things from a design perspective. So really, it’s about the team that is there to just create the best thing possible. And having people in their separate siloed, isolated lanes and saying, “That’s my territory,” was never a great way to build product.

With AI, it’s really leaning further into that. It’s everyone thinking about what is the best product experience that we can build. And everyone will bring different skills to the fore. So a designer will obviously have a certain expertise, a PM will have certain expertise, an engineer will have certain expertise, but we’ve always thought of it as a bit of a team sport where the best idea should be winning and everyone should be collaborating to create the best outcome that they possibly can for our community.

So I understand this positive case for AI, and why you made the decision. I understand that the product promise of just “tell this box what to make and it will make you a first draft and you can go on from there,” based on the data you have. There’s a pretty significant downside to AI, particularly as it relates to branding.

There’s polling here in the United States, at least, that basically is just bad vibes around AI. The last NBC News poll that we are constantly citing is AI is polling under ICE in terms of favorability and just above the war in Iran. That’s not a great place for AI to be.

People are voting against data centers in their communities. AI is widely associated with job loss and maybe now you’re going to cause some enterprise job loss because social media teams don’t need to be as big as they needed to be anymore. There’s a lot of layoffs that are being blamed on AI across the board. 

You’re leaning into AI with Canva. You’re rebranding the whole product as having AI in it. How do you think about that downside risk, that people don’t like it? The more they’re exposed to it, the more they’re saying, “Wait, stop. I don’t want this around me.”

I think it’s like any tool. It will be whatever you want it to be. And so if you want it to help empower people, if you want it to help deliver better experiences for your customers, if you want it to uplift students and to give them great quality education materials, it can do that. 

Wait, can it do that? I’m actually not so certain about the student thing.

We launched something called LearnGrid and LearnGrid enables, across many countries, to be able to have the curriculum aligned content created. That can be worksheets and immediate feedback. So we’re really excited about being able to put these tools in teachers’ and students’ hands around the world. 

We’ve got 100 million teachers and students using Canva today, but the access to great tools is very divergent, depending on the wealth of a school, for example. So we’re really excited about being able to bring that accessibility to students around the world.

Right. But I think my question is more about slop, right? People are experiencing the tools that exist today, and maybe mostly they’re experiencing the free version of ChatGPT or whatever AI Overview Google puts in front of them, running on the cheapest possible model at the biggest possible scale. And they’re having these experiences. I know that the industry likes to say most people have never used AI and certainly no one’s paying for it, but like a billion people have used ChatGPT and then the polling is the polling.

I’m just wondering how you’re thinking about communicating this is an AI product because, to me, it feels like it comes with all kinds of baggage. I’m watching OpenAI buy TBPN because they think they have a marketing problem. I’m watching all the venture capitalists say, “The media is lying about AI and it’s going to change everything for the better.” 

And then you’re racing into being like, “Canva’s AI now.” I think you know that a bunch of designers are going to be very unhappy about this. There’re some people who are going to just say, “This is bad. They’re ruining the product.” I’m just wondering how you are thinking about navigating that balance.

I think there’s going to be a plethora of opinions on any topic. What we always do is just put what our community wants and needs at the center of it. So we’ve had a lot of people asking, even yourself quite specifically, like, “I’ve got this goal. Why can’t Canva AI just know everything about it and be able to help me with that first draft?” So helping people to achieve their goals is always going to be at the center of what we do and that’s exactly what drives these sorts of decisions.

It is about being able to take out a lot of the manual work from being able to create and lay things out. So I really believe that AI should accelerate your vision and creativity, not override it. I think that it’s really important that AI is just another tool in our toolkit and it will help achieve our goals, if we choose to use it. So we’ve been really intentional about the product design, like Canva AI is a new tab. So if you just come in and you love templates, you can use that. If you come in and you just love the elements and just creating things from scratch, that’s totally fine. That’s totally cool.

But if you want to be able to express an idea just by dictation or through typing, you can do that too. So I think it’s really important that we understand that every one of our community members is at different stages and different scales of comfort with AI. We want to be making sure that we’re helping to facilitate that. So I think this is the full spectrum and it’s really important that Canva isn’t turning into a chatbot by any stretch of the imagination, but if you do want to be able to just chat to something and have it help you out, you can do that too. So it’s about really enabling all of that. 

I can’t speak for other companies out there in the world. But Canva has benefited greatly from an incredible community. We’ve got a quarter billion people that use Canva each month. There’s a lot of love for our product. I think that that love really comes from being able to have Canva be the thing that helps people to express their ideas and turn that into reality. We take that extremely seriously. So with all of these product developments, we are continuing to keep that at our core and empowerment is such a critical principle for us that is very much through everything that you’ll hopefully be seeing and touching very soon.

Let me ask you about the competition because you’re describing goals and when I talk to executives and they describe goals and what people really want, you often realize you’re talking about business software. Your enterprise is growing for you and this very much feels like an enterprise offering to me. You’re going to connect to all these other systems and you’re going to get some work done and you’re going to do work.

That’s what this feels like to me. And I know Canva has a big consumer base and a lot of people have fun with it. This feels like a work product. Is AI fundamentally enterprise software? To me, I don’t think that people yearn for automation in their personal lives. I think you want to get rid of busy work at work so you can do something more important and a lot of work is inherently repetitive and AI just makes a lot of sense in this zone. Do you think AI is fundamentally enterprise software?

I think you’re right. Canva AI will totally be the system at the center of how work gets done, but that doesn’t mean that if you’re creating those wanted posters for your daughter’s party, you can’t be like, “Pull the invite list from the party coming up.” And just wanting it to connect to that.

This implies that I have good access to the database of the eight-year-old girls coming to my house next weekend, but I’ll grant you that.

But yeah, it often will be about work and work means many different things to many different people. So work can mean a teacher in a classroom, work can mean at a large company, work can mean a small business trying to just get their marketing collateral created. I think we’ve shifted away from broadcast communication, where everything is one to many, to maybe having a hairdresser be able to send out a campaign on someone’s birthday to say, “Here’s a special voucher for your birthday. We have that particular thing that you like.” Being able to have that much more personal communication, I think is another aspect.

It does feel to me like the cutting edge of social media marketing in particular is automation in this way. I probably watched more TikToks and Instagram Reels of social media managers explaining how they have built incredible dashboards using AI tools, and automated entire workflows and built content pipelines. You can see it. There’s something very important happening there. Presumably Canva will participate in that and they will build those tools inside of Canva. 

Right next to that is Meta itself and TikTok and YouTube, which are all working on tools exactly like this. Mark Zuckerberg last year — I’m just going to read you this quote — said this to Ben Thompson: “In general, we’re going to get to a point where, if you’re a business, you come to us, you tell us what your objective is, you connect to your bank account, you don’t need any creative, you don’t need any targeting, you don’t need any measurement. You tell us the results you want and we will give them to you. You expect to be able to read the results that we spit out.”

That’s a redefinition of advertising. They’re describing, to some extent, your product. You tell it what you want to achieve and AI is going to make a bunch of creative and schedule it across their platform. I know TikTok is working on this. I know YouTube is working on this. They all see this thing that they can sell to their biggest clients, their advertisers. How do you think about competing with the platform’s own native capabilities that look a lot like what Canva’s trying to make for marketers?

It’s actually funny. Back in 2012, we had this pitch and we called it the design engine. And we said all these other platforms are going to have tools and they did. Lots of companies have lots of different tools for a specific platform, but it’s annoying because as a company, you probably want to be advertising in lots of different places. You probably want to be having your pitch decks and your docs and all the different things and you don’t want to have that fragmented across lots of different tools and systems. 

So Canva is everything in one place, rather than having to go and have your knowledge in lots of different places. So that’s, I guess, one of the key things that we’ve been leaning into for the last decade is that Canva can be that thing that is at the center of your work.

So the back and forth there is these platforms either have bad analytics or are not very generous in sharing their analytics or make you pay extra to access their analytics. Meta obviously has its own models. Google obviously has its own models. They might say, “Look, if you want to run this creative, you have to make it in our tools. If you want to use this stuff, we will throttle you if you come to us with creative made elsewhere. We’re going to push you towards our tools. So you use our models and we get two bites of the apple on token pricing.”

I’ve heard this from a bunch of AI CEOs, that database access in general is going to become a new pricing vector. We’re going to charge for tools. If you want to connect to our system, the customer will have to pay some higher access fee. Have you seen any glimmers of this yet or is it too early to say?

I’d say, A, it’s too early, but B, I think that hopefully the customer wins out of all of this. 

That’s very optimistic.

Hopefully the customer is able to achieve their goals and use the tools that they want to use. I guess at the end of the day, why I’ve been so infatuated with design is that design is imagining the future and then willing it into existence. And so, design really radically helps that process. You mentioned optimism. I think that’s why I love design so much is because you do have to imagine the future that you want and then you can work to bring it into reality.

The reality is Mark Zuckerberg exists and he’s very, very, very competitive. There’s also that piece of it. 

I think they also like money. I think from our experience, they love to have creative because creative is the blocker.

[Laughs] Did you say they like money? I heard you. Well, I mean, look… I know a lot of social media people who take it as an article of faith–

[Laughs] Let me give a little clarity on that. They’re not going to stop advertising. Their company is built on advertising, so they’re going to want to take creative from wherever to have it on their platform. In fact, the lack of companies being able to create great advertising materials has been a huge blocker from people being able to advertise on their platform. And so I don’t think they’re going to be sad about creating it in Canva.

I’m curious how this one plays out because the other thing that I see at Meta doing is investing heavily in AI themselves. Every week, Zuck has spent another $200 trillion hiring three AI researchers who are going to build him the best model. Who knows how that will pay off. The same way who knows how any of this will pay off.

But one way it could pay off is for Zuckerberg to say, “If you want to buy advertising on our platform, you’re going to generate it with our AI models. And because we own the model, we can charge you less than Melanie, who has to go buy tokens from someone else and pay their margin and pay her margin.”

I know a lot of social media managers who are fully convinced that they need to make their videos in Instagram’s Edits app because Instagram will promote it more heavily, even if they’re not actually making the videos, even if they’re just feeding it through to get whatever little metadata that says “Edits.”

Maybe that’s true and maybe it’s not, but the perception of Meta as a platform, the perception of YouTube as a platform, is that they will self preference in this way. So if they’re also the model providers and they can have lower pricing and the perception of self-preferencing, how do you expect to come up against that?

Let’s check back in a few years.

Okay. I thought that’s what you would say, but I just see it coming. Especially for Meta, which has to find some way to make money with the models they’re building. As of yet, I don’t know what it is except for maybe they’re doing Reels targeting on GPUs.

I can’t speak for them and their business model, but I can certainly say, from a customer’s perspective, being able to create all of the content that you want in one place, having little friction between that, being able to deploy into lots of places is what we’ve been specializing in for, I’d say, the last decade. And certainly being able to take that to other platforms has been great for our customers, but then also great for the other platforms because then they’re able to have all these people that can do their marketing on those platforms.

The last time we talked to your model provider was OpenAI, I believe. Is that still the primary partner?

We partner with OpenAI and Anthropic and then, of course, our own internal models. We love to collaborate with everyone.

Are their models interchangeable? Or do you use them for specific tasks inside of Canva AI?

We always take the best model for the best task, continuously. So it’s been great to have so many great partners in the space, from Google to Anthropic and OpenAI.

My sense of the situation is that every token costs the big company’s money, that they’re all subsidizing token use. At some point that’s going to turn, right? They’re going to want to make a penny of profit on every token. What does that do to your pricing when that happens?

Investing in our own models has been a really core part of our strategy and we were able to bring the cost down, the latency down. And the price is being driven down radically. If you look at the price of LLM queries, it’s gone down 50 times in the last three years. So it’s pretty exciting from that standpoint of having so many big companies racing to provide the cheapest models.

When you say your own models, actually, are you in the fight for GPUs? Are you training them on someone else’s cloud? How’s that working?

Yeah, it’s been a really important area of investment, which is why we’ve got our own research team of 100 people that are investing in the areas that we need. So for example, I was mentioning the design side — like Magic Layers was from our own research org. It’s been really exciting to invest in the areas that other companies aren’t.

We don’t need to go and compete in areas where there are billions of dollars of investment already happening, but in the areas that we know we can give great advantage to our customers, we certainly do that. So Magic Layers lets you now take any image from wherever you might generate it into Canva and then it will actually split it out into layers, so you can just edit it like a Canva template, which is pretty exciting.

Does Magic Layers happen on your models or are you going out? 

Yeah, that’s certainly our models.

That’s really cool. When you’ve made the decisions to invest in your own models versus going out to other providers, is there a cost performance ratio? How do you make that decision? Because investing in your own models is expensive.

It is expensive, but for example, Magic Layers has had eight million uses in the four weeks since launching. It really hit a pain point that people had, which was that you generate something and you have to go and reprompt the LLM over and over again to be able to do it. So being able to just go in and make that tiny little text tweak or to be able to collaborate or whatever it might be has been really important.

So I guess every time we’re choosing a model, it’s about “what is the best in the world?” We want to have price brackets for each of the different areas of our company. So you’ve got different models, you can choose your premium models or you can choose standard models. So we are domain experts in design and visual AI. And so that’s been really the focus of our research and development.

You said you don’t want to talk about your competitors, but I want to wrap up by talking about your biggest competitor. We spent some time on it the last time you were on the show. 

I’m actually curious, I don’t even know who you’re going to name. Who’s our biggest competitor?

I think it’s Adobe. I think in the world of creative software for professionals, it’s obviously Adobe. And maybe Canva’s more consumer than that. Who do you think your biggest competitor is?

I shouldn’t have opened that question up, should I? I should have let you go on–

[Laughs] You walked right into this.

I know, I know. When we set out years ago, we were like, there’s this huge gap in the market. There weren’t tools that enabled easy design and that were rapid and enabled creative freedom. And I think that that’s exactly what we want to do, with Canva AI 2.0 bringing creativity and productivity together, being this place where you can get all of your work done in one place. 

I don’t really think of them as competitors. There are our community of a quarter billion people that we need to satisfy and help them achieve their goals. We really focus on running our own race and filling the gap in the market. 

No, but you have to answer. Who’s your biggest competitor?

Who’s our biggest competitor?

You can’t say no one. You can’t be a $4 billion company with no competitors. That’s not a choice.

I think the way we think about it, it would be actually a bad business decision to be like, “You know what I’m going to do? I’m going to go and create this product that another company has created.” That wouldn’t make any sense. We literally go in and we say, “Where is the gap in the market? Where are users currently having friction?”

I like what you’re doing, and I appreciate it and it’s very good, but it has to be someone. Who do you want to take market share from and who might take market share from you?

I don’t know that I have a great answer for you. I think there’s a lot of fragmented tools right now and having that in one place, I think, is going to be the gap in the market that we fill.

Were you born this way? You’re such a pro. It’s very good. It’s incredible. I’m impressed. 

You can name some. Who do you think? I’ll let you say whoever you think.

I do think it’s Adobe. And specifically, when I think about the Canva community, it’s a lot of people who need to make something as consumers or as a one-off at their company and they graduate to the full suite. I think we have talked about that journey for a lot of folks. And when I was young, getting my first legal Photoshop license was a marker. And I think that is still a marker for a lot of people. I think Premier is a marker for a lot of creators, being able to afford that software.

