Confronting the CEO of the AI company that impersonated me

19:16Nilay Patel:Did you track how many times you were using people's names? I mean, 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? It's not tagged that way, but we'll have to produce it, obviously, for a lawsuit. Yeah. When you think about that lawsuit, Julia's filed it. She's filed a class action lawsuit. There's a lot of ways that could go. you 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? I think it's actually quite clear.

19:46I think 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's the feature. 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.

20:25And the very heavily watched lawsuit. And 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, 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 creator program, which as far as I know is still the only platform with an open rev share that's out there. So I don't think the legal standard is the right standard to be looking at.

20:59I'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 think that creators, 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.

21:18Nilay Patel:We need to take a quick break. We'll be right back.

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26:11Nilay Patel:We're back with Superhuman CEO Shashir Mahotra. I have a lot of thoughts about YouTube. I'm going to ask you at 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 the policy 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 particularly AI today. Sure. I just want to stay on this one more turn. You're saying impersonation. 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.

26:48Nilay Patel:And so here you did have a commercial purpose. 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 than straightforward impersonation. It is the use of likeness for commercial purposes. And I'm just – you're saying without merit, and I haven't seen you address that specifically anywhere. You know, I think 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.

27:31what every LLM on the planet is doing and so on, and didn't come close to using name and likeness in any way that was beyond attributing the source.

27:43Nilay Patel:I mean, the thing I would say to you, and you've already said this feature is bad, so I won't hammer you on this too much, is I'm reading the edit that was generated with my name on it, which is just bad. Yeah, I saw your screenshot. 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 to a reporter. By the way, you pinned the reason why, right? I mean, the idea that you can uncover your editing style from the end work, I just think it's not possible.

28:19I mean, 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. And so you don't have an annotated list of whose names are used in the feature,

28:44Nilay Patel:but you have logs of everybody who used the feature, presuming those logs have the names in it, and you presume you'll be able to provide that if you get to... I'm sure we'll be asked. 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 they respond to the New York Times lawsuit, says, this never happened until you prompted us specifically to do the things you said are illegal.

29:16Nilay Patel:And here you have the same out. You could say, actually, we hadn't – until you asked us, we never generated your name. Has that come up? There's 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 question as harshly as I'm asking it is I don't think the defense is whether or not people use the product or whether or not the name has ever showed up. I think those are just sort of like clear cut, like binary on or off.

29:46Nilay Patel:Your name never showed up. You can't sue us. You're saying the defense is, hey, that's not how attribution should work. And you used to be the chief product officer at YouTube. And YouTube is defined by creator attribution scandals. Like 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 like the essence of the YouTube creator ecosystem. You know how YouTube reacted to this feature when we wrote the story?

30:20Nilay Patel: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? You know, 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. 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.

30:55And they're great tools for creators. My team built the Content ID tool with the same idea. If Marquez Brownlee, if somebody does that to him and they copy his videos and put them up, then you can use that tool. And he can not only go claim them, he can go make money on them. And that is a tool we built for YouTube. And I think it's been incredibly popular. And we took what looked like a scandal and went well beyond it. To be super clear, it's not what the law requires.

31:21Nilay Patel:No, I understand some of the 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 sort of defined, and in many ways the products are built around issues of attribution and payment and monetization and where the views flow and where the money flows.

31:56Nilay Patel:And 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. The music is everywhere on YouTube, and 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. And 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. And I'm just wondering if you see the distinction.

32:26You just said it. What YouTube did is said when it happens, we're going to help you find it, but you're not preventing someone from doing it. It's a very different standard.

32:36Nilay Patel:But you're making sure that people get paid. You're making sure after. To be clear, the idea of copyright is very different than a name and likeness claim. If I built a video that said, hey, I really like Marquez Brownlee, and here's what I think he would say, let me tell some jokes about Millet, it's a very different standard. The standard for YouTube was about copyright. And that's a set of regulations that are covered by a totally different part of the law. And 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.

33:15But the principle of what is similar in that in both cases, there's a law. The law does not really meet the creator bar. I think the goal of the community, the goal of a product 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. Yeah.

33:50Nilay Patel:Look, I used to be a copyright lawyer. I'm not saying I was the world's best copyright lawyer. In fact, I will happily admit that I was not the world's most 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. And 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, right?

