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 you.
How many times did you use my name?
You know, I can't get into that because it's a legal case. I really can't get into details of those types of things.
Did you track how many times you were using people's names?
I mean, we certainly logged all the different interactions. Yes.
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 I would ever say anything like this. Like if I'm like, I talked to Shashir 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, you know, whatever quick version of Claude or ChatGPT to just make something up and I'm going to put his name on it. Like there's something meaningfully different there and it doesn't seem like you're willing to concede that.
Hello and welcome to Decoder. I'm Nilay Patel, editor-in-chief of The Verge, and Decoder is my show about big ideas and other problems. Today I'm talking with Shashir Mahotra, the CEO of Superhuman. That's the company formerly known as Grammarly, which is still its flagship product. Shashir 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 broadly about AI and what it's doing to software platforms and creativity. Then things took a turn. There's a feature in Grammarly called Expert Review which allows people to get AI writing suggestions from quote-unquote experts, and reporters at The Verge and other outlets discovered that those experts included us, included me. No one had ever asked us permission to use our names in this way and a lot of reporters and other authors were outraged by this. The talented investigative journalist Julia Angwin was so upset she filed a class action lawsuit. Superhuman responded to all this controversy by first offering up an email-based opt-out and then killing the feature entirely. Shashir apologized and you'll hear him apologize again in this conversation. We'll put links to all this backstory in the show notes if you really want to dive in. Throughout all of this, the Decoder team and I kept wondering if Shashir was still going to show up and do an interview because my questions about decision-making and AI and platforms suddenly seemed a lot harder than before. To his credit, he showed up and he stuck it out for the entire conversation, which got tense at times. It's clear that Shashir and I disagree about how extractive AI feels for people and the value that these platforms can actually provide. I'm not going to stretch this out any longer. I'm dying for you to listen to this and I'm dying for your feedback. We really do read all the emails. Here's Shashir Mahotra, CEO of Superhuman. Here we go. Shashir Mahotra, you're the CEO of Superhuman. Welcome to Decoder.
Uh, thanks for having me.
Uh, 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, you own Coda, you own a bunch of companies. Just quickly describe the structure of Superhuman and all your products.
Oh yeah, sure. So 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. I did that because the scope of what we do 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, a very popular email client called Mail, and we launched a new product called Superhuman Go. Go is the platform that brings you a network of proactive and personal AI assistants 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, and so on can all help work with you right where you work. And 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. So 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.
So 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, right? 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, right? They're going to put AI right next to the insertion point, right next to your cursor. What's the big differentiation for you?
Actually, 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. So the way to think about Grammarly is it's your assistant that lives everywhere. So you might be in a web app, so 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, could be every mobile application. We have for every one of those applications we 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. So as you jump from tool to tool, yeah, there's 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. That's what they use it 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, I mean, becoming more intelligent is certainly part of it. I mean, I think for many people it's just that one familiar experience that really feels like that virtual human working right next to you.
So is it consistency of experience or is it better and more useful results?
I mean, it's both. So I mean, and if we think about Grammarly, I think Grammarly is both the ever-present, is very important, and very high-quality grammar results. As we split the product into parts and 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 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, which is a question I ask everybody but I think the stakes are a little bit higher here, is about decisions. How do you make decisions? What's your framework?
Yeah, I mean, I think we have a lot of different thoughts on how to make good decisions. I wrote a piece a long time ago called 'IEN Questions' 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 Dorian 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, you know, when I worked at YouTube or Google or so on.
All right, 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. You used my name among many other names. Casey Newton, Julia Angwin down the line. bell hooks was in there, which is hilarious in its way. You did not have our permission to use our names to do this. You had little check marks next to her name that indicated that 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.
Yeah. So let's, I expected we'd talk a bit about this. So let's, lots of different thoughts on it. You know, first off, I'd say, you know, I understand and respect how challenging a world it is for experts and idea generators these days. You know, I've made a long career out of being a partner to folks like you, to folks like the ones you mentioned. It deeply pained me to feel that we underdelivered for them and I'd really like to apologize for that. That was not our intention. On the specific feature you're talking about, you know, I'm sure we'll talk more about it, but just to give the high-level view, my view of it is 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. You know, 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. That wasn't the way we wanted to go after it. And 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?
So 1,500 people. How many people decided to launch this feature?
Oh, it was a small team. There's probably a PM and a couple engineers.
Okay. Inside your decision-making process, where you described a way of making sure you solicited the right feedback and didn't have groupthink, it never came up that using people's names without permission would make them mad.