I think Adobe is a different company, and maybe you don’t think they’re a competitor, but they occupy the same space for a lot of creatives, in a lot of ways. Their products line up right with yours. You can prompt Photoshop in exactly the way that you were talking about prompting Canva, and Adobe will tell you that its PDF business is the best business database that has ever existed in the history of the world, and they’re going to line it all up. I know what they’re going to do.

One of the things that I think is the most interesting, when I line up these two companies, is, in general, people love Canva. I think that, on balance, is true. I’m very curious to see how that goes once you put AI in front of everybody.  I think that there’s some risk there, and in general, people are really mad at Adobe all the time. That is just the nature of those two companies, the way they’re situated right now. 

So I’ve got to ask you this. Shantanu Narayen is leaving Adobe. He announced he’s going. We don’t know who the new CEO is going to be. Who do you think the next CEO of Adobe should be?

[Laughs] I definitely can’t comment on that.

Yeah you can. Should it be you?

No, definitely not. Maybe you can, but then we-

No. Nobody wants me to be in charge of PDFs in the world. You don’t want that at all. But I’m asking, if you’re looking at this, there’s a leadership change coming. Do you see that as an opportunity? Do you see that as, I will say, your competitor, retrenching? But I’m curious how you are perceiving that changeover there.

Honestly, we really have been pretty busy just focusing on our quarter billion users to try to make sure that we’re putting great products in their hands.

Very good.

I just genuinely haven’t given that any consideration.

Really? No one sent you a text, like, “He’s leaving”?

I was aware of it, but it’s not where my mind is focused. I’ll give you the way I think about the world. I always think it’s an internal locus of control and external locus of control. Things that you can control, that actually have an impact and then things that are completely outside your control. I really focus on the things that are within our control and that’s delivering a great product to our customers that is helping to close our community’s wishes. And then the things that are outside of my control, I literally just don’t focus my time and energy on because there’s quite a bit inside the internal locus of control.

One of the reasons that I think designers are always mad at Adobe is their pricing goes up; they change the plans, they charge for more, and features go away. You’re at a scale with Canva now where you have what I would call the Microsoft Word problem, where the toolbar has to have every button in it because you’re so big that even if it’s only 1 percent of users who use the button, it’s still millions of people and you can’t have millions of people mad at you because you remove the button.

That feels like Canva’s at this scale, which is why AI is in a tab, right? You can’t change it too much. How do you think about making sure your Canva customers, who all use the product every day, seem to be very happy with you and stay happy with you, even as you roll out these products that might fundamentally threaten their jobs or how they work?

I think all of those considerations you said are absolutely very much something we focus greatly on. So for example, when we launched Canva AI, what we’re really excited about is there’s so much breadth and depth in Canva’s product now that a casual user might not be aware of all of the different things and capabilities that Canva can do. Many users are very deeply aware of every single button in Canva, but Canva AI really brings that all together.

So you could just say whatever it is that you want and you might not know the specific tools that you need to be able to use to bring that to life, but it can do it for you. So we’re really excited about how that will be able to make complex things simple even from the perspective of being able to create your first design in Canva.

We also do an extraordinary amount of user testing and we do that with existing Canva community members, and with new users, and that really helps to refine the products before we’re getting them out the door and into our community’s hands. We get more than one million wishes a year from our community and so we have actually just granted 40 of them at Canva Create.

So all of these things that we’re doing are very much in partnership with our community. And I think that’s a really key part for us, is that we want to be building Canva in partnership with our community, getting their feedback, helping to learn from what they want, what they need to do to achieve their goals. And that’s very much at the center of how we think about it.

All right. I need to ask you one very important question right at the end.

Sure.

Do you promise to keep Affinity free?

Yes, absolutely. We’ve made that absolutely key commitment.

Just checking. I feel like every time I talk to you, someone tells me, “Make sure you ask her if Affinity’s going to stay free.”

I can very much say Affinity is going to be staying free. It’s a critical thing. We knew that that was a really critical part of why Affinity was created in the first place — being able to make it more accessible. And then a key part of Canva has always been having our free product. We’ve got hundreds of millions of people using our free product. Affinity itself has had more than 5 million downloads since we announced it. So yeah, it’s a really key part. Affinity is free and will be. 

That’s great. Canva 2.0 is basically in beta, right? You’ve announced it, but it’s in a small beta.

Yeah, in a research preview.

When does it go big?

At Canva Create, we gave one million people access to Canva AI 2.0. And so we’re really excited to be watching how everyone is using it and how it’s helping them to achieve their goals.

Great. Well, I look forward to getting secret access to it so I can make even more silly posters for birthday parties. Melanie, it’s always so much fun talking to you. Thank you so much for being on Decoder.

Thank you so much for having me. Thanks for your great questions.

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

Today, I’m talking with Chuck Robbins, CEO of Cisco.

Cisco is one of those big companies that everyone has heard of but that most of us don’t have to interact with very much; it’s not really a consumer brand. But all of us are in some way using Cisco’s products and services every day because it makes a huge amount of networking equipment for other big companies, like telecoms and ISPs. It’s a guarantee that somewhere between me recording this and you watching, listening to, or reading it, the bits have passed through Cisco products. Without the actual routers and switches and silicon — and the software to make those things work — there’s no internet, there’s no cloud, and there’s no AI.

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.

That’s Cisco’s new big business, of course: building all the networking needed inside all of the data centers the AI companies are trying to build. Chuck and I spent a lot of time discussing that. First, where should we build all these data centers? Because it’s not clear that anyone wants them around.

A data center is a really unpleasant neighbor to have: It’s loud, it’s ugly, and it uses a ton of electricity, making rates for regular people go up. AI itself is polling pretty badly with Americans, and there’s now fairly robust, bipartisan opposition to new data center builds all over the country. So I had to start by asking Chuck what feels, strangely, like one of the most urgent questions of the moment: Should we build data centers in space?

Elon Musk sure seems to think the answer is yes, and he’s pushing SpaceX that way. Sam Altman — along with a whole bunch of experts who understand how cooling and radiation work in orbit — thinks we’re not there yet. So I had to ask Chuck which way he’s leaning, and I was a little surprised how quickly and emphatically he answered.

You’ll also hear me ask very directly whether Chuck thinks AI is a bubble, and you’ll hear him say very directly that he thinks it is. And he would know: During the dot-com bubble, Cisco — the internet builder — was very briefly the most valuable company in the world.

Beyond the AI of it, I love bringing big companies that are kind of hidden in plain sight onto Decoder, and Cisco is a perfect example. Chuck has made some big bets around chip investments to position Cisco on what he calls the leading edge — but not bleeding edge — that are really fascinating when you think about the kind of infrastructure he sells to companies all over the world.

Those companies are dealing with an increasingly fractured global landscape, and asking big questions about data. Who owns data? Where can it be stored? Should the internet have a kill switch in different countries? They’re important questions, but they also don’t have easy answers, and you’ll hear Chuck really delve into how complicated it is keeping the world connected in the deeply weird realities of 2026.

Okay: Cisco CEO Chuck Robbins. Here we go.

This interview has been lightly edited for length and clarity.

Chuck Robbins, you are the CEO of Cisco. Welcome to Decoder.

It’s great to be here. Thank you.

I’m excited that you’re here in person. I have a lot of questions for you. It seems like a very complicated time to run an infrastructure company — which is fundamentally what Cisco is — especially one for global infrastructure. The internet’s a global network, and that seems to be under a lot of pressure from a lot of different directions. So, I want to get into a lot of things with you. 

But I actually want to start with a question I’ve been dying to ask you ever since we scheduled this interview/ I thought finally I can ask this question and someone will be able to tell me the answer. Should we put data centers in space?

Absolutely.

Yes?

And we will.

You think so?

I think so. Right now we’re dealing with lots of power constraints, and up there you don’t have that. And if you think about the people who are talking about putting data centers in space, I wouldn’t doubt them.

Elon [Musk].

Yeah. And there’s a lot of stuff we’re working on right now. We’re thinking through what we need to do to our portfolio to make it work properly in the conditions that might exist up there. But I think we’re going to see it. I think we are.

So Elon’s plan — he recently filed for approval for this plan — is to launch a million satellites as part of a constellation. He’s launched constellations before. You mentioned power, that’s obviously solar. Can’t we just do solar power here on Earth? Is that not a possibility?

Well, up there it’s unlimited and unimpeded, so it’s just easier. You don’t have to deal with a lot of the challenges, like people who don’t want these data centers in or near their communities. So, that’s obviously off the table. I think it solves a lot of problems. There are a lot of challenges figuring out how to make it all happen. But again, given his history, I wouldn’t doubt him. We’re going to prepare so our technology is ready.

What does that preparation look like for you?

It’s very early stages right now. Our teams literally came to me I think about two or three months ago. My head of product said, “We really have to be prepared for data centers in space.” I looked at him like he was crazy. Subsequent to that, we’ve just been talking about how we don’t even know everything we need to do yet. We’re in the early stages of just making sure the atmospheric issues, the temperatures, all of those things are taken into consideration. 

But at some level, we don’t have to deal with the cooling and things of that nature, which add a lot of weight to the product because you first start thinking about how do we get them up there. So, there are a lot of things that our team’s thinking through right now.

What does that networking stack look like for you? Do you have to invent a whole bunch of new stuff? Is it the same stuff without as many cooling loads or with less energy needs?

I think it’s generally the same with perhaps different interfaces for different satellite technologies, things like that. It shouldn’t be too dissimilar.

Do you want to be on the bleeding edge of that, or are you waiting and seeing if Elon can prove it out?

No, I’d like to be on the leading edge. How about we say that? Maybe not bleed, but let’s lead.

What does that investment look like for you? Are you going to send up a team?

The teams that currently build our data centers are the logical ones to actually do this analysis, and I think that’s what’s happening right now.

To me, the cooling piece of it seems challenging in a lot of ways. You have to move the heat out of the products. There’s no air in space. That’s not going to naturally happen.

You’re getting way beyond me pretty quickly.

I’m just curious. We’ve written a bunch of “should we put data centers in space?” stories now, and I was dying to ask you these questions because it feels like someone has to do a lot of basic R&D work to make this happen.

I’d say six months from now, have my chief product officer do this, and he can go through a lot of that with you.

Fair enough. Let me ask you the flip side of this; you mentioned this already. There are problems with building data centers in the United States and around the world. I want to come to that in more depth. But are we just running away from the problems of politics and saying we’ll just do it in space where there’s no one to get in our way?

I don’t think that’s it. I think it just eliminates a lot of the challenges that you’re facing on the planet. Let me assure you. I grew up on a farm in Georgia, so the last thing I ever thought I’d be talking about are data centers in space. Even five years ago, I wouldn’t have thought I’d be talking about it.

If you think about a lot of the dynamics we’re dealing with, I don’t think it’s politics so much as it is the physical limitations, the community. There is an aspect where a lot of the people in the communities don’t want these things in their backyards, and I get that. Sam Altman is one who says, “I don’t think they should be in their backyards.” We’ve got enough rural areas in this country where we ought to be able to put these things, but we’ll see.

Sam Altman also notably says putting data centers in space is a pipe dream. So who are you going to believe?

Does he?

So who’ve you got?

I wouldn’t bet against Elon.

All right, fair enough. Let’s talk about Cisco for a second. You’ve been CEO for 11 years. You’ve been there for almost 30, I want to say. This is a company that goes boom and bust with boom and busts. I think in the dot-com era, Cisco was briefly the world’s most valuable company.

For about a day, I think, yeah.

And this is a company that, when it’s time to do infrastructure, can be one of the big growth drivers.

Infrastructure’s cool again.

It’s time to build, as they say. What is Cisco to you right now? How would you describe this company?

We securely connect everything. That’s basically what we do. We connect systems, we connect people, we connect things, and we do it in a secure way. We’re connecting AI data centers, we’re connecting GPUs within AI data centers. It’s primarily about secure connectivity.

I think when people have thought about connecting everything, they’ve thought about, honestly, the last mile. Like, you build the big internet, that’s an enterprise problem. Then, we’re going to do 5G. Or it’s Mobile World Congress and we’re going to do 6G now. Who knows when that’s going to be. But that’s the big internet people have long thought about. I know you have a big corporate business.

The turn for networking right now feels like data centers. It feels like we’re building these big data centers. We’re going to link up a bunch of GPUs in ways we haven’t linked them up before. We have different kinds of workloads because of AI. Is that a meaningful difference to how you conceive of Cisco?

It is. There’s certainly more and faster innovation around things like the silicon we design ourselves that goes into the data centers. The continued evolution of data centers is forcing us to drive those cycles faster. If you look at our enterprise data center business — going back to 2010 or 2008, when the cloud came along — there was a belief that there was never going to be another private data center built. And if you look at the last eight quarters, our enterprise data center networking business has had double-digit growth in six quarters and high single digits in the other two. 

So, we see that business growing. If you go back five or six years, we had relatively zero business from the big hyperscalers, and this year, we’ll do billions. And most of that’s driven by AI infrastructure and their data centers. So, I think your assumption is accurate.

Is that just their lack of capacity? Amazon or Microsoft wants to build out another data center, but they can’t do it themselves because they’re building so fast so they turn to you?

No, we’re selling them equipment that they’re using to build their own data centers. So they’re building them. They are building them.

So what was the turn? Why did that line start growing for you when it wasn’t growing before?

Success in business is always a combination of good decisions and a lot of luck. The luck struck in 2016 when one of my engineers, who built our hardware, came to me and said, “There’s this silicon company in Israel that I think we should buy.” It gave us the opportunity to standardize on a single silicon architecture across the entire portfolio. 

So in 2016, we bought this company called Leaba. Fast forward and we’re one of basically three companies in the world that can build the networking silicon that’s needed to connect these GPUs, run the training models, and run these AI data centers. So, that was a big part of what’s helped us get there. 

And to be candid, if we didn’t have that silicon today, we would not be participating in this phase. Otherwise, I’d be buying merchant silicon like all my competitors, and I’d be just like everybody else. So, that’s the biggest thing that’s differentiated us and got us to this point.

We have a lot of competitors or would-be competitors come on the show and talk about networking. That seems like a growing business for a class of companies.

The one that I’m particularly interested in is Nvidia. You guys have a deep partnership with Nvidia. They just had GTC. Jensen [Huang, Nvidia CEO] is out there pointing out that their networking business is huge. It’s bigger than yours in some ways. Its last fiscal year was $31 billion. I think you guys were at $20 billion in the last quarter. It’s billions bigger than yours. Is it a threat that Nvidia is so deep into building up the networking component? Because its obviously selling the GPUs. There’s a place it could go. It can just expand its footprint. Is that competition? Is that coopetition? How’s that work?

It’s coopetition. If you look at the big hyperscalers, they actually build their own integrated architecture using best of breed or whoever they want to use. They are very good at balancing their spending across multiple vendors. They like to have optionality. They want diversity at the silicon level. That’s how they think. You see some neoclouds as an example. Nvidia sells a fully integrated stack that has networking included in it. That’s the path of least resistance, and it helps them get there faster. So sometimes they’ll buy that. 

If you look at the enterprise, most enterprises have built 40 years of knowledge, processes, everything around our platforms and our technology. That’s why what we can do together in the enterprise is a big part of why Nvidia values our partnership.