34:24Nilay Patel:Like this is a thing that is being suggested because copyright law is more or less the dominant regulatory framework that exists on the internet. And I look at the big social platforms like YouTube, like Instagram, like 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. And then our likenesses are not one of them. Our names and faces are not one of them. And 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.

35:01Nilay Patel:And you are the one who's experienced it the most loudly recently. And I'm kind of 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. And we'll see if the laws find a ground on that. I do think it's a catch-22 as a creator. I mean, the copyright law has been around for hundreds of years now and in its various forms. The way music composition was licensed started with actually Mozart and Bach and has grown since then. And almost every country in the world has reached a very similar standard.

35:38I think there's a very thin line between taking publicly available work and being able to refer to it and copying it. And I think the idea that defining all references to work as being uses of names and likenesses, it would break your business. You wouldn't be able to refer to me. How did you get on a show last week and talk about me?

36:03Nilay Patel:I mean, just to be clear, I don't want to be in the inside baseball of making a podcast. We made you sign an appearance release. No, no, no. 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 able. I talked about you before I came on the show, but in order to run – 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.

36:32No, 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 using their name and likeness, then it's a very hard line to draw.

36:53Nilay Patel:I just want to be – 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 ever would 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 existed that would lead you to this outcome with my name attached to it. I'll repeat it. The future was here's a suggestion generated by a specific work from a specific person. Everything is clearly indicated that it's a suggestion generated.

37:33I'm sorry.

37:33Nilay Patel:You think in my role as editor-in-chief of The Verge and co-host of The Verge Cast, I emphasize the importance of crafting compelling headlines that convey urgency? I already told you it's a bad feature. You're not, that's not what you're questioning. I'm just saying, 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 ask to— No, it doesn't. It just says, this suggestion is inspired by Nealai 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.

38:08Nilay Patel:The Vergecast is not a show about editing headlines about smartwatches. I understand. First of all. 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 it 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 of can the internet, when you publish work, can humans and AI use it to generate other suggestions, other impressions?

38:51They can, and you would like for them to attribute it.

38:55Nilay Patel:But it's not work that that person made. Like 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 is I'm not sure why this is an attribution. Like if I'm like I talked to Shashir and I think here's what he would say, that's very different than saying like I read all of his work and I've asked, you know, whatever quick version of Claude or G-A-T-B-T to just make something up and I'm going to put his name on it.

39:29Nilay Patel:Like there's something meaningfully different there and it doesn't seem like you're willing to concede that. No, I'm not. I think it's fairly clear that generating a suggestion based on somebody else's work, just use a simple test of a human doing it. If you did that 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 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.

40:00Nilay Patel:That idea is clearly mine. The feature is very clearly stated that this is a suggestion developed by this feature based off this work. Let me ask you a different question. And I'm curious about this across the whole sweep, right, 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. I think this is tough. AI is polling behind ICE and only slightly above the Democratic Party. This is a tough spot to be in. It's a negative 20 perception. I think the reason for that is because it's so extractive and the value isn't there.

40:40And I would compare this to YouTube, which a lot of people thought was pretty extractive, right?

40:44Nilay Patel: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. And 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 in school, like in studying copyright law during the case. And the vast majority of people were like, YouTube is really useful. We love it. And these big Hollywood companies suck. Napster, the public was not on the side of the record labels. They were not on the side of large oil. They were on the side of file sharing because the utility was so high regardless of the economic or social costs.

41:22Nilay Patel: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. You can tell people all that there's a trial right now about whether social media platforms are damaging to teens' health, whether they're effectively designed products that hurt kids. The trial is ongoing as we speak. The jury is empaneled 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 buy trucks.

41:50Nilay Patel:That's what we're going to do. AI isn't – that isn't there. It is only perceived as extractive. It is not – 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 right now. I think great consumer products that provide a lot of value overcome their social costs. I think there's the number one. I think AI has a lot of challenges ahead of it. There's lots of opportunity.

42:22It does meet the 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 it's challenging people's sense of future of their humanity. It's their ability to work. Those are really the challenges there. I think the line we're talking about here, I don't think that's actually what you're reading into that poll.

42:54Nilay Patel:What would you read into the poll where AI polls below ice? You think people are just scared of their jobs? I think so. 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 in 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 most worried about and how it could replace their jobs. But by the way, 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.

