The Exchanges

Q You mentioned you always knew that you could raise more money. I love that. What was the business model? Venture capital. Harry's like, thank God I still have a job. Um, but when you think about the fundraisings that you did, what was the hardest? A series A. Talk to me about that.

A So, so we, we started as a research project at Carnegie Mellon University, and the belief was, oh, this is, it's these two academics. Luis was a professor, and I was his PhD student. It's these two academics, and, and, and they're gonna build something that's not gonna make any money, and they're gonna sell to Google. Okay, and then That, that was kind of the belief. And by the way, that, that belief lasted until we actually made money. So for like five years, the first five years ago, oh yeah, they're, they're, you know, these, like these, these two researchers, and they're gonna build this, this thing, and, uh, they're eventually gonna sell, you know, they're not gonna become a public company or anything. And that was one reason. And then I think it was just, this was, um, we, We had a, we were raised on a prototype, and it was a website.

AI assessment note: “we started as a research project... the belief was, oh, this is, it's these two academics”

Q about the not having PMs, and actually, if all the biggest companies have them, maybe there's something to it. And it makes me think of this, like, conventional rules are conventional for a reason sometimes. What conventional rules do you find are conventional for a reason? One. And then what one conventional rule do you find, what the fuck? That, that's just the way it's been, but it's not right.

A Well, first of all, I would say you should always, not always, but every now and then, especially when there's a big technology shift like now, you should question all of these assumptions, right? Like, uh, you know, how you build companies. I think it, it just, we're in the middle of this massive transformation. You can build companies with probably 10 times fewer, uh, employees. Um, so, so that, that, that convention is, is, is, uh, you know, uh, completely You know, that you need to hire a lot of people. Um, that's one thing. Uh, I would say, you know, early on there was like uh,, ah, this is, this is going back. It's not a, not a great answer, but, um, there was like this, this belief that you can run a completely flat organization, right? No, no managers. Um, no hierarchies, no levels. And. I think that's not really possible. Uh, at a certain scale, you need to have managers or layers, or you need to have some sort of hierarchy. You need to have some sort of, um, career progression and stuff like that. I think that You know, the, the oldest organization in the world, the Catholic church that is still around, it's very hierarchical. And, and I think there's probably some, some reason for it. Yeah.

AI assessment note: “at a certain scale, you need to have managers or layers”

Q fundamentally, they don't want to work, and AI is as good as they are at sales, at marketing, whether you're an SDR, whether you're a social media content creator for memes or GIFs or whatever it is. Like, actually, and so in 12 months, We're going to see huge, huge unemployment in this kind of lower level tech employee, and it's, it's going to happen. Do you think that's true?

A I'm not sure. So, so here's another thing. Um, so the, the general consensus is that these AI tools are really good for senior software engineers or staff level software engineers, right? So because they, they, um, you know, they have been trained and now they can use AI and they become much more productive. They're now a 10 X engineer. And, and then, uh, they can, you know, AI, the, the, the general consensus is that AI can do the, the job of an entry level engineer or an intern or something like that. Therefore, let's stop hiring entry level engineers and only hire senior engineers. But I think that's a mistake. And, and we're actually not doing that at Duolingo. We still hire from universities. And one of the reasons is That we believe that people that grow up with these tools and, you know, start using these tools early will become much better at using them. Um, so in a way, yes, they're, they're, uh.

AI assessment note: “I think that's a mistake. And, and we're actually not doing that at Duolingo.”

Q How do you think then about Synthesia, about 11 Labs, about some incredible lovable in Sweden being built from Europe?

A That is great. I think for, and you know, uh, they, they, They should deserve all of our support. And you know, the, the, the, the, the, the sad part is also, I think in, You know, in Silicon Valley is like being a tech founder is, is, is really, you know, you're, you're mostly a good person. Of course, there's also, uh, it's, it's, it's, it's aspiring, right? So, so people want to be that. I think a lot in, a lot of people in, in Europe, you, you just like, you're kind of like, why