The other thing we have, which no one else has, is security. As we move to this agentic era with agents operating all over your infrastructure, you have to do security in the network because the latency requirements are going to require full-time security on these agents all the time. I’m doing access, validation, and identity validation of agents. We’re the only networking company that has a big security business. None of our security competitors have a networking business. So it’s a big advantage to us as we go forward.

We just had the CEO of Okta on the show, and his entire pitch was, “I will build you a kill switch for your agents.” Is that competition for you? Is that something that will work alongside what you’re planning?

I actually think there’s a great opportunity for us to partner with Okta. That kill switch might be implemented at the network layer because we may see something happening that it won’t see at the upper layers. So we’ll figure it out, but the teams are working on this day and night right now.

The deal is being made here on Decoder. You heard it here first.

Exactly.

This seems like the opportunity. When I say Cisco’s a company that grows with booms and busts, the amount of compute that everyone is describing that they need in order to deploy agents at scale across the enterprise and to train the next generation of models is vast. You are obviously going to help build the data centers that supply a lot of that compute. The question I have is, do you see the revenue on the back end of that? This is a lot of growth, a lot of forward investment.

For them?

For them and for you, right?

Well, we’re getting the revenue now. We would not expect this buildout to end anytime soon. Everybody wants to compare this to the dot-com era, right? Is it a bubble? Is it going to bust? I’m like, well, did the dot-com bust or did the winners emerge, the losers failed, and now we have what we have? If they hadn’t been successful, we wouldn’t be talking about anything we’re talking about today.

So, it wasn’t like it went away. People lost money, but the winners emerged. I think you’re going to see the same thing here. The difference is that, in a lot of cases, the companies that are spending so much money on this infrastructure view it as an existential issue for their survival. They’re going to continue to build, and they’re going to continue to invest. I think they’ve proven that over the last few years, and I think we have a long way to go. We’re very early in this cycle.

I have two thoughts about this I’m eager to push you on. One — and this is just related to the infrastructure — a big part of the bubble there was that we built a fiber network that sat dark for ages. You can say whether that was good or bad, but we had it. And the fiber itself was valuable, even if it wasn’t full of traffic yet. Is a data center valuable on the same scale? If you build a data center, and there isn’t the consumer workload to run it, you can’t just show up 20 years from now and plug into the fiber the way that you could.

I think that the difference is that, unlike that fiber, these data centers are being used day one at full capacity. I mean, they’re just being used. In our world, it’s about the networking connectivity, but it’s also about optics. We haven’t talked about optics, but we made some strategic acquisitions in optics, which has also been a big deal for us. Because at some point, you won’t be able to get the packets off the processor over copper because the speed’s just too great. So us having both those technologies in house is another benefit as we look to the future.

The other question I’ve been really thinking about with the dot-com era comparison is less dot-com and more mobile. If you look at the promise of the dot-com era, it was, “We’re going to take the economy, and we’re going to move it onto the internet broadly. You’re going to buy your pet food online, and maybe you weren’t going to buy it on a Dell desktop PC.” It actually happened when we got to mobile. We just moved the economy onto the internet. Everyone’s doing e-commerce, and it turns out buying pet food from Amazon on a computer totally works when that computer is a phone. Then, Apple and Google get to extract rent from everybody for all their purchases and games. We have an economy that works that way.

The promise of AI is we’re going to do it again. We’re going to move the economy a third time to the next paradigm in computing. What’s the evidence you see that that is happening or will happen at the scale necessary to support this investment?

Well, if you look at some of the early agentic platforms, you heard Jensen this week talking about OpenClaw. I guess when this is broadcast, it would have been two or three weeks ago, but nonetheless. If you just look at the early promise of what that can do for you, I think you’re going to see it automate a lot. It’s going to make your whole purchasing process different.

I think it’s yet to evolve, but I just reflect back to 2007 when the iPhone came out. None of us had any clue what we’d be doing with that phone today, none of us. Maybe there were some people somewhere who were such visionaries that they saw it coming. But the application portfolio that we have today is much broader than we ever thought it would be. I think you’re going to see the same thing emerge around AI. 

We don’t know what is going to come. We have ideas about things that we think will happen, but we don’t know everything that’s going to happen. I mean, this stuff’s changing so fast. I talked to Kevin Weil at OpenAI and he’s like, “We’d sit down and have meetings about what are we going to do the next two months, and then three weeks later, we throw it out and start over because everything’s changing so quickly.” I think that’s the way we’re going to all have to operate, which is going to be very uncomfortable for a lot of people.

Is that changing the way you’re selling your products to build this capacity? Because if you don’t know what the capacity is for, it must change how it’s being built.

It’s changing a lot about how we design silicon. These customers are so big that they’re a market of one. So, we have unique requirements coming from an individual company, which we haven’t had to deal with in the past. We built general-purpose silicon, we sold it to everybody, and it worked.

So, you have different applications, different use cases, different customers that are leading us to move faster and build more variants of this technology than we would have in the past.

That’s right up against the insatiable demand of other silicon providers, right? There is a capacity crunch for chips, there’s a capacity crunch for RAM. How is that working for you? Are you able to get the flexibility you need?

Yeah. Certainly, when you look at fab capacity, we could use more, but the world could use more. I don’t think you’d get anybody on here who builds chips that wouldn’t say, “I’d love to have more capacity.” Same thing for memory. We’re in a crunch for probably 18 months  doing everything we can to try to secure what we need. We feel pretty good about where we are right now, but we’ll see how the demand plays out over the next year and a half.

I’ve talked to people about RAM margins like consumer laptop vendors who say, “There might not be consumer laptops this year.”  It might just be priced out. You might never be able to cover the cost to just put a stick of memory in a cheap laptop. y You might just be out. The CEO of Razer, which makes gaming laptops with lots of fun lights, was like, “Week to week, I don’t know what the margin on that product will be.”

It’s true.

You’ve got to build a big piece of the infrastructure puzzle. The GPU is useless without the networking. This at least has to equalize somewhere for you,  right? You’ll say, “Look, this is our margin to build the networking, to get the value out of the GPUs that we’re buying at super high rates from Nvidia and whoever else.” Is that working in the market to at least equalize your prices?

Networking equipment uses a lot less memory than compute platforms do. So, we still have memory in every networking device, but it’s much smaller percentage of the BOM than it would be in a —

That’s “bill of materials.”

Thank you, sorry about that. It’s a much smaller percentage than it would be in, like, a server. The customers understand… what I keep trying to explain to them is that price increases are happening upstream from us. We’re just an absorber of the price increase. We’re having to do more frequent price increases than we have in the past, and we’re having to change our terms to deal with the same thing that your other guest talked about, which is the dynamic nature of the pricing that we’re seeing right now in the memory space.

But when you go to the large hyperscalers… I said earlier that it’s existential. So, what we’ve just adopted with them is a more transparent model that says, ” Here’s what we need. Here’s how it works. Here’s our pricing.” And they generally understand.

Because there are other choices, especially, for you to provide —

Everybody’s in the same boat. It’s not like you’re going to go somewhere else and somebody’s going to give you memory at 10 percent of the cost of what we’re offering. Everybody’s just trying to deal with the capacity crunch right now.

This brings me to the Decoder questions because my next set of questions after this are how you’re handling this interlocking set of complicated puzzle pieces.

Tell me how Cisco is structured right now. How big is the company? How is it organized?

We’re 85,000 people, plus some contractors. We’re functionally structured like most companies. We’ve got a sales organization. We’ve got a product organization. The one change I made about 18 months ago was to consolidate all of our products under a single leader for the first time that I can remember. It’s a big complex portfolio, so we did that. We’ve got a services organization. It’s fairly functional. Pretty standard.

You’ve been reducing the size of the company pretty substantially over the past three years, I would say.  You had two big rounds of layoffs in 2024. You just had some other little layoffs.

Most of the time those are rapid reallocations that we need to do. It’s unfortunate, but it’s not… Typically, the ones we’ve done have not been about reducing the total head count. At least, they have not generally been that way up until now.

I was reading some coverage of those changes. There’s a lot of, “Are these AI-related layoffs?” Is that on your mind? That you might be thinking about new kinds of structures, new kinds of engineering structures?

As an example, let’s say that our engineers become twice as productive because of coding. This year, we’ll have five or six products that’ll be 100 percent written by AI. Next year, we’ll probably have 70 percent of our code be written by AI.

You still have to test it. You’ve still got to go through all that stuff. But let’s say you make them twice as productive, just to simplify the math here. The companies are going to have to decide, “Am I going to maintain the same pace of innovation with half the people? Or am I going to double my pace of innovation with the same number of people?” I think different companies are going to make different decisions with some in-between variants. I think that’s where we’re heading.

But we’ve got to see this all come to life. We’re seeing the early coding successes of coding, but we haven’t seen the unintended downsides that we haven’t figured out yet. My head of product was saying that we’ve got 20 or 30-year-old code that’s integrated in the systems that’s written in C++, as an example. That head of product told me, “We took all these old lines of code, we compressed it by about 20 percent, and we converted it to a modern language using AI.” My first response to him was, “You better test that like crazy before you put it in a product and then put it in a customer environment.” There’s a lot of stuff we’re still learning as we go through there.

Stay on that for one second. Cisco code can’t fail, right? The networking components should not go down in the same way that… I don’t know, how we are resilient to Amazon being broken for five minutes and then it coming back to life, right?

The world stops.

Yeah. If Cisco fails, something bad happens in an escalating, catastrophic way.

I get those calls, by the way. [Laughs]

I have a lot of listeners who are like, “What’s Chuck’s phone number? Because I manage a Cisco portfolio.” We’ll give it out at the end.

Okay. Great. Perfect.

Stick to the end of the episode. There’ll be an affiliate code when you call. [Laughs]  

How do you think about that risk? I keep joking about how I ask everybody the org chart question. I’ve asked it for five years, and there’s two answers:  we’re functional, we’re divisional, and we get through it. 

Now, I think we’re on the cusp of seeing some of the weirdest org charts in business history. “I manage a team of two people and 500 agents.” Meta is about to do one manager to 50 individual contributors all using agents to write code. I don’t know how any of that’s going to work. You can’t take some of those risks, but you’re describing the productivity gains that might come with some of those risks. How are you thinking about that?

We need a little more runtime. You’re right. The whole mental model around our software development versus these models. Kevin Weil from OpenAI made a comment at our AI summit, and he said, “You guys should be using these models when they’re working properly 10 percent of the time just to get to use them.” I sat there and I listened to that comment. It’s just a different way of thinking. Granted, they’re going to get it to full… But you go into it recognizing that it’s still evolving. We don’t have that luxury. Our stuff has to work. We’ll have to figure this out as we go, but we’ve seen how dependent the world is on technology functioning properly. We’ll have to just assess it as we get closer, but I think there’s going to be an awful lot of testing that has to get done. 

But the flip side is that we think AI can help us find bugs more quickly. It can help us assess customers’ infrastructure and say, “Hey, you’re running these four versions of our software. We’ve seen a lot of instances where when you’re running those four, it’s created a problem.” Or, there’s cybersecurity risks in certain parts of the code that AI can help us find. There are a lot of upsides. There’s a lot of opportunity for AI to help us become more reliable safely.

You’ve mentioned security several times now. The flip side of deploying AI to help with security is your adversaries who attack might be able to deploy AI to attack you much more efficiently.

And they are.

How is that playing out for you?

The emulations that you’re going to see, like email and video simulations and people replicating me, is just going to get crazier. So, we have to be better at using our tools. I have also been a big proponent of all of the security competitors in the industry laying down our weapons. We still compete but in service to our customers. I believe we have to more effectively share intelligence in real time today to help our customers deal with this because any one of us on our own is going to be less effective than all of us together.

That’s a big thing we’ve been pushing. We’ve been building a lot of capabilities. There are a lot of opportunities to integrate our platforms and our threat intelligence. If you think about what you can do with models, like training on threat intelligence and conditions that led up to threat vulnerabilities, there’s an awful lot we can do to get ahead of this. And we need to do that.

I think this brings me into the other Decoder question that I ask everybody. This is the one that I think is pressure for everybody. At the scale of change you’re describing here, how do you make decisions? What’s your framework?

When I wrote my thesis during the process of becoming CEO and the board was assessing the candidates, one of the things that I called out in the document — and this is 12 years or 11 and a half years ago — I said that the industry is moving so rapidly that you’re going to neede team-based strategy. You have to have a lot of people developing strategy because there’s no one individual. There’s some brilliant minds, so I’m not ruling any one human out, but there’s no one individual who can come up with the exact right strategy every time they’re assessing what they need to do.

So, we spend a lot of time together as a team. We spend anywhere from one to three hours together every Monday. We go off-site together for two to three days every quarter. And the way we make decisions… Look, 99 percent of the decisions get made below me because they’re easy or because two smart people agree. When they get to me or any other CEO, you’re usually assessing two potential bad choices. Or you have two smart people who completely disagree, which tells you it’s complicated. In general, we just spend a lot of time in transparent discussion and open communication about how we’re going to make the decisions. 

At the end of the day, I own them. I have this belief that when a decision goes really well, you give everybody else the credit, and when it goes very poorly, it’s all on me. That’s just how you have to operate.

To the decisions question, you are dealing with a vast amount of uncertainty, right? There’s a vast amount of uncertainty with how the global internet will be structured. What do the hyperscalers need as they build out new capacity for uncertain workloads? Who knows. We’re going to sell a bunch of products to the neoclouds, which have circular financing. Those bills might not get paid, which I want to come to. That is a lot of uncertainty. I would say whether or not all of this infrastructure investment pays off in GDP growth is the biggest uncertainty of all. How are you dealing with that?

You haven’t even gotten to three or four other big ones.

Go ahead. What are they?

Well, you’ve got the geopolitical situation, you’ve got sovereignty requirements emerging all around the world. You’ve got two wars around the world. You’ve got tariffs, you’ve got memory costs, you’ve got all these things that we’re all trying to navigate. So, it’s pretty complicated.

That is a lot of uncertainty on your decision-making. You’re saying it all rolls up to you when it goes wrong. Has that affected how you’re making choices?

Faster. You just have to move faster. We had an all-hands with our entire company yesterday. We do it once a month. I told them, “Look, if speed and change makes you uncomfortable, you’re going to be uncomfortable because it is a world where companies can get seriously damaged in a very short period of time.”

This is what’s driving a lot of the investments. There’s a big FOMO issue in the C-suite today. CEOs are like, “What am I missing? What’s my competitor going to do that I don’t know about?”  We used to say, “Get 80 percent of the information you can, make the decision, and then adjust as you go.” And I think that’s… Maybe it’s not 80 percent anymore, but you’re going to have to take that approach. You’re going to have to be willing to take risks, and you’re going to have to be comfortable being uncomfortable. And if you’re not, it’s going to be a pretty complicated and stressful time.

Billions of dollars in capital are being allocated for infrastructure. Does it come up that the products that might pay this off don’t exist? Does it come up next to the FOMO?

Depends on the customer. If you look at the [telecom operators], the cloud providers, the people whose core business is highly dependent upon products that we build. Everybody is, but we will have those conversations with their CEOs and their leadership team. You go to Mobile World Congress, as an example. We were just there in every meeting the CEOs from some of those carriers and service providers are in. So, they care. When you get into the enterprise space, some of them are super technical. They understand the value of technology. So, they want to talk about trends. They want to talk about what we see other companies doing or what we’re doing as an enterprise that they should be thinking about. 