43:23I think actually one of the reasons why I think 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 does it pull so low, it's because the copywriter feels like maybe I'm not going to need it anymore. It's the salesperson 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 that has something to do with name and likeness, I think, is a pretty big stretch.

43:56Nilay Patel:Well, I mean, again, 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, an ad agency, I know a lot of copywriters at ad 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. People who write Tumblr are saying now OpenAI is going to make a porny fanfic for people. That was our job. Why didn't you pay us? I think you're absolutely right.

44:29Creators are facing a very hard road right now. And I don't think it's caused just by this feature or just by the latest events of AI. They're facing a hard future for a lot of different reasons. I think the poll you're referring to of the broad population, 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 I think the entire industry has done a really bad job of helping people understand why technology like this can help them and not prevent their job from being taken away.

45:19And most people just aren't creators. I'm not objecting to what you're saying about creators. Just saying most people aren't stressed about that because that's not their job. That's not what they're individually afraid of.

45:29Nilay Patel:No, I understand what you're saying. I'm just pointing out that almost every major technological shift has been extracted in some way. Google copied all the books in the world with that 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. And 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. And it was obvious that Google was going to win that case.

46:00Nilay Patel: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 deep fake of my face and use it to sell headphones in Alibaba. Hey, 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. Like 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 apparent.

46:38I'll tell you, I think in some ways I like the YouTube analogy. I think it's a good way 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. I think there are other products that are very close to this line. I think our core strategy is about building a platform that you can choose to participate in or not and 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.

47:32Actually, most of the internet wouldn't exist. And so the idea that it got litigated that way, I think it's a win for everybody. I think 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.

47:45Nilay Patel:What happens if there's a bunch of copyright cases against the AI companies? I feel like I should disclose that our company has Google over ad tech. It has nothing to do with AI or copyright. I feel like I need to disclose it because I disclose everything all the time. And I think Vox Media sued Cohere, one of the AI labs, over copyright infringement. The New York Times has sued OpenAI. There's a million of these copyright cases. There's more every day. One of them could go the other way, right? And this industry could faceplant. What do you think happens if that goes – what do you think happens if one of the big AI labs loses a copyright case?

48:16Are you asking me as someone watching the industry or are you asking me in my superhuman role?

48:21Nilay Patel:Both. I think – My superhuman role is straightforward. I mean the models – 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, both directions. And I have real empathy for both sides. I mean, copyright law is, like you said, it's some of the work that has allowed the internet to work. And not everybody is happy with how the law draws a line. And I think you're right that YouTube tested that line in a new way, Viacom case so on.

49:01I think what OpenAI and Claw and Gemini are doing are going to test it in a new way. And I think, I hope they find a good line for it. I don't think that's where we're going to be. I mean, it's not, we're not going to be the ones in the middle of those lawsuits or those figuring out where that line is.

49:19Nilay Patel:We need to take another quick break. We'll be back in just a minute.

49:45Nilay Patel:We'll see you next time.

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53:19Nilay Patel:We're back with Superhuman CEO Shashir Mahotra. 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. But I don't mean to say it doesn't matter to us as our own entity. It matters to me as a citizen. I mean, I think it's really important. But I would also remember, like, for us, the primary agents people are trying to build on Superhuman have nothing to do with this. I mean, the expert case is one case.

53:53What 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 6 p.m., please make sure that I'm actually free then. Like I said, this is not a common part of our business.

54:19Nilay Patel:No, I'm not saying the expert review part. I'm saying, what you're describing, take all of my sales literature, take my calendar. That gets loaded into context for a model that you call. Yeah, 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? I mean, 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. I think that's the business model they should have. So my personal view is 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 from the New York Times.

55:03And 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. I'd say I just won't use it.

55:12Nilay Patel:Right, but a lot of these – all these cases are different. So I'm going to generalize here, and you can attack me for generalizing. 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, right? Like Suno can make a Beyonce song. That's copyright infringement on output. The other set of cases where I think it's much more important is on input, is on training, right? And saying you actually ingested all my material without permission. That's also copyright infringement. And if that goes the wrong way for the model companies, their cost structures change in retrospect.

55:45Nilay Patel:You can't build the systems you're describing because the model itself is infringing. That's what I was responding to. So an output, a copyright law covers it. And I think if you actually produce something that could be mistaken for the work of another person, then you can file a claim, you can get it taken down, and then you can get, 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. 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.