You know, maybe we should step back and talk about what inspired this team and what they were trying to do and what fell short. So let's start with what they were trying to do. So you know, they were heavily influenced by both what we view users to want and what we want experts to want. So start with users. You know, we think of Grammarly. A lot of people describe us as, they talk about us as the last mile of AI. They talk about us like 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 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.' So that's the core ethos of what we're building is taking Grammarly, 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. And they try to do that today with LLMs. They go to Chat and Claude and they say, 'What would Nilay think about my writing?' and so on. That was the inspiration for what the user was trying to do. I think on the other side was what the experts are trying to do. And I think as we formed our strategy here, turning Grammarly into a platform, actually 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. You know, your path to getting to your fans is you 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. You know, what happens when they put my book down? Can I still be with them and help them along the way?' And you know, it feels like the world shifted against them. You know, AI overviews are stealing a bunch of their traffic and so on. And boy, this seems like a much better way to go after it. So that was the inspiration behind it. The team, you know, the feature didn't deliver and I think 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. I think the reason, actually the fundamental reason, is something you said last week, that it's really hard to distill what you would do as an editor based off the outcome of your published work. I just think it's like really hard for AI to do that and we need your engagement for that to be a good feature. So I think they launched something that wasn't particularly good. You know, I think 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?
So I think it's really important to think about attribution and think about impersonation and so on. I think that, you know, as an expert you have a trade you make on the internet. And I think the idea 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. So I think the idea of when somebody uses your content, should they attribute you? Of course. And to attribute you, you have to use your name. I think there's a different line which is should people be able to impersonate you? And I think that is a very different standard. And you know, we saw the lawsuit, you know, respectfully. We believe the claims are without merit. I think the idea that the feature was impersonation is quite a big stretch. The feature was very much, every mention was very clearly this is inspired not only by this person, 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. Should you, if your work is used, should you be attributed? Yes, I think you should. I think that would be the nice contract. It doesn't always happen. I mean, I think that there's many products that will use your work and not attribute. We thought it was very important to attribute. But 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 you and they should link back to you. And I think that's a human contract we have of how the internet is supposed to work. And I think it's a really important one is that we should make sure, and I think it should be the standard you're looking for from LLMs too. I think 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 don't really want to, 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. And you should choose your business model. And 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, wrote the story about it. It 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 you didn't want to be in the feature, 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? Why was the first an email opt-out?
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.' And we announced we're taking it down well before there was a lawsuit. The reason we took it down is it's off strategy. It's not what we want to do. It'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 you know, the feature wasn't good. We took it down.
Tell me, you said it's off strategy for you. The feature obviously shipped. What made it on strategy at the time it shipped?
You know, I think at the time they 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 in 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, creators, I would lean into it. I think it's a big opportunity.
Why would they lean into it if the value for that is zero dollars?
No, I mean, I think it should be our job to make sure the value is not $0. We want you to...
So 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.
Yeah. 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?
Yeah. So we're building this business model now. The way our store currently has a payment model for this that has a 70/30 rev split that's very similar to how a lot of other products do. So 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're very different features and the team that built Expert Review, you know, they were trying to address this need, they just missed.
How many times did you use my name?
You know, I can't get into that because it's a legal case. I really can't get into details of those types of things. But you know, 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 thin air? Was it randomly hallucinating names?
It came right from the popular LLM. 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.' You know, by the way, I think 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?
I mean, we certainly logged all the different interactions. Yes.
So you do have a record of like how many times my name showed up or Casey Newton's name showed up or anything?
It's not tagged that way. But we'll have to produce it obviously for a lawsuit.
Yeah. When you think about that lawsuit, you know, Julia has filed it. She's filed a class action lawsuit. There's a lot of ways that could go. You've said the claims are without merit. What did your lawyers say to convince you that the claim is without merit?
What did the lawyers say? I mean, I think it's actually quite clear. I think the layman's test is 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. I don't, 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 can step back for a second and say, you know, 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 and the very heavily watched lawsuit and 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 creator program, which as far as I know is still the only platform with an open revshare that's out there. So 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 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.
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 the policy of 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 particularly AI today.
I just want to stay on this for 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. 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. 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, what 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.
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. Like, 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...
Yeah. And 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. I mean, it's very, 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, but you have logs of everybody who used the feature. Presumably 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. 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, you know, 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.' 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 names ever showed up. I think those are just sort of like 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. 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. That is 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?
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 because I think video...
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 and they're great tools for creators. My team built the Content ID tool with the same idea. If Marques 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.