But usually, if there’s something big going on the table, my only position with them is, “If you go with us, you have my personal commitment that we’ll throw all the resources you need to make you successful.” That’s usually all they want to know.

I feel like there’s a split in the market right now. I understand the enterprise use cases for AI. I understand why you’d want to build as fast as you can there — particularly in software development, as you described. We can see the benefit. 

We talk to developers all the time here at The Verge. They’re like, “Our entire job is different.” The world has changed. The market has cracked open. Something is going to happen there. Then, downstream of that, you can say, “Well we hired a bunch of engineers to build us business process automation. Maybe we get way more value out of those engineers and we get way more automation.” There’s something in the enterprise that’s going to happen with AI, that feels like I understand the value. Do you see any consumer applications of that scale beyond just telling Alexa to buy me shoes. Quite honestly, I don’t yet, apart from Google Search getting a lot weirder over the past two years.

I don’t have any great examples yet. You’re right. You are seeing some horizontal areas in the enterprise that are consistent across almost every company, like coding. Customer service is one that everybody’s working. You start to see some emerging horizontal use cases in legal. We’re seeing a lot of use cases in our people organization, too. I think those are pretty standard. Everybody’s at least aware of those opportunities. People are at different stages on the journey. But, I’m not the consumer expert by any stretch. We’re purely B2B, so that’s where I spend all my time.

If I saw it, I would have probably read it on something you published.

We’re looking for it every day.

The reason I’m asking is because I think this relates to why I started out asking about data centers in space. I’ve heard [Google CEO] Sundar Pichai say variations on this idea. Without the big consumer application that everybody understands and can see the benefit of, putting the data center in the backyard is becoming an increasingly harder sell. The power requirements, the water requirements — which I know are controversial and often argued about — just the energy, resources, and requirements of the data centers are making them unpopular. 

I don’t think it’s all that. I don’t think the environmental argument historically wins in America. I drive a V8 Mustang, and I’m going to keep driving that car. We have an EV that’s parked right next to it, but those cars are popular for reasons. Fast fashion, enormous environmental impact. People like it. There isn’t an AI product for consumers that they like so much that it just transcends objections they can reach for. We’re seeing it play out in really weird ways. In bipartisan ways, people are pushing back against the data centers. 

Are you going to be able to hit your goals if data center construction slows? Is there a way to overcome those goals without the great consumer product?

I think there is. Look, we’ve been the most innovative country on the planet for a very long time, and that’s not going to change. Some of the smartest people in the world are actually trying to solve these problems, and they will. 

By the way, I think if you give some of those residents the greatest AI tools that they’ve ever seen in their lives on their phones, they still don’t want the data center in their backyard. I don’t think they’re going to say, “Oh, this is great. Go ahead and drive my energy costs through the roof and I’ll be okay with it.” That’s not going to be the gating factor. I think those apps will come. We saw a little bit of this with 5G. They didn’t want radio towers. You remember that whole thing?

Oh, I remember.

This is that at a much greater scale, but I think we’ll figure it out.

The 5G comparison’s really interesting. I know you just came back from Mobile World Congress. At least the telecom industry understood that they had to describe some applications that all of this build-out will accomplish. The ones that got me every time were, “We’re going to have self-driving cars and we’re going to do robot surgery.” There were all these demos of these things. I went to endless CES demos. A self-driving car demo is fundamentally very boring. You don’t want to be in an exciting, self-driving car demo.

You don’t.

I sat in a lot of them at CES and pretended to be very excited that 5G would drive the car. 

That car looks like every other car driving.

Yeah. And it’s like, “I would like this to be as least exciting as possible.”

Yes.

Maybe there was one demo of a 5G surgery, and it was still backstopped by wired internet. 6G has the same sort of application problem, right? We don’t know what it’s for. AI has the same problem. You can’t describe what it’s for in a way that might overcome the objection. That feels like a fairly unique point for the whole industry to be at, where the next generation of technology is very exciting to a handful of providers. It’s the future of your business in real ways, and the applications are harder and harder to describe.

You’ve seen it all. I’m asking you this question on a big sweep. If we’re talking about the internet, it was easy to describe what it might do for people. I actually disagree with you. I think a lot of people instantly saw what the phone would become. There was an excitement there. That’s where you got startup founders from, in that way that you got founders from.

This one just seems more nascent to me. How would you place that in your sweep of history?

You’re right, we didn’t have the number of use cases. I think if you asked the telecom CEOs, they would probably say that they’re disappointed in the return they got on all the investment around 5G. That’s pretty well-understood. I think robotics in general could be the real driver of 6G utilization once it gets built. But again, its early days are being defined. Typically, we’ve talked about these tech transitions for years and years and years before they come to fruition. 

AI is different. We did talk about it for a long time, and then all of a sudden it broke loose. The pace at which it’s changing is just unprecedented. I think we’ll have to see on 6G; it’s still TBD. I don’t expect that you’ll see the same mistakes made from a speed-of-investment perspective until they become more clear.

The internet also was hand-in-hand with globalization, right? We both have iPhones that are made all over the world. You had this giant global network. Maybe this is going to lead to an age of prosperity. Maybe this is going to lead to an age of extreme labor displacement. You can read that however you want. There are a lot of opinions about what the internet and particularly globalized manufacturing led to. 

That’s all being undone. You can see that’s being undone every single day. Whether that’s with tariffs in an effort to bring manufacturing back to the United States — which we’ve talked about on the show with many of your peers — or whether it’s, “Hey, we’re going to put up big walls on the internet.” Australia’s going to have a social media ban for teens. They’ve got to enforce that somehow. That’s probably going to happen at the network layer. You have the European Union saying, “The data has to be here. We have to put the data here. The European data has to be in Europe.”

You build the networks. I’m imagining all of this is just one more layer of complication, even as you describe how we should have global systems that bring us to an era of shared prosperity. How are you dealing with that?

I think what you’re seeing play out is not only do countries want data sovereignty, they want to have sovereign control over any technology they’re using. And it’s not limited to Europe at this point. They don’t want the US to have the ability to impede the use of those products under any conditions. As an example, some of the meeting platforms like Webex or Zoom don’t want any other country — I’ll say the US but any other country — to have the ability to cut off access to these platforms if they’re going to invest and use them for critical reasons in other countries. Let’s use Europe as an example. In many cases, European companies that build the technology they use in their infrastructure don’t have that capacity at scale. So then they have default to, “Who are the companies that I trust?” And trust becomes such a big… It’s a big discussion obviously around AI, but it is really a big deal.

So for us, as an example, we have always tried to be good citizens and good members of the community in evert country we operate in. We’ve had education programs for 25, 30 years that train learners on digital skills around the world. Last year alone, we had 5 million learners around the world go through one of these programs. So, that trust element’s going to become very important. The technology is one thing. You have to build technology that can be deployed the way they want it to be deployed. Then, you have to have a very high degree of trust when you work with them.

Is this changing how you’re architecting some of your products?

It is.

What are some specifics?

Well, you’d love to have a cloud solution. Historically, what you would do — and a lot of companies were built this way —  is build global instances, partition them, and sell them off to different customers. As an example, if you go to Germany and Germany says, “I want to have my version of that running in my country,” it’s architecturally different than how you might have designed it to begin with.

We’re now designing a lot of those control or cloud-oriented systems so that they can be structured to run in a country alone, and we don’t think about building global instances anymore.

From your perspective, this is a very different way of building the internet, right? It just isn’t the thing. My first experience with the internet was watching the coffee pot at the University of England.This was the promise when I was a kid watching a one-frame-a-minute live stream of a coffee pot and being like, “I can go there.”

You watched live streams of coffee pots, for real?

Do you remember this? In 1994, the first video feed on the internet was a coffee pot in Cambridge.

It blew my mind when I was kid. 

In some ways, it’s more than ever, right? You can watch live streams of all the coffee pots ever.

Any one you want.

If you want to. In some ways, this is just closing down, right? Every country is saying, “Our citizens are here and we’re going to manage what they do. Their lives are on the internet. We are going to control the internet in our country.” That’s happening all over the place in all kinds of ways. It’s honestly happening state to state. The internet in California looks different than the internet in Texas today. 

You’re the networking provider for many of these countries, for many of these companies. When you think about the sweep of what the internet might look like, when you think about the amount of compute that’s happening in a data center as opposed to happening locally on my laptop, (which is always a kind of dance) what does the internet of the next five years look like to you?

Well, it’s going to be more fragmented for sure. You’re seeing the cloud providers build in regions and certain places, and they’re having to re-architect to think about this. I’m not sure most of the functionality we use for the internet today is going to change much, to be honest. There are going to be controls that will exist, but I don’t think it’s going to change the core, normal operating functionality of how it works today. They’ll be there in the case of an issue or an emergency.

Now, it’s not the network’s issue where you store data and all those kinds of things, so how that plays out is independent of what we would think about. But I think you get into times of crisis and that’s when you might see things happen differently. If you’re a certain country that gets into a conflict and you want to isolate yourself from a communications perspective so you can trust that your communication’s clear, then that might create short-term dynamics for your citizens. But I don’t think it’ll be meaningfully different on a day-to-day basis.

We’re seeing that right now. India shuts off the internet and cash flow all the time. The Iranian internet is on and off every day. Are those things that your customers are coming to you and saying, “The government wants this capability of the network one level up. Can you help us build it?”

They are having those conversations primarily around not wanting to have a third party or another country disintermediate their capabilities through tech by having some control or a kill switch. That’s typically what they’re talking about.

How does that play into AI a bit? Now, we have these workloads built on networks that you’re supplying, you’ve got a bunch of agents doing stuff all day long, and you’re saying, “We’re going to be the security provider for it.”

At some point, does Donald Trump get to say, “Turn off the agents, it’s getting out of control?”

You have to think about security at an agent level. It’s like you would do at an employee level but on steroids. You’ll need to apply five to 10 times more security, maybe more. I’m just throwing numbers out. We have to figure that out as we get going, but it’s certainly going to introduce an entry point for bad actors to do things that you wouldn’t want them to be able to do. We’re learning, and everybody is working on this problem simultaneously right now.

I feel like for most of this conversation, my assumption has been that this is going to keep going. This is going to keep working. The problems will be complicated, everyone will work diligently, we’ll solve them, someone will invent the consumer product, and all of this will pay off.

What if it doesn’t? What if this bubble pops? What does that look like for you?

What’ll happen is there’ll be lost, misplaced capital. There’ll be companies that shut their doors. Then, the winners will emerge, and we’ll build out at scale just like we saw with the first wave. I suspect that’s what will happen.

I think there are certainly going to be companies that will cease to exist. They’re going to go away. That’s what happens with any of these early things. You take a risk. That’s why the reward is so high; it’s risk-reward. It’s the nature of these massive transitions, and this is bigger and faster than anything we’ve ever seen.

The amount of capital tied up in what you might call circular financing with some of these neoclouds seems dangerous to me. It seems like if I had to point at where things will get shaky first, it will be, “Well, we did a lot of forward investment with a lot of debt investment into neoclouds against workloads that themselves have not yet paid off.”

Eventually, the bill will come due or the investments don’t happen. Is that a risk that’s on your mind?

It is, but not particularly for us. We’re super conservative. I’ve heard instances where we’ve looked at financials and have chosen not to do business with some of these folks. I think every company has to make their own decisions. 

We also have creative financing solutions that protect us so we can work through. We learned a lot in 2000 because we were doing a lot of that back then.

The neoclouds, are you in them or are you staying away from them?

No, we’re in some of them. Some of them want to use us. Honestly, a lot of them want partnerships with us because they want the enterprise access. They don’t have a robust enterprise sales force, and they think we can help them there. So, in many cases, we work together to figure that out.

The other way I can see things maybe not getting shaky but changing dramatically so that it changes the investment available in the AI industry is if inference becomes more valuable than training, right? So far, all the emphasis has been on running these GPUs red-hot to do training because the next version of the model will finally be capable enough to, I don’t know, be your girlfriend. Whatever it is that they think they’re going to do. Something about training has been the point. We’re going to build AGI. They don’t want to say it, but they’re saying it all the time. There’s a chance that the models are good enough, and it’s actually just inference now. We’re just going to run agents and Claude Code is big enough to meaningfully affect enterprise cost dynamics.

Does that change your business if we’re done with training and, actually, inference is the point?

No, it is actually great. I don’t think you’re going to be done with training, by the way. I think the inferencing stuff is going to be additive.

Do you need all the new data center build-outs if it’s inferencing instead of the training?

I mean, we would like to participate, and we’d obviously like to see that continue to grow because it’s good for our business. But some people believe the inferencing side is  going to be bigger.

I think that it’s going to be very distributed. You think about how a lot of enterprise customers are going to want to do inferencing at a point of interaction with a customer and garner immediate value in that interaction, and that’s going to be very distributed. Distributed compute requires high-performance networks, which is good for us. So, we like that.

This is what I was mentioning: the dynamic between the edge and the data center seems to always be changing. I think I saw some press releases out of Nvidia’s GTC about more compute coming to the edge of certain big network providers.

Are you seeing that play out? We don’t know where it’s supposed to be, so everyone is investing in both the edge and the data center?

It’s still early at the edge. I think everybody believes they’re going to need it, and we’re seeing certain applications where people are starting to pilot it. I think this may be a good opportunity for the telecom providers. There has always been this thesis that edge compute was going to be a big benefit for them.

That was the thesis of 5G. I won’t say the name, but I went to a very long dinner with one of the major telecom providers, and they told me all about self-driving cars powered by edge networks.

But you could see this become something. There are discussions now of inferencing grids and the dynamic routing of these inferencing requests based on everything from cost of power at a given time of day to capacity that’s available. I mean, there’s a lot of thinking about how this plays out. I think it’s still TBD, but it’s coming.

So, I want to bring this all back around. The business here is building data centers with people, with big customers.

It’s part of it. We also connect all the employees and everything else, too.

Well, sure. I mean, do you want me to talk about Webex for another hour? Because I have a lot of notes about Webex.

[Laughs] We can talk about anything you want.

Apple uses Webex. Does Tim Cook ever say, “Dude, can you just make the Mac client a little bit better?”

No, it’s actually better than most others. Do you use it?

I’m a journalist. I’m on calls with these companies all of the time. So Webex comes up in my life.

Okay, good. I’m glad to hear that.

I’m just telling you, find the person, the native Mac client —

All right. I’m going to get one of my guys on the phone with you and make sure that — 

We’ve got to do it on the show, and we’ll just go through a demo together. But you’ve got to be there.

I’ve got to be there?

Yeah.

All right.

We’ll do live notes on a Webex call.

For you to be happy with Webex, I’ll do that.

Every time an enterprise software CEO comes on the show, I’m like, “Do you use your product?” And I would say it’s 50-50.

I do all day long.

You obviously do.

All day long. But I was also a coder early in my life, so I’m a little weird. I’ve used Claude Code, so I’m — 

You’re in it.

Yeah.

All right. But I’m saying the growth of the business, the explosive growth that everyone is seeing, is in AI, right? It’s in building these new generation of data centers, this new generation of compute. I just keep circling around it, but the problem is that people don’t want those data centers near them, and I have yet to see the argument for why that should happen.

In my mind, the argument is great consumer products. If you’re like, “That’s where Netflix comes from,” I think people will calm down. But that’s not the argument we’re making right now. There isn’t a product like Netflix.

That’s where Netflix comes from.

I think if you were like, “Netflix is building a data center in your town,” people would be like, “That rules.”