56:23I would split the model. If it really went that way, and I would say, fine, you don't want your content there. I will build a version of the model that is just for time subscribers and charge them. Your particular question was, will that cost get passed along to the other users of the alums? I mean, that is what's happening right now. I mean, they are paying that content. It is being passed to us. You know, does it matter to us? I mean, frankly speaking, the pace of innovation in that category is so high that the profits being generated there are so high that, no, it hasn't mattered to the upstream users, to us, to ChatGPT users, Gemini users, so on.

57:00It hasn't stopped their growth at all. Will it someday? Maybe. I don't know. But my point was more in this world of like output copyright is fairly clear. Law covers it pretty well. Input copyright is not that clear. You know, and it's not clear for good reason, right? If you're a human and you read a book and then you learn something and you talk about that thing, like, you know, 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.

57:37We'll have to deal with it. Everybody will.

57:39Nilay Patel:The other dynamic here, by the way, most humans cannot infinitely scale to create trillions of dollars of enterprise value by reading one book. That's the difference, right? To get that value at that scale, usually lots of people have to buy copies of the book. And the economics spread out, right? I mean, the scale is the difference. I think it's, I understand that is a very fair argument that this is not the same as a human reading the book. And 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.

58:17And I think the idea that that's going to get into the exactly right spot and you're going to get pennies for every query coming through Gemini, that's certainly one path. I think 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 connection 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. And I think YouTube offered a great way to do that.

58:53I think what we're doing at Superhuman should offer a great way to do that as well.

58:57Nilay Patel:Let me ask you about that specifically. I wasn't 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 carousels. So I'm just going to read you the caption. This is from the superhuman suite at South by Southwest. 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.

59:28Nilay Patel:And in the AI era, taste and judgment are more valuable than ever. Valuable on what metric? Is it dollars? It's valuable in every metric. I mean, I think it's - But it's specifically dollars. Dollars are what I pay my mortgage in. Is it dollars? 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. 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?

1:00:00So 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. So, guys, that's what the banner's about. I think your question, I think, is a very good question.

1:00:35Nilay Patel:Wait, that's how the banner says taste and judgment are more valuable than ever. And 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 and you're a person who's 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're addressing, we have 40 million users who use our products. The vast majority of them work in professional industries.

1:01:13They'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. I do think we have a proposition for you, Nile, as well, which is that you can now become one of those assistants to all those people. And many of them have no idea that they could use your help. But if you can build that relationship with them like Grammarly does, and people personify Grammarly all the time as my high school English teacher sitting next to me everywhere I work, that makes me better.

1:01:59If I can have my high school English teacher with me everywhere I work, it makes me better. It makes my trust and judgment shine through. I would like your agent, for the people that matter, 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've got 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.

1:02:30You should be able to construct it the way you want. You should control it. And you should be able to make money on it. And you should – yeah.

1:02:37Nilay Patel:Wait, hold on. I'm just going to – 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. Right? I didn't make that statement. 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 mean, I'm not here to tell you how to answer every question for what's changed in the creator economy.

1:03:15I think it's one way to look at it is that the path of being a creator has become harder. I think there's other ways that, you know, I assume this is going to end up on YouTube and Spotify and so on. There's paths to becoming a creator that become easier. And I think there were folks that when YouTube came out, they told us all the same things. And they said, we don't understand. Our business model is screwed over there. And so why should we work on YouTube? And 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.

1:03:49And I think you saw that opportunity and you expanded what you could do. I think 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, I think that's one way to look at it. And I think 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.

1:04:23And I think that's the bright future. I'm not really trying to say you have to or you don't have to. I think 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, I think there's an opportunity. I had one creator tell me that their traffic in just the last year from Google is down 50%. They said that AI overviews and so on, traffic is down 50%. They sell books. And my reaction to them was, that really sucks. I mean, I understand why that really sucks.

1:04:59I would also tell you, 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. 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. And I think platforms like ours are going to give that opportunity to people who choose to take it.

1:05:28Nilay Patel: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, the AI companies, their sort of relentless expansion into every category, and then what you might call the cesspocalypse. 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 Vibecode something that looks like Grammarly and run it instead of paying? You're like$160 a year? Like this is the thing that's coming for the software industry writ large. Do you feel that same pressure?