Yeah, it’s going to be faster.

Right. Is Tom Cruise going to be there? You would have some emotional connection to the thing that’s happening. We don’t have that right now.

The pressure on not building these data centers is only going to go up in weird ways. In Alabama, there’s a state senator that proposed blocking solar build-outs as a way to reduce data center interest in his state. That’s a weird outcome. What happens if we can’t build more data centers? What happens if the public just doesn’t buy in?

We’ll build them in space faster, I guess.

This is why I started off asking if you’re just trying to escape the political problems of Earth.

I don’t think they’re political problems. I think they are issues of utility and power, cooling and water, and all those things. They’re all interconnected. 

Again, I don’t wake up every day and deal with this issue, but the people who do are very smart people. I think the thing a consumer will be okay with is if you go in and not only build a data center but somehow increase the utility capacity of that community or do something positive in that community beyond streaming Netflix faster. That’s when they’ll be okay with it because I don’t think their concerns are around it being unsightly or anything like that. I think the issue is the concern over the inflationary pressure that it puts on utilities and the things they need.

In my hometown of Racine, Wisconsin, there was supposed to be a Foxconn factory, and that never came to pass. Now, it’s going to be a Microsoft data center. Instead of 13,000 or 15,000 jobs, which is what Foxconn promised to that site, there’s going to be like a couple thousand.

This is a lot of water and a lot of power without the economic lift that you get. Then maybe there’s the inflationary pressures on power or other utilities. As your customers are building out, are you working with them to reduce those pressures, to find ways to make the data centers more efficient?

Our role is really around the power consumption of the platforms that we sell, and that’s a massive part of our innovation cycle. We want to deliver higher performance and lower power consumption every time. So, that’s the role we play in that space.

Well, Chuck, you’ve given us a lot of time. What’s next for Cisco? What should we be looking out for?

It’s hard to predict what’s going to happen. As I said earlier, we had a high degree of luck with the optics and silicon investments that we made. We had some smart people who were suggesting that we make them, but they’ve turned out to be magical for us right now.

For the next three to five years, we’re going to be spending every ounce of our energy on secure connectivity in this agentic era. But I mean, I don’t know what we’ll need to do three years from now because things are changing so quickly. I think we’re as prepared as we can be.

Well, we’ll need to have you back sooner than three years to see where the pulse is. Thank you so much for being on Decoder, man.

Thanks, man.

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

Today on Decoder, we’re talking about the major antitrust lawsuit against Live Nation, and what it might mean for antitrust and competition law in general now that the Justice Department under Trump has decided to settle its part of the case. That’s even as many states — including New York, California, and Texas — carry on the fight.

To break it all down, I’m joined by Verge senior policy reporter Lauren Feiner. Lauren is our resident court expert, by which I mean she’s been in the courtroom herself and chronicling this trial from the beginning.

You might be unfamiliar with the name Live Nation, but you’ve almost certainly encountered one of its many, many subsidiaries — the most infamous of these is called Ticketmaster. Longtime Decoder listeners might recall an episode we did on Ticketmaster back in 2023, in the wake of the Taylor Swift Eras Tour fiasco. That was when Ticketmaster’s website crashed during the first major rush for Eras Tour tickets. It was such a scandal, and Swifties are so politically powerful, that Live Nation was then dragged in front of Congress after widespread backlash spilled over into the mainstream. 

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.

In 2024, the Department of Justice launched an antitrust lawsuit against the company, seeking to break it up — to split Ticketmaster off from Live Nation to try and combat predatory practices and increasing ticket fees.

This seemed like a real slam dunk case against Live Nation, regardless of political affiliation — nobody likes Ticketmaster, and breaking up the company would score political points for whoever finally pulled the trigger. It was also supposed to be a sign of strong bipartisan antitrust support. 

The lawsuit was filed under the Biden administration. So even though Trump has since replaced Biden’s antitrust leaders, there was good reason to believe the new people in charge, in particular DOJ antitrust chief Gail Slater, would keep up the pressure, especially against tech companies. You might remember that JD Vance used to go around calling himself a fan of former FTC chief Lina Khan and calling for the breakup of Google. 

But nothing about the second Trump admin is predictable. In early February, Gail Slater was pushed out. And then just one week into the Live Nation trial, part of that lawsuit came to a sudden and shocking end. The DOJ settled its portion of the case, extracting what many in the broader live event and music industries see as weak concessions. This has stirred up accusations of outright corruption on behalf of Trump himself, who reportedly intervened in the case directly to demand a speedy settlement.

But the lawsuit isn’t over yet. Because the case against Live Nation also included dozens of US states and districts, there is still a majority of state attorneys general who have refused to give up the fight. So Live Nation remains in court, fighting off accusations that it operates an illegal monopoly in the ticket business, which is illegally tied to its promotions business… which is illegally tied to its venues business.

But the DOJ settlement raises all sorts of complicated questions about where antitrust policy stands in the US today, especially with regard to ongoing cases against Big Tech companies like Apple and Amazon.  

Lauren has been tracking all of these developments in detail — the trial, the settlement, and now the states continuing the fight — so let’s get into it. 

If you’d like to read more about what we discussed in this episode, check out these links:

• States’ anti-monopoly case against Live Nation continues Monday | The Verge
• The Live Nation trial restarts with a ‘velvet hammer’ | The Verge
• Live Nation settles government antitrust suit — and dodges a breakup | The Verge
• The Live Nation settlement has industry insiders baffled | The Verge
• Listen to the Live Nation CEO’s alleged threats to a concert venue | The Verge
• The threats and bare-knuckle tactics of MAGA’s top antitrust fixer | The Wall Street Journal
• The Trump admin just gave Live Nation the gift of a lifetime | The New York Times
• How Live Nation allegedly terrorized the concert industry | The Verge
• The US government is trying to break up Live Nation-Ticketmaster | The Verge (2024)
• Taylor Swift vs. Ronald Reagan: the Ticketmaster story | Decoder (2023)

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Today, I’m talking with Shishir Mehrotra, who is CEO of Superhuman — that’s the company formerly known as Grammarly, which is still its flagship product. 

Shishir also used to be the chief product officer at YouTube, and he’s on the board of directors at Spotify. He’s a fascinating guy, and we actually scheduled this interview a month or so ago, thinking we’d talk about AI and what it’s doing to software, platforms, and creativity pretty broadly.

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.

Then things really took a turn. Back in August of last year, Grammarly shipped a feature called Expert Review, which allowed you to get writing suggestions from AI-cloned “experts,” and reporters at The Verge and other outlets discovered that those experts included us. It included me.

No one had ever asked permission to use our names this way, and a lot of reporters were outraged by this — the talented investigative journalist Julia Angwin was so upset she filed a class action lawsuit about it. Superhuman responded to this by first offering up an email-based opt out and then killing the feature entirely. Shishir apologized, and you’ll hear him apologize again. 

Throughout all of this, I kept wondering if Shishir was still going to show up and record Decoder, because my questions about decision-making and AI and platforms suddenly seemed a lot harder than before. To his credit, he did, and he stuck it out. This conversation got tense at times, and it’s clear we disagree about how extractive AI feels for people. But I won’t stretch this out any longer.

Okay: Shishir Mehrotra, CEO of Superhuman. Here we go.

This interview has been lightly edited for length and clarity. 

Shishir Mehrotra, you’re the CEO of Superhuman. Welcome to Decoder.

Thanks for having me.

I’m happy you’re here. I’m a little surprised you’re here. I think you know what some of the questions are going to be, but I’m really happy you made it. I have a lot of questions about AI, how people feel about AI, and then a feature you launched in Grammarly, which is one of your products, that made people feel a lot of feelings about AI. So we’re going to get into it.

Let’s start at the start. Superhuman owns Grammarly and Coda. You own a bunch of companies. Just quickly describe the structure of Superhuman and all your products.

Superhuman is the AI native productivity suite. We bring AI to wherever people work. Late last year, we changed the name of our corporate entity from Grammarly to Superhuman. We did that because the scope of what we do has broadened quite a bit. And so in addition to Grammarly, which is everyone’s favorite writing assistant, we now have a document space called Coda, and a very popular email client called Mail.

We launched a new product called Superhuman Go. Go is the platform that brings you a network of proactive and personal AI assistance directly to wherever you work. So for people familiar with Grammarly, you can think about Go as taking that core idea and allowing anybody to write agents that work just like Grammarly does. Your sales agent, your support agent, so on, can all help work with you right where you work.

The core idea is that most AI tools require a big change in behavior. We bring AI where you work. Across our products, we see about a million different apps and agents every day. We seamlessly blend AI right into your experience, so you don’t have to think about AI.

That’s what we’ve been doing with Grammarly for years. And now we are opening that up so anyone can build on that with Superhuman Go.

You and I hung out a few weeks ago, and one of the things we talked about was the fact that Grammarly, for most people, is expressed as a keyboard. It shows up on your phone and your documents. You spend a lot of time figuring out how to make sure you work with things like Google Docs. 

All of those products are integrating AI in exactly the same way as you’re describing. I think you put AI right next to the insertion point, right next to your cursor. What’s the big differentiation for you?

First off, I think very few of them actually are doing that particularly well. A handful do. But as I mentioned, we see a million unique apps a day. The way to think about Grammarly is it’s your assistant that lives everywhere. You might be in a web app. It could be Gmail, it could be Google Docs, it could be Coda, it could be Notion. 

You could be in a desktop app. That could be Apple Notes, that could be Slack, that could be whatever app you’re using. It could be every mobile application. We have, for every one of those applications, figured out the right way to observe what you’re doing, annotate it in a way that is unobtrusive to you and to the application, and to make changes on your behalf. And doing that everywhere is the proposition.

As you jump from tool to tool, there are different types of AI in each one. Most of them actually don’t have that. Like I said, we see a million unique surfaces a day. And the ones that do don’t feel like one integrated experience. That’s why we have about 40 million daily active users and that’s what they use us for.

It feels like the promise there is by looking at all the places you work, your tool will be more intelligent than disparate tools you might encounter in all those places.

Yeah, becoming more intelligent is certainly part of it. For many people, it’s just that one familiar experience that really feels like a virtual human working right next to you.

So is it consistency of experience or is it better and more useful results?

It’s both. The fact that Grammarly is ever present is very important and [it produces] very high-quality grammar results. As we split the product into parts, we said, “We’re going to take the platform layer of Grammarly and we’re going to turn it into a platform.” That’s what we call Go. That’s about allowing other people to create agents and experiences that provide a high-quality experience that we can make ubiquitous for them.

All right. I wanted to understand what you think that the sell of the tools is. I think that’s very important for my next set of questions.

The other thing that I really want to ask is a question I ask everybody, but I think the stakes are a little bit higher here. It’s about decisions. How do you make decisions? What’s your framework?

We have a lot of different thoughts on how to make good decisions. I wrote a piece a long time ago called Eigenquestions, which is about framing not only the right solution, but how do you frame the right question? In terms of rituals we use, the most canonical one is something we do called Dory and Pulse, which is a way to solicit feedback and opinions so that you get rid of groupthink in the decision making process.

But those are probably the two that get mentioned the most if you were to ask teams here at Grammarly or previously at Coda or before that when I worked at YouTube or Google, or so on.

You can see where this is going. Let’s put this into practice. You launched a feature in Grammarly called Expert Review that generated suggestions on how to improve text. It synthesized advice from experts. It used my name among many other names: journalists Casey Newton and Julie Angwin, you can go down the line; bell hooks was in there, which is hilarious in its own way. 

You do not have our permission to use our names to do this. You had little check marks next to the name that indicated it was somehow official. People did not like this, I did not like this, and you removed the feature. Tell me about the decision to launch this feature with names you didn’t have permission for and the decision to unlaunch the feature.

I expected we’d talk a bit about this, so I have lots of different thoughts on it.

First off, I’d say I understand and respect how challenging a world it is for experts and idea generators these days. I’ve made a long career out of being a partner to folks like you, to folks like the ones you’ve mentioned. It deeply pained me to feel that we under-delivered for them. And I’d really like to apologize for that. That was not our intention.

On the specific feature you’re talking about, I’m sure we’ll talk more about it, but just to give the high-level view, my view of it is that the feature was not a good feature. It wasn’t good for experts, it wasn’t good for users. It was a fairly buried feature. It had very little usage. You mentioned it last week and talked about it. It took months for anybody to even sort of find it. All that doesn’t really matter. We can do much, much better. I believe we can and we will do better.

We decided to kill it pretty quickly. Notably, we decided to kill it while there was some feedback well before there was a lawsuit and so on. It was just not a good feature. It was misaligned to our strategy. It wasn’t the way we wanted to go after it. We have a much better view on how we think experts should participate in our platform, and I’m a lot more excited about that.

How many people work at Superhuman?

About 1,500.

So out of 1,500 people, how many people decided to launch this feature?

It was a small team. It was probably a product manager and a couple engineers.

Inside your decision-making process where you described a way of making sure you solicited the right feedback and then have groupthink, it never came up that using people’s names without permission would make them mad?

Maybe I should step back and talk about what inspired this team and what they were trying to do and what fell short. Let’s start with what they were trying to do. They were heavily influenced both by what we view users to want and what we want experts to want.

Let’s start with users. A lot of people talk about Grammarly as the last mile of AI. They say, “It feels like having your grammar teacher right next to you everywhere you work.” And so many of our users will say things like, “What would it feel like if instead of your grammar teacher, it was all the rest of the people in my life that could be with me as well? I want my head of sales to sit next to me and tell me I’m about to recommend the wrong product. I want my support person to sit next to me and say, ‘I’m about to email this person and you should know they had a big support issue last week and you should acknowledge that before you talk to them.'” 

That’s the core ethos of what we’re building. It is taking Grammarly and expanding it so that many of these other experiences come along with you. For some of those people, the people they want feedback from are the people they admire. It’s the experts in the world, it’s the people that they’re trying to look up to and trying to model. They try to do that today with LLMs. They go to ChatGPT and Claude and say, “What would Nilay think about my writing?” That was the inspiration for what the user was trying to do.

On the other side was what the experts were trying to do. As we formed our strategy here, turning Grammarly into a platform, the first people I called when thinking about this were a set of experts. I talked to some prominent YouTubers, I talked to a really prominent book author, and they all told me the same thing. It’s a really hard world for experts out there right now. It’s really hard to drive connection. If you’re a book author, your path to getting to your fans is you just keep publishing more and more books. And they all heard what we were doing and said, “Boy, it’d be really amazing to develop an ongoing connection with my fans. What happens when they put my book down? Can I still be with them and help them along the way?” It feels like the world shifted against them, AI Overviews stealing a bunch of their traffic and so on. This seems like a much better way to go after it.

That was the inspiration behind it. The team and the feature didn’t deliver. It didn’t deliver on either side of it, really. We ended up with an experience that was pretty suboptimal for the user and obviously suboptimal to the expert. The fundamental reason is something you said last week, that it’s really hard to distill what you would do as an editor based on the outcome of your published work. It’s really hard for AI to do that. We need your engagement for that to be a good feature.

So I think they launched something that wasn’t particularly good. Doing that and learning from it is part of the process, but that’s what they thought they were doing.

Sure. How much do you think you should pay me to use my name?