1:06:01I personally think it's a little overstated. I'll give you my view of it. I think that there's 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. I'll just focus on CRM. So 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, actually, first they say, why would anybody have a CRM?

1:06:42And then it's if they do need a CRM, why would they pay for Salesforce? Well, maybe I'll answer both questions. So why pay for a CRM? And, you know, my view of it is that, you know, 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. I think when I have 1 ,000 agents selling on my behalf, I'm going to need a way for them to coordinate with each other.

1:07:18It 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 reason is it becomes, I think all the powers of network effects are going to become much higher. And 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 mean, I'm sure they'll try. I mean, my hope is by that point, we are the platform for all the best agents that work right where you work. And you'd have to go replicate all of them.

1:07:48And I'm sure there will be people that will, but I think most people won't. And I think that's an important bet for how the software industry moves on. I think the need for software is only going to increase, and I think the importance of network effects will only increase.

1:08:04Nilay Patel:You don't think that OpenAI or Anthropic or any of 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 – I mean, they're just buying our tokens anyway. We can just kill them pretty easily. I mean, I think 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. I think 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.

1:08:35That's always true.

1:08:36Nilay Patel: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. Like 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. And at the end of it all, the creators all have to pivot to selling something.

1:09:10Nilay Patel:The Paul brothers have to sell you bottled water. Mr. Beast has to sell you energy bars. like we are we 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 like the history of business most businesses pivot from atoms to bits right 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.

1:09:48Nilay Patel:This whole conversation has been about that pressure. And 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, is that all of these platforms at the end are becoming about someone trying to sell you something else. And AI is just accelerating that. I'm just wondering where you think the endpoint is. Actually, I think it's an interesting characterization. I mean, I think there are multiple business models out there. What you described as bits to Adams, I think is one way to look at it.

1:10:23I mean, I think the reason why YouTube creators end up with those other opportunities is not because, I mean, I'm sure some of them feel like the ad revenue from YouTube is not enough. It's because there's an opportunity. 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. I think it's much more advertising versus subscriptions versus purchases. And I don't think the spread on that is really about the bit or atom piece. It's about the connection piece.

1:10:56There's a set of platforms that are built off eyeballs. I mean, what I built at YouTube was primarily built off eyeballs. And there is, you know, over all of history, the amount of advertising spend has always been some percentage GDP. It's hovered between two and four percent of GDP forever. And that gets divided up amongst all these eyeballs. And that is one business model. And yes, the number of creators fighting for that has dramatically fragmented over the last couple decades in every platform. And so what can come from that is smaller. There's also the ability to sell products. And as old as time has been the ability to sell products.

1:11:33And in the middle is the ability to build connection. And I think those products tend to do a lot of work with subscriptions. I mean, it's interesting when we think about some of my favorite creators, you know, many of them subscribe to the thousand fans theory that if you can get a thousand people to pay you a hundred bucks a year, you all of a sudden have a hundred thousand dollar business. And I think that there's a whole class of people for whom they've decided if I can, I can either go somewhere where 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.

1:12:08Or in the middle is 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. And if I can do that, then I can build a real business out of it. And there's some fantastic creators who have done a really good job of that. Many of the ones I'm sure you know. I think what I'd like to do, what we're trying to do with Superhuman and our agent platform, is enable people to build that level of connection. I mean, a lot of them are doing newsletters. I mean, it's very meaningful to say, I got a newsletter.

1:12:40It's 100 bucks a year. Here's how you can do it. A thousand people get through to 100 grand. 10 ,000 people get through to a million bucks a year. It 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 a thousand people to say that's worth a hundred bucks a year to me, I think you'll be able to.

1:13:10Nilay Patel:And I think, wait, I'm just going to ask you this as directly as I can. Do you think that feature will be good? I think it'll be as good as the work that the creator puts into it. And it's a little bit like, you know, are all newsletters good? No, most newsletters suck. There's no, there's no guarantee that the newsletter platform can make them good. You know, is every YouTube video good? No, they're, they're mostly, they're quite terrible. But does it allow? But do you think you can get an – like, 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.

1:13:46Nilay Patel:You're dependent on the capabilities of the models themselves. So I'm asking you kind of in 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 mean, I would say that I think 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. I think 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.