It’s really important to think about attribution and think about impersonation, and so on. As an expert, you have a trade you make on the internet. The idea is that when you put content out there, myself included, you hope people use it. You want to refer to other people’s content. You want people to link to you. You really, really hope they attribute you when they do. When somebody uses your content, should they attribute you? Of course. And to attribute you, you have to use your name.

There’s a different line which is, should people be able to impersonate you? And I think that is a very different standard. And we saw the lawsuit. Respectfully, we believe the claims are without merit. The idea that the feature is impersonation is quite a big stretch. Every mention was very clearly, “This is inspired not only by this person, but also inspired by a specific work from this specific person, with a clear attributed link to get back to them.” It’s far from that test [of impersonation].

If your work is used, should you be attributed? Yes, I think you should. That would be the nice contract. It doesn’t always happen. There are many products that will use your work and not attribute. We thought it was very important to attribute. I think that would be the view.

Let me flip around the other way–

Wait, let me ask you that question again. If you use my likeness, how much should you have to pay me?

We should not be able to impersonate you, period. We did not. If we use your work, if any LLM product or any product at all uses your work, they should attribute it to you and they should link back to you. That’s a human contract we have for how the internet is supposed to work. It’s a really important one. It should be the standard you’re looking for from LLMs too.

It’s a very different question you’re asking here, which I think is a more important one. I’m not really here to defend this feature. I don’t think it’s a good feature. I’m not trying to be close to this line. I think our main goal is to build a platform a lot like YouTube. You should choose to be on our platform. You should be able to choose and build an experience you trust. You should choose your business model. When you choose your business model, you should get paid for your contributions to it. That’s the model we’re working on. That’s really where I want to be.

I hear that you’re saying you’re not here to defend the feature. I just want to put you in the chronology for one second. The feature was launched. It is true. It took a while before we even discovered it, and wrote the story about it. It then blew up. Many other people wrote stories about it.

Your first response to the negative publicity was to offer people an email opt-out where if I didn’t want my name to be used, I could email Superhuman and say, “Please take me out.” Only after the lawsuit did you discontinue the feature. 

That’s not true, Nilay. We heard the first complaints from a handful of experts. They said, “I’d like to opt out of the feature,” and we addressed what they asked for. We then sat down and looked hard at the feature, and to be honest, I hadn’t spent any time on it. I came and looked at it and I said, “This is off-strategy for us.”

We announced we were taking it down well before there was a lawsuit. The reason we took it down is it’s all strategy, it’s not what we want to do. That’s not how we want to work with creators. We think we’re building a platform you should want to be on. We think we’re hopefully part of the solution for how you can take your work and make sure it’s present for people everywhere. It wasn’t our goal to be anywhere close to that line. But the feature wasn’t good, so we took it down.

You say it’s off-strategy for you. The feature obviously shipped. What made it on-strategy at the time it shipped?

At the time, the team believed they were doing that. They were looking at users and they were focused on a user need, which is, “I wish an expert could give me feedback at this moment. I wish my salesperson could give me feedback. I wish my support person could give me feedback. I wish my idol could give me feedback. I wish this expert could give me feedback.” In itself, I think that motivation that users have is a really good one, and I think one that I would encourage experts and creators to lean into. It’s a big opportunity.

Why would they lean into it if the value for that is $0?

No, it should be our job to make sure the value is not $0. We want you to–

How much do you think you should pay me?

To be clear, when you do the work to bring an agent, craft it, put it on our platform, then you should get paid for it. Just like how platforms like YouTube work.

Walk me through the economics. If you launch a platform that lets me say, “Okay, Nilay Patel can give you advice inside of Grammarly,” what are the economics of that platform? How much will I get paid to do that?

We’re building this business model now. Our store currently has a payment model for this that has a 70 / 30 revenue split that’s very similar to how a lot of other products do. If you want to go build an agent like that, you can do that today. There are a number of experts that already have. And that’s the core part of our strategy.

If you already had that system, why build another system that used my name for free?

We didn’t have the system at the time. And they are very different features. The team that built Expert Review, they were trying to address this need, they just missed.

How many times did you use my name?

Because it’s a legal case, I really can’t get into details of those types of things, but it was a very small number for basically everybody. The feature had very little usage.

Was there a set group of names? Was it just picking names out of the ether? Was it randomly hallucinating names?

It came right from the popular LLMs. So it’s exactly the same experience you would have if you came to Claude or Gemini or ChatGPT and said, “Can you take this piece of writing, recommend the people who would be most useful to give feedback on it, take their most interesting works and use that to try to give me feedback.” 

By the way, that’s a really hard feature to make good for users and it’s going to take work with people like you to actually deliver on that need.

Did you track how many times you were using people’s names?

We’ve certainly logged all the different interactions, yes.

So you do have a record of how many times my name showed up or Casey Newton’s name showed up, or anything like that?

It’s not tagged that way, but we’ll have to produce it obviously for a lawsuit.

Journalist Julia Angwin has filed a class-action lawsuit. There are a lot of ways that could go. You’ve said that claims are without merit. What did your lawyers say to convince you that the claims were without merit?

What did the lawyers say? It’s actually quite clear. It’s a layman’s test, it’s pretty obvious. It’s just not impersonation. When you look at the feature, there’s a disclosure next to every single link at the top and the bottom of the panel, very clearly stating these are inspired by these people. It clearly states we have no relationship with these people, that that’s the future. By the way, I’m not trying to defend it as a good feature. I don’t want to be on this line.

Maybe I could step back for a second and say, this is not the first time I’ve seen a situation like this. I used to run the team at Google — I used to run the YouTube team. When I got to YouTube, we had a big lawsuit from Viacom at the time, a very heavily watched lawsuit that we won. We won on summary judgment actually. We completely crossed the legal bar. But that’s not the standard we held ourselves to.

We looked at that and we said that the law doesn’t require us to do this, but we chose to do a lot more. We launched Content ID as a way to make sure that creators could find content that other people uploaded on their behalf. We launched an open creative program, which, as far as I know, is still the only platform with an open revenue share that’s out there.

I don’t think the legal standard is the right standard to be looking at. I’m not trying to get close to it. It’s fairly clear to me that we didn’t cross below it, but that doesn’t matter. We’re not trying to be close to that standard. We need creators to work. We need their business models to work for our platform to work, and it’s very similar to what happened at YouTube.

I have a lot of thoughts about YouTube. I’m going to ask you about YouTube. I have a lot of thoughts about the Viacom case. A lot of what happened with Google and YouTube is the foundation for the internet and policy on the internet as we know it today. That is changing because of AI. So I do want to ask you about that stuff because I think your history will shed a lot of light on how people feel about AI in particular today.

Sure.

I just want to stay on this one more turn. You’re saying “impersonation,” but that’s not the claim in the lawsuit. The claim in the lawsuit is the law in New York and California that bars companies from using names and identities of people for commercial purposes without their consent. And so, here you did have a commercial purpose here. You were selling the software and names were appearing as inspired by our names. 

I’m not in this lawsuit. I haven’t signed up for the class. The class hasn’t been certified. I promise I haven’t sued you yet. But the bar is very different from straightforward impersonation. It is the use of likeness for commercial purposes. And you’re saying it is without merit, and I haven’t seen you address that specifically anywhere.

I’ll have to leave the legal arguments for the lawsuit and for the court case. I think our view of it is that the set of work that was there was a fairly standard attribution that was well above the bar that any other product would do, what every LLM on the planet is doing and so on. And it didn’t come close to using name and likeness in any way that was beyond attributing the source.

You’ve already said this feature is bad, so I won’t hammer you on this too much, but I’m reading the edit that was generated with my name on it, which is just bad. I would literally never give this edit. It says I should “raise the stakes of a headline by adding emotional or stakes-based words that could underscore why this launch matters right now.” I’ve been an editor for over 15 years. I’ve literally never said anything like that.

You pinned the reason why. The idea that you can uncover your editing style from the end work, I just think it’s not possible. It’s very hard to come back from that end work and say, “What was the editing pass before that?” To do that well, you have to do it. You have to sit down and say, “Here’s how I would edit these things.” And I think you can provide that service and you can get paid for it. And hopefully we’re one of the platforms where you choose to do that.

So, you don’t have an annotated list of whose names are used in the feature, but you have logs of everybody who uses the feature, presuming those logs have the names in it, and you presume you’ll be able to provide that if you get to discovery.

I’m sure we’ll be asked. Yeah.

Do you think you’ll be able to provide that list?

I’m sure we’ll be asked. We’ll see.

Because it strikes me that one way you could get around this lawsuit is by just saying, “Actually, we never used Julia’s name until she went asking for it.” In the same way that OpenAI, when it responds to the New York Times lawsuit says, “This never happened until you prompted us specifically to do the things you said are illegal.” And here you have the same out. You could say, “Actually, until you asked us, we never generated your name.” Has that come up?

There are a lot of things in our defense that I won’t cover, but I think the core of this argument isn’t going to be that. The core of the argument is that what we did is normal attribution of content on the internet.

The reason I’m asking this very specifically is, “Hey, we never actually used your name,” puts you in a different spot than, “Hey, we have different feelings about the value of attribution.” The reason I’m asking this question as harshly as I’m asking it is that I don’t think the defense is whether or not people use the product or whether or not the names ever showed up. I think those are just clear cut, binary on or off. “Your name never showed up, you can’t sue us.” You’re saying the defense is, “Hey, that’s not how attribution should work.”

You used to be the chief product officer at YouTube, and YouTube is defined by creator attribution scandals. Every year, there’s another scandal about react videos. Every year there’s another scandal about the usage of copyright, about whether or not you can make an AI creator out of Marques Brownlee and just run a million videos of him and steal his views. It’s the essence of the YouTube creator ecosystem.

Do you know how YouTube reacted to this feature when we wrote the story? They invited me to an early preview of their AI likeness detection system, because they knew that would be good press for them. If you were still running YouTube, would you have ever allowed a feature like this to go out?

It’s interesting the way you just described it. First off, some of the ones you described, describing react videos as scandals is a very interesting way to describe it. Because I think–

Oh, they’re absolutely scandals.

I understood your definition. They’re also incredibly popular and have led to a whole genre of content being created. Likeness detection, Content ID, they were all fantastic tools for creators. My team built the Content ID tool with the same idea. 

If somebody does that to Marques Brownlee and they copy his videos and put them up, then you can use that tool and he can not only go claim them, but he can also go make money on them. That is a tool we built for YouTube, and I think it’s been incredibly popular. We took what looked like a scandal and went well beyond it. To be super clear, it’s not what the law requires.

No, I understand what some of the law requires, but the use of Content ID and the issuing of copyright strikes, which is something I’ve experienced, if you issue a copyright strike as a creator against another creator, that is a nuclear move, that comes with severe social and community consequences.

To be clear, if you use Content ID and you use it for monetization, you’re not issuing strikes.

Right. But I’m saying the YouTube economy writ large is defined and in many ways the products are built around issues of attribution and payment and monetization — where the views flow and where the money flows. 

Content ID is a brilliant innovation because it allows people to get some views and the right people to get paid. YouTube doesn’t exist without music. If the music is ever on YouTube, the publishers get paid because Content ID can identify the music and get them paid. I understand that. But that is a system that tracks attribution and delivers monetization. 

I’m just saying, I don’t see how YouTube could have ever said, “We’re going to let Marques Brownlee edit your video without paying Marques Brownlee.” It wouldn’t exist in that ecosystem. 

No, you just said it. What YouTube did is say, “When it happens, we are going to help you find it,” but you’re not preventing someone from doing it. It’s a very different standard.

But you’re making sure that the people get paid.

You’re making sure after. To be clear, the idea of copyright is very different from a name and likeness claim. If I built a video that said, “Hey, I really like Marques Brownlee, and here’s what I think he would say,” or “let me tell some jokes about Nilay,” it’s a very different standard. The standard for YouTube was about copyright, and that’s a set of regulations that are governed by totally different parts of the law. 

In that case, you have a claim, there’s a DMCA statute that allows you to go and enforce your copyright. That’s not actually what we’re talking about here. But the principle of what is similar is that in both cases there’s a law, and the law does not really meet the creative bar. I think the goal of the community, the goal of products like ours, working with people like you, is not to use the law as the test. The goal is to get well beyond that to align our interests, such that your success is our success, and that should be our goal.

Are we required to do it? No. I don’t think that’s a requirement. We choose to do it because it’s the best way to build the right products for our customers.

I used to be a copyright lawyer. I’ll happily admit that I was not the world’s best copyright lawyer. I understand that people don’t understand the difference between copyrights and trademarks and names and likeness. I’m saying that AI is collapsing those differences faster than ever before. There are European countries that are just openly suggesting you should expand copyright law to include likeness. 

I should be able to copyright my face, and then that means I can slide in under the existing legal regime instead of hoping that the United States Congress in 2026 can reach a resolution on expanded likeness protections. This is a thing that is being suggested because copyright law is more or less the dominant regulatory framework that exists on the internet.

I look at the big social platforms like YouTube, Instagram, and TikTok, and they have built all these systems to respond to copyright law — specifically copyright, things that can be protected by copyright law, that can be monetized in different ways by copyright law. Our likenesses are not one of them. Our names and faces are not one of them.

Yeah.

This seems like the place where the things you’re allowed to do and the things you should do are going to be ever more divergent. You are the one who’s experienced it the most loudly of late. And I’m curious if you’ve learned anything other than, “There’s what the law says I should do and there’s what I should do and we’re going to find the line down the middle.”

We’ll see if the laws find a ground on that. I do think it’s a catch-22 as a creator. The copyright law has been around for hundreds of years now in its various forms. It started like the way music composition was licensed, it started with Mozart and Bach. It has grown since then. Almost every country in the world has reached a very similar standard.

There’s a very thin line between taking publicly available work and being able to refer to it, and copying it. The idea that defining all references to work as being uses of names and likenesses, it would break the internet, it would break your business. You wouldn’t be able to refer to me. How’d you get on a show last week and talk about me?

Just to be clear — I don’t want to be all inside baseball about making a podcast, but we made you sign an appearance release to come on the show.

To come on the show. But you talked about me before I came on the show. Of course you should be–

We talked about you before you came on the show, but in order to be a real media company and not fly-by-night and then to use clips of your face talking, our lawyers need a release. And if you don’t sign it, they won’t let me use the show, because they need to be protected against you showing up tomorrow and saying, “I didn’t give you permission to use my face.”

No, I understand that. My point is broader than that. You talk about lots of people and that’s part of discourse. That’s part of how we work. Your articles will link to people, you attribute them. I think that’s really important. And if you drew a line that attributing something is like using their name and likeness, then it’s a very hard line to draw.

Again, this wasn’t an attribution. You just made something up and put my name on it. There’s no attribution here. This isn’t anything I ever said. It’s not something I would ever say. I’m not even sure how you would get to the idea that based on my work that I would ever say anything like this. There isn’t an attribution here. There’s no work that exists that would lead you to this outcome with my name attached to it.

I’ll repeat: The feature was, “Here’s a suggestion generated by a specific work from a specific person.” Everything is clearly indicated that it’s a suggestion generated from–

Wait, I’m sorry. You think in my role as editor-in-chief of The Verge and co-host of The Vergecast, I emphasize the importance of crafting compelling headlines that convey urgency?

I already told you it’s a bad feature. That’s not what you’re questioning.

You’re telling me there’s attribution and I’m just wondering what the attribution is.