1:14:20Nilay Patel:What does that tool look like? How does build a good tool that lets me edit look like? I think the start of it is actually what you said earlier. You have to write down that viewpoint of what is your editing like. No, but literally describe the interface that your tool provides me to do that. Oh, the main part of the interface is a prompt box and what we call triggers. So 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. So 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.

1:14:57And when you see this, do this. When you see it, like 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 would you 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? So you'd probably sit down with them and you'd write some things down. And then the second thing you do is you'd watch them do it and then you correct them.

1:15:29And so 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. We call them accept to look rates. You're going to come back and you're going to look at it and say, yeah, that clearly didn't work. Maybe it might be it didn't work for the user. They ignored my suggestions. Maybe it didn't work for what you think was good work.

1:15:56You looked at the output and said that wasn't particularly good work. And you're going to train it. And I think the idea of being able to train a custom agent for each person, for each product, I think 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.

1:16:25Nilay Patel:Do you have an example of one of these that you think works well today? I mean, I think Grammarly is the most obvious one. Most of the other really good ones. Grammarly is like grammar, right? It's rules-based in a very specific way. 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.

1:17:03Grammar 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 when people pay for Grammarly. That's the type of suggestions they get from us. And they seem to like them. There's 40 million people who 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. One launched a couple 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, how do I turn it into a slide deck?

1:17:38We've seen a lot of them being built inside of companies. I think the sales example I gave is a very common one. 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 even great.

1:18:00Nilay Patel:Those are enterprise uses. And I actually understand the sales use case a lot. Like, you need the salespeople all to say the same thing all the time. I understand they don't do that all the time. We have salespeople. Can a creative one work? I'm asking, I don't think taste is rules-based. But actually, I'm confident that a coder of producers are in the background here just in a puddle because part of their job every week is to try to write like me. And they get a lot of feedback from me directly on I would, this is, I'm literally editing the document so I can read the intros and outros and I'm changing the questions.

1:18:34And it's really hard, even when it's just three people

1:18:37Nilay Patel:who have spent years working together to try to get to an output that works. And they're really good. Yeah, I think it's totally fair that it's not. And my guess is the types of experts that will first prevail here won't be the ones you're describing. That make something creative, sound unique, make it sound better is probably not the ones that will work first. But I do think there's a set of experts and creators that will work great. I mean, maybe I'll pick the ones that are right next to Grammarly. I think there's a set of teachers for whom this is going to work really good. They're going to say, hey, in addition to making sure your grammar is good, it looks like you're writing something about history.

1:19:12I can probably help you cover history more clearly. It's not quite as clear as grammar facts, but it's pretty close. Like this is what happened in this period. You should know these different elements of it. I think teachers will be a great example of that. I think that as you work up to the more and more creative side of it, we all know that what our alum is really good at, they're really good at averaging what everybody says. So can they do something really unique like you do? You know, probably not. Can they take some part of your suggestion and turn it into enough usefulness that you can get a thousand people to pay a hundred bucks a month?

1:19:50I bet you can come up with something. Because the bar isn't, just repeat the bar. 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 human. You just need to create enough benefit that a thousand people pay you a hundred 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.

1:20:18Nilay Patel:I'm going to have to think about that quite a lot. Shashir, we are at time. Thank you so much for coming on, for answering the questions, for being game to answer the questions. I appreciate it. 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. Yeah, we're very busy building out Superhuman Go. I think we have a big set of launches coming in the next couple months. So keep an eye out for that. All right. Shashir, thank you so much for being on Decoder. All right. Thank you.

1:20:48Nilay Patel:I'd like to thank Shashir Mahatra for taking the time to join Decoder. And thank you for listening. I hope you enjoyed it. As I said, I'm dying for your feedback on this episode. If you'd like to let us know what you thought or really anything else at all, drop us a line. You can email us at decoder at theverge.com. We really do read all the emails. Or you can hit me up directly on Threads or Blue Sky. You can also find us on YouTube where we have full episodes. We're at DecoderPod. We also have a TikTok and Instagram. We're also at DecoderPod. They're a lot of fun. If you like Decoder, please share it with your friends and subscribe wherever you're podcast.

1:21:14Nilay Patel:Decoder is a production of The Verge and part of the Vox Community Podcast Network. The show is produced by Kate Cox and Nick Stat. This episode was edited by Xander Adams. Our editorial director is Kevin McShane. The Decoder music is by Breakmaster Cylinder. We'll see you next time.

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