Just read the rest of it. It says, “Based off of this work from you, we asked–”

No. It just says, “This suggestion is inspired by Nilay Patel’s The Vergecast.” I promise you on The Vergecast, I’ve hosted that show for a long time. I have never said, “What emotional or stakes-based words could underscore why this launch matters right now?” The Vergecast is not a show about editing headlines about smartwatches, first of all.

I understand, yeah.

So I don’t know how you got from A to B and then I don’t know why you think that’s an attribution.

If you were to go and read someone’s work, put it online—you do this on your show all the time—and say, “I read this person’s work and here’s now my conclusion from it,” you should decide whether that is a suggestion generated from attribution or not. I told you I think it’s a bad quality suggestion. I’m not trying to defend it. I don’t think that’s what we want to talk about there. But the question, when you publish work, can humans and AI use it to generate other suggestions, other impressions? They can, and you would like for them to attribute it.

But it’s not work that that person made. Hallucinating a thing that you thought I would make and then saying you’re attributing it to me, doesn’t provide me any benefit. It might actually detract from the benefits I could provide to other people. That’s the disconnect that’s in my brain. I’m not sure why this is an attribution.

If I’m like, “I talked to Shishir and I think here’s what he would say,” that’s very different than saying, “I read all of his work and I’ve asked whatever quick version of Claude or ChatGPT to just make something up and I’m going to put his name on it.” There’s something meaningfully different there. And it doesn’t seem like you’re willing to concede that.

No. I’m not. It’s fairly clear that generating a suggestion based on somebody else’s work… just use the simple task of a human doing it. If you generated a suggestion based on someone else’s work on your show and you said, “I read this person’s work and here’s my impression from that, this is what I think they meant,” you could build a whole show based on that. So you don’t always get it right. You don’t always say things about the people that you’re commenting on that are correct.

Right. But I’m not attributing that idea to them. That idea is clearly mine.

The feature is very clearly stated that this is a suggestion developed by this feature based off of this work.

Let me ask you a different question. I’m curious about this across the whole sweep, from YouTube to now. There’s an NBC News poll that just came out about how people feel about AI. And the answer is bad. People feel badly about AI. AI is polling behind ICE and only slightly above the Democratic Party. This is a tough spot to be in. It’s a -20 perception.

I think the reason for that is because it’s so extractive and the value isn’t there. I would compare this to YouTube, which a lot of people thought was pretty extractive. You fought a pitched copyright battle about YouTube, about whether South Park could be on YouTube without permission, and Viacom was going to sue you. That case was fascinating because the public was decidedly on YouTube’s side.

Oh, that’s an interesting memory of it.

I covered that case. I was in law school studying copyright during the case. The vast majority of people were like, “YouTube is really useful. We love it. And these big Hollywood companies suck.” When Napster was under fire, the public was not on the side of the record labels. They were not on the side of large companies. They were on the side of file sharing. Because the utility was so high regardless of the economic or social cost. I could keep going on and on with this. You can tell people all day long about the labor costs of Uber and they’re still going to use Uber. 

There’s a trial right now about whether social media platforms are damaging to teens’ health, whether they’re defectively designed products that hurt kids. That trial is ongoing as we speak. The jury is impaneled right now, and people are still going to use those platforms because they don’t care.

The environmental costs of big, stupid cars — you can tell people all day that trucks will ruin the environment, Americans will still buy trucks. That’s what we’re going to do. AI is only perceived as extractive. It’s less beloved than ICE. That’s crazy to me. Do you understand that the extractive nature of AI is causing a problem for the whole industry? Because you’re sitting in the middle of one of these controversies right now.

I think you’re drawing a pretty broad link for why people are afraid of AI.

I think great consumer products that provide a lot of value overcome their social costs.

Number one, AI has a lot of challenges ahead of it. There’s lots of opportunity. It does meet your other tests. It has created some of the most popular products in history. And there are many people who would have you pry any of those products from their cold, dead hands.

I think that the challenge with AI right now is that it’s challenging people’s sense of the future of their humanity, their ability to work. Those are really the challenges there. The line we’re talking about here, I don’t think that’s actually what you’re reading into that poll.

What would you read into the poll where AI polls below ICE?

People are scared for their jobs.

You think people are just scared for their jobs?

I think so. I think–

Do you understand that that’s extraction? You’ve taken the sum total of everyone’s work on the internet and now you’re going to use it to replace human beings and their jobs without any economic recompense.

That is certainly one way it could replace people’s jobs. I don’t think that’s the way that most people are worried about how it could replace their jobs. I think they’re wrong about it. I don’t actually think it’s going to replace as many jobs it’s going to create. One of the reasons why is that our model for thinking about AI is about bringing it to people and expanding their work. We like to call it the product that helps you become a superhuman. So I think they’re wrong about it. 

But if you’re asking me why it polls so low, it’s because the copywriter feels like, “Maybe I’m not going to need it anymore.” It’s the salesperson who says, or a support person who says, “I wonder if an agent’s going to be able to do my job.” I think the idea that it has something to do with name and likeness is a pretty big stretch.

You’re sitting in the middle of a controversy where a lot of people are mad at you for appropriating their work. If you’re a copywriter at an ad agency — I know a lot of copywriters at agencies — they’re saying, “You took all of my work.” Not you. “The AI companies have ingested all of my work for training and now they’re going to replace me and no one got paid.” Hollywood is basically like, “No one’s paying us for this.” The people who write on Tumblr are saying, “Now OpenAI is going to make a porny fanfic for people. That was our job. Why didn’t you pay us?”

You’re absolutely right. Creators are facing a very hard road right now. I don’t think it’s caused just by this feature or just by the latest advanced AI. They’re facing a hard future for a lot of different reasons. But the poll you’re referring to is of the broad population, and the broad population is not creators. The broad population has jobs that they are afraid may not be available to them. Whether they’re a truck driver, whether they’re a support person, that’s what they’re afraid of.

I’m not diminishing the fact that creators also have an issue with AI. I’m just pointing out that the broad impression of AI, the challenge we have with it, is that the entire industry has done a really bad job of helping people understand why a technology like this can help them and not prevent their job from being taken away. And most people just aren’t creators.

I’m not objecting to what you’re saying about creators. I’m just saying most people aren’t stressed about that because that’s not their job. That’s not what they’re individually afraid of.

No, I understand what you’re saying. I’m just pointing out that almost every major technological shift has been extractive in some way. Google copied all the books in the world without permission, and then we had a Google Books case, and Google had to win that case. And they did. They were able to do it. 

Google had to win the Viacom case with YouTube. Google had to win the Google Images case against Perfect 10, which was maybe the least sympathetic plaintiff of all time, because it was a porn company, and Google was doing Google Image thumbnails of softcore porn. It was obvious that Google was going to win that case, but they still had to win that case. 

All of this stuff got litigated at pretty intense levels in ways that are precedent still to this day, and it doesn’t feel like we’re spending the time to litigate, “Hey, you can just make a deepfake of my face and use it to sell headphones on Alibaba.” You can just start a company and say, “Well, it’s attribution, so I’m just going to use the names of famous people on my product to say these are the edits.” 

There’s a link there that seems very direct to me, maybe just as a creator, but also I would submit to everyone else who says there’s a pretty extractive cost here and the consumer benefits are not nearly as clear. 

In some ways I like the YouTube analogy. It’s a good analogy. When I talk to our team about why the legal standard shouldn’t be the minimal standard we try to hit. I will also tell you that what we’re doing here at Superhuman, I don’t expect to be very close to this line. There are other products that are very close to this line. Our core strategy is about building a platform that you can choose to participate in or not. I don’t think it’s going to be a fine line for us. I know in this case, we built a bad feature. It was not received well by either users or experts. I don’t like that. I killed it for that reason, but I don’t expect to be sitting here…

The YouTube analogy: you’re right. The Viacom case had to get litigated for YouTube to exist. And if it had gotten litigated the other way, YouTube wouldn’t exist. Actually, most of the internet wouldn’t exist. And so the idea that it got litigated that way, it was a win for everybody. It was a win for society. I do think it was a win for YouTube. I don’t expect that to be our case here. This is not a line I’m going to be close to.

There are a bunch of copyright cases against the AI companies. I feel like I should disclose that our company, Vox Media, has sued Google over ad tech. It has nothing to do with AI or copyright. I feel like I need to disclose it because I disclose it every time. Vox Media sued Cohere, one of the AI labs, over copyright infringement. The New York Times has sued OpenAI.

There are a million of these copyright cases floating around. There are more every day. One of them could go the other way, and this industry could faceplant. What do you think happens if one of the big AI labs loses a copyright case?

Are you asking me as someone watching the industry or are you asking me in my Superhuman role?

Both. 

My Superhuman role is straightforward. Whatever the models do is what we’ll use. And so if the models end up needing to restrict that behavior, then that is what it is. We sit on top of the models. I don’t think we’ll be the ones in the middle of those cases. If I look from an industry perspective, I think it’s a really hard case, in both directions. I have real empathy for both sides.

Copyright law is, like you said, what has allowed the internet to work, and not everybody is happy with how the law draws a line. You’re right that YouTube tested that line in a new way with the Viacom case and so on. What OpenAI, Claude, and Gemini are doing will test it in a new way. I hope they find a good line for it. I don’t think that’s where we’re going to be. We’re not going to be the ones in the middle of those lawsuits or those figuring out where that line is.

If the incremental cost of a token skyrockets, because suddenly the AI companies have to pay massive licensing fees to copyright owners downstream, what happens to your business?

I don’t think it really matters to us because it’ll all happen in the models underneath us. It doesn’t matter to us as our own entity. It matters to me as a citizen. I think it’s really important. But I would also remember that for us, the primary agents people are trying to build on Superhuman have nothing to do with this. The expert case is one case. 

What people are doing with our product is they’re going and taking their sales methodology and turning it into agents for their salespeople to be able to use. They’re taking their support tools. They’re taking their calendars and making sure that as you’re writing an email and saying, “I can meet tomorrow at 6PM, please make sure that I’m actually free then.” Like I said, this is not a common part of our business.

No, I’m not saying the expert review part. I’m saying you’re describing, “Take all of my sales literature, take my calendar,” that gets loaded in a context for a model that you call, right?

Yeah.

If the incremental cost of a token in that model goes up because the AI companies suddenly have to pay a bunch of copyright licensing fees, what happens to your business?

If I were those companies, the solution I would have isn’t to go distribute that cost across all users. I would charge users a subscription for using that information. That’s the business model they should have.

My personal view of what should happen is I should come to ChatGPT or Gemini or Claude and I should prove that I’m a New York Times subscriber, and then it should give me answers for The New York Times. And The New York Times is going to have to make a choice of, “Do I only want my content to be used for my subscribers or not?” But if I were those companies, that’s what I would promise.

All these cases are different. So I’m going to generalize here and you can attack me for generalizing and that’s fine. But broadly, they split into two lines. There’s one, the thing you’re describing, which is you spit out content that I’ve already made, like Suno can make a Beyonce song that’s copyright infringement on output. Other set of cases where I think much more important–

It’s on input.

It’s on input, it’s on training. And saying, “You ingested all my material without permission.” That’s also copyright infringement. If that goes the wrong way for the model companies, their cost structures change in retrospect. You can’t build the systems you’re describing because the model itself–

No, that’s what I was responding to. So output, a copyright law covers it. If you produce something that could be mistaken for the work of another person, then they can file a claim, they can get it taken down; if they choose to leave it up, you can choose to negotiate a revenue share agreement or whatever you might want to do with that. Output is cleared. Input is not cleared, like you said, and the cases haven’t been resolved in a particularly clear way.

The point I was making is if I were them, I wouldn’t take the cost of input and distribute it across all users. I would split the model. If it really went that way, I would say, “Fine, you don’t want your content there. I will build a version of the model that is just for New York Times subscribers and charge them.”

Your particular question was, “Will that cost get passed along to the other users of the LLMs?” That is what’s happening right now. They are paying for that content. It is being passed to us. Does it matter to us? Frankly speaking, the pace of innovation in that category is so high, the profits being generated there are so high, that no, it hasn’t mattered to the upstream users — or to us, to ChatGPT users, Gemini users, and so on. It hasn’t stopped their growth at all. Will it someday? Maybe. I don’t know.

But my point was more that in this world of output, copyright is fairly clear and the law covers it pretty well; input copyright is not that clear. It’s not clear for good reason. If you’re a human and you read a book and then you learn something and then you talk about that thing, what should happen? And that’s a legitimate question that hasn’t been well tested in the courts.

I don’t think the industry is going to take that cost and just pass it along to all users, but we’ll see. If it does, then it does and we’ll have to deal with it. Everybody will.

Most humans cannot infinitely scale to create trillions of dollars of enterprise value by reading one book. That’s the difference. To get that value at that scale, usually lots of people have to buy copies of the book and the economics spread out. The scale is the difference.

I understand that is a very fair argument, that this is not the same as a human reading the book. Obviously that’s the line being taken there. I would postulate that whatever way that case ends up, the correct answer for experts is it’s time for a new business model. And I think the idea is that you’re going to get into exactly the right spot and you’re going to get pennies for every query coming through Gemini. That’s certainly one path. 

When I went and talked to people about what we’re doing here at Superhuman, what they told me is, “Actually, I don’t really want to be fishing for pennies whenever my work gets used. I want to build connections with people. I didn’t build content to put it out there and get paid a fraction of every use. I want to go build a product that actually connects with people. I want to do this.” YouTube offers a great way to do that. What we’re doing is Superhuman should offer a great way to do that as well.

Let me ask you about that specifically. I wasn’t at South by Southwest. We have a little baby. I didn’t travel this year, but I watched Instagram. I experienced South by Southwest through the magic of Instagram and TikTok. 

You had a suite there at South by Southwest. I looked at some of the videos. The caption on one of the Instagram carousels… I’m just going to read you the caption. This is from the Superhuman suite at South by Southwest. There were a lot of talks there. The summary of the talks was, “AI can’t replace human creativity, empathy, or emotion. It won’t take all of our jobs, but it will reshape how we work. And in the AI era, taste and judgment are more valuable than ever.” Valuable on what metric? Is it dollars?

Valuable on every metric.

Specifically dollars. Dollars are what I pay my mortgage in. Is it dollars?

I’m sorry, I didn’t understand the question.

If my “taste and judgment are more valuable than ever,” but it’s also infinitely replicable and you think I need a new business model or every creator needs a new business model or–

Sorry, you made a big leap from that.

How do I make more dollars? If my “taste and judgment are more valuable than ever,” where do the extra dollars come from?

So just to be clear on the tagline for Superhuman, what we believe is that we can help all our users become superhuman by bringing them tools that allow them to expand their work. The main way we think about people is that Grammarly doesn’t do your work for you. Grammarly helps make you a better writer. And you still publish your essay, you still post your article. It’s our job to turn you into a superhuman. That’s our promise to our users. That’s what the banner’s about. Your question is a very good question.

The banner says “taste and judgment are more valuable than ever.” I’m just asking you to define the value and what value is going up and what value is going down.

If you’re using Grammarly and you’re a student or a salesperson, it is your taste and judgment that is actually what gets valued in the end. We’re here to help make sure you don’t make a mistake. We’re here to help make sure that you present yourself the best possible way. That’s what that banner is about.

We have 40 million users who use our product. The vast majority of them work in professional industries, they’re salespeople, they’re support people, that’s who that’s addressing. And we’re trying to tell them, “Don’t worry about losing your job when you use our products because we’re here to help you scale more. We’re here to help you be a better version of you.” That’s what that banner is about. That’s what our promise is about.

We have a proposition for you, Nilay, as well, which is that you can now become one of those assistants to all those people. Many of them have no idea that they could use your help, but you can build that relationship with them like Grammarly does. People personify Grammarly all the time: “My high school English teacher sitting next to me everywhere I work, that makes me better. It makes my trust and judgment shine through.”

I would like your agent for people for whom you matter. You should be able to build an agent that sits right next to them and you can actually feel like their editor. Now, you have to do some work to make that a good experience. You’re going to have to figure out how to document your editing style in a way that actually produces a good result, not like the one you quoted earlier. But if you can do that, you should be able to build that relationship. You should be able to construct it the way you want, you should control it, and you should be able to make money on it.

Wait, hold on. You understand that you’re saying I have to do that because all of the work I’ve produced in my career to date has been taken without compensation by AI companies.

I didn’t make that statement.

What? You’re saying I need to invent some new business model as an expert and upload an agent of myself to your tool and then advertise it to get a 70 / 30 revenue split from however many people use Grammarly, because my actual body of work has been reduced to zero value. That’s a pretty hard sell.

I’m not here to tell you how to answer every question about what’s changed in the creator economy. One way to look at it is that the path of being a creator has become harder. I assume this podcast is going to end up on YouTube and Spotify and so on. There are paths to becoming a creator that become easier. There were folks that, when YouTube came out, told us all the same things and they said, “We don’t understand. Our business model is screwed over there. Why should we work on YouTube?” 

The ones that looked at it that way and saw it as replacement ended up not moving forward to the future. Obviously you did. You run a show on all these platforms and you figured out a way to turn that into a business. You saw that opportunity and you expanded what you could do. 

If we look at AI from that perspective and say, “AI is here and it’s reducing the number of people who need to traffic to my current experiences,” that’s one way to look at it. There will be some creators that look at it that way. I would hope we look at it the other way and say, “Some of these platforms are going to give you a way to participate, are going to give you a way to take your expertise and put it in front of people in a way that actually helps them in a different way than you could connect in the past.”

That’s a bright future. I’m not really trying to say you have to or you don’t have to. It’s an expansion opportunity. I’m not really here to defend what some other company is doing with content. What’s happening there is happening there. I’m just saying creators feel that pressure. We recognize it. There’s an opportunity. I had one creator tell me that their traffic in just the last year from Google is down 50 percent. They said that with AI Overviews and so on, traffic is down 50 percent. They sell books.

My reaction to them was, “That really sucks. I understand why that really sucks.” I would also tell them, “If you’re a book author, waiting for people to search your name on Google has got to be the least good way to monetize your expertise. So now let’s talk about how we can take what you do well and get it in front of people in a way that creates value in a different way.”

Maybe we can do it in a way and get it in front of people in a way that creates value in a different way. And maybe we can do it in a way that isn’t tons of incremental work for you and brings you a new type of opportunity. I think platforms like ours are going to give that opportunity to people who choose to take it. Not everybody will.

Can I extend this to you as the CEO of a software company?

Sure.

This is the same argument I hear about the frontier models, and the AI companies and their relentless expansion into every category. And then what you might call the SaaSpocalypse. Why would I pay your margin on tokens that you’re buying from them when I can just buy their tokens directly and just talk to Claude? Why wouldn’t I just vibe code something that looks like Grammarly and run it instead of paying… what, you’re like $160 a year? This is the thing that’s coming for the software industry writ large. Do you feel that same pressure?

The SaaSpocalypse is not an easy word to say. It’s a little overstated. I’ll give you my view of it. There is a lot of software. The ability to build software is definitely getting much, much easier. I think the reasons why people choose to use software is often because it does a job particularly well and that there’s often a network effect associated with it. 

I’ll give you an example and I’ll just focus on customer relationship management (CRM). People look at the SaaSpocalypse, they go and try to judge Salesforce and say, “Why would anybody pay for Salesforce? I could just vibe code my own version of it.” Well, first they say, “Why would anybody have a CRM?” And then if they do need a CRM, why would they pay for Salesforce?

I’ll answer both questions. Why pay for a CRM? When you have groups of humans working together, you need software for them to work together. If I have one salesperson, I can keep all my sales in my head. If I have 10 salespeople, maybe I can do it with a spreadsheet. When I have 100, I need software to keep them together. That software today is called CRM software. When I have 1,000 agents selling on my behalf, I’m going to need a way for them to coordinate with each other. It might be different, but I do think it’s going to be important. Why is it going to be products like Salesforce? I don’t know if it will be Salesforce, but the power of network effects is going to become much higher.

You’re going to say, “These are products for which I’m going to pick the product that is plugged into the ecosystem in different ways.” Why would people rebuild Grammarly? I’m sure they’ll try. My hope is by that point, we are the platform for all the best agents that work right where you work and you [don’t] have to go replicate all of them. I’m sure there will be people that will, but I think most people won’t. That’s an important bet for how the software industry moves on. The need for software is only going to increase. The importance of network effects will only increase.

You don’t think that OpenAI, or Anthropic, or Google will say, “Well, Grammarly is pretty useful. We can build a tool that looks just like it in seconds and ship it and kill their product. They’re just buying our tokens anyway. We can just kill them pretty easily.”

The ability to build that tool has existed for a long time. So if that were true, our business wouldn’t be growing. We wouldn’t have 40 million people using it every day. The idea is getting easier and easier. Yeah, we can’t stand still. If we stand still and don’t continue to innovate, if we don’t build that network effect, if we don’t continue to add value for people, we’ll get caught. That’s always true. 

I just want to end on a big thing. Again, you used to run these platforms. You’re on the board at Spotify. I know you think about the economy here and how work gets produced and who gets paid as deeply as anyone. I look at the shape of the media landscape right now, the information landscape that you might call the internet. And I say, “Boy, everything is slowly turning into QVC.” Making this stuff is getting devalued every single day. Being the person who makes the stuff is getting harder and harder. It’s something you’ve repeated several times now over the past hour. 

At the end of it all, the creators all have to pivot to selling something. The Paul brothers have to sell you bottled water. Mr. Beast has to sell you energy bars. We’ve devalued the work so much that unlike any other industry in the world, the internet industries, the information ecosystem pivots from bits to atoms. That’s pretty rare in the history of business.

Most businesses pivot from atoms to bits. The margins of bits are historically much better than the margins of atoms except on YouTube, except every major artist has to be on tour forever because the money from selling music itself is so low. AI is bringing that at scale. You can feel the pressure. This whole conversation has been about that pressure.

Maybe the legal doctrines don’t line up exactly and maybe I’m making too many generalizations and I hear the criticisms that you’ve parried me with, but that’s what I feel. All of these platforms, at the end, are becoming about someone trying to sell you something else. AI is just accelerating that. I’m just wondering where you think the endpoint is.

It’s an interesting characterization. There are multiple business models out there. What you described as bits to atoms, I think is one way to look at it. I’m sure some creators feel like the ad revenue from YouTube is not enough. It’s because there’s an opportunity, right? Why would you not take an opportunity? I think “have to” is one way to describe it. “Get to” is a different way to describe it. The other thing I’d say is I don’t really think it’s quite accurate to say bits versus atoms. It’s much more advertising versus subscriptions versus purchases. And I don’t think the spread on that is really about the bit and atom piece. It’s about the connection piece.

There are a set of platforms that are built off eyeballs. What I built at YouTube was primarily built off eyeballs. Over all of history, the amount of advertising spend has always been some percentage of GDP. It’s covered between 2% and 4% of GDP forever. That gets divided up amongst all these eyeballs and that is one business model. Yes, the number of creators fighting for that has dramatically fragmented over the last couple decades on every platform. What can come from that is smaller. There’s also the ability to sell products. The ability to sell products is as old as time, and in the middle of that is the ability to build connections. Those products tend to do a lot of work with subscriptions. 

It’s interesting when we think about some of my favorite creators, many of them subscribe to the 1,000 fans theory: that if you can get 1,000 people to pay you 100 bucks a year, you all of a sudden have a $100,000 business. There’s a whole class of people who have decided, “I can either go somewhere I get a little bit of money every time somebody happens to blink and look at me. Or I can get them all the way down the funnel to buy my hamburger or my water bottle. Or in the middle, I can build a deep enough connection with a person that they’re willing to pay me a substantial amount of money on an ongoing basis and I don’t need a lot of them. If I can do that, then I can build a real business out of it.”

There are some fantastic creators who have done a really good job of that. Many of the ones I’m sure you know. What I’d like to do and what we’re trying to do with Superhuman and our agent platform is enable people to build that level of connection. A lot of them are doing newsletters. It’s very meaningful to say, “I got a newsletter. It’s 100 bucks a year. Here’s how you can do it. 1,000 people gets me to 100 grand. 10,000 people gets me to a million bucks a year.” That feels like a meaningful connection.

In our case, I’m saying AI is going to allow us to do more than show up in your inbox. It’s going to allow you to show up with a red pen and a blue pen right next to the person and say, “I can help you in the thing you’re doing, at least the part of it that we’re working on.” And I’m willing to gamble that, can you go get 1,000 people to say “that’s worth 100 bucks a year to me”? I think you’ll be able to.

Wait, I’m just going to ask you this as directly as I can. Do you think that feature will be good?

It’ll be as good as the work that the creator puts into it. Are all newsletters good? No, most newsletters suck. There’s no guarantee that the newsletter platform can make them good. Is every YouTube video good? No, mostly they’re quite terrible. But does it allow–

I don’t know what your tool looks like to build an agent inside your platform, but I haven’t seen an LLM that can replicate my writing, let alone my editing. And you’re dependent on the capabilities of models themselves. So I’m asking you kind of a general way, but you know how your tool is built, can you actually make a tool that can do that well?

I think so. I would say that we did a pretty good job with Grammarly, that we replicated a grammar teacher pretty well. Can we do that with a broader spectrum of things? I believe so. We have some good evidence of it already with some of the agents working on our platform. Can we build a good one for you or can you build a good one for you? I don’t know. I’d love to work with you on it.

What does that tool look like? What does “build a good tool that lets me edit” look like?

It’s what you said earlier, you have to write down that viewpoint of like, what is your editing like? 

No, I mean, literally describe the interface that your tool provides me to do that.

Oh, the big part of the interface is a prompt box in what we call triggers. You’re going to say, “Here’s my instruction.” Think of it like you’re going to publish your manual and here’s your trigger. Here’s a set of things that say, when you see this, do this. And here’s my manual, here’s how I think about things. And when you see this, do this. You gave the example of feedback on a headline. You didn’t like the feedback you gave on the headline. It’s reasonable. I wonder if you could write down what feedback you would give on a headline?

Let me suggest a different way to think about it. Pretend for a moment you were trying to train someone else. You’re saying, “Hey, I’m going to hire an employee and I’m going to scale myself and I’m going to teach them to be like me.” How would you teach them? You’d probably sit down with them and you’d write some things down. And then the second thing you’d do is you’d watch them do it and then you’d correct them.

The other piece we have to do is we have to say, you need to get feedback and you need to be able to come through and say, “That was a shitty suggestion. Don’t do that again.” And so that’s what that interface has to feel like. You give a set of instructions, you give a set of triggers, and then you get feedback. And you say, “This worked, this didn’t work.” You’re going to come back and you’re going to look at it and say, “Yeah, that clearly didn’t work.” Maybe it didn’t work for the user, they ignored your suggestions. Maybe it didn’t work for what you think was good work. You looked at the output and said that wasn’t particularly good work and you’re going to train it.

The idea of being able to train a custom agent for each person, for each product, is really interesting and compelling. I don’t think it’s going to be easy to do for everybody, but the people who do it well will be like the prominent YouTube creators of today. You’re going to make a very deep connection with a broad set of people in a way that you’re never going to capture with ad dollars or with selling water bottles.

Do you have an example of one of these that you think works well today?

I think Grammarly is the most obvious one. Most of the other really good ones—

Grammarly is like grammar, right? It’s rules-based and a very specific one. Grammar has rules, it has a logic. It’s squishy on the margin, but there’s good grammar and there’s bad grammar and you can pretty clearly detect the two.

It’s actually interesting. Grammarly is a stack of models. The base level model is actually spelling. Spelling is the very core definitional thing. Grammar has pretty good rules. Spelling has really clear rules. Grammar has pretty good rules. 

But actually the reason why people use Grammarly is we go well beyond that. So we do advice on tone, we do advice on style. We do, “Hey, this is making you sound harsh.” These are all things you get when you pay for Grammarly. That’s the type of suggestions they get from us and they seem to like them — 40 million people use it every day. There’s a wide set of partners that have jumped onto the platform and built agents as well. Many of them are closer to tools.

So one launched a couple of weeks ago from Gamma that helps you build a really good slide deck. They did a lot of work to take “what did you write?” to “how do I turn into a slide deck?” We’ve seen a lot of them being built inside of companies. The sales example I gave, which is a very common one, is, “Hey, if I’m a head of sales, I have a sales methodology. You should always ask these three questions. You should always pitch our product in these ways.” They write those down, they turn it into an agent and say, “Make sure this is in front of people while they’re working.” And I think some of them are doing great.

Those are enterprise uses and I actually understand the sales use case a lot. You need the salespeople to all say the same thing all the time. I understand they don’t do that all the time. We have salespeople.

Actually, can a creative one work?

I’m asking because I don’t think taste is rules-based. Our producers are in the background here just in a puddle, because part of their job every week is to try to write like me. They get a lot of feedback from me directly on that. I’m literally editing the documents so I can read the intros and outros and I’m changing the questions. And it’s really hard even when it’s just three people who have spent years working together to try to get to an output that works. And they’re really good.

Yeah. It’s totally fair. My guess is the types of experts that will first prevail here won’t be the ones you’re describing. Those that make something creative, sound unique, make it sound better, are probably not the ones that’ll work first. But I do think there’s a set of experts and creators that will work great. Maybe I’ll pick the ones that are right next to Grammarly.

There’s a set of teachers for whom this is going to work really well. They’re going to say, “Hey, in addition to making sure your grammar is good, it looks like you’re writing something about history. I can probably help you cover history more clearly.” It’s not quite as clear as grammar facts, but it’s pretty close. “This is what happened in this period. You should know these different elements of it.” Teachers will be a great example of that.

What are LLMs really good at? They’re really good at averaging what everybody says. So can they do something really unique like you do? No, probably not. Can they take some part of your suggestion and turn it into something useful enough that you can get 1,000 people to pay 100 bucks a month? I bet you can come up with something because the bar isn’t high. 

I know we’ve flipped the conversation around a little bit. If we’re talking about you and your business opportunity, you don’t really need to replicate yourself the way you would be in person. You just need to create enough benefit that 1,000 people pay you 100 bucks a year. That’s what you need to do. Is there some part of your methodology that you think is so good that people would do that? I bet there is.

I’m going to have to think about that quite a lot. Thank you so much for coming on, for answering the questions, for being game to answer the questions. I appreciate it.

Sure.

I have a lot of other questions. We’re going to have to have you back sometime soon to expand the full scope. What’s next for Grammarly? Tell the audience what they should look for.

We’re very busy building out Superhuman Go. We have a big set of launches coming in the next couple months, so keep an eye out for that.

All right. Shishir, thank you so much for being on Decoder.

All right. Thank you.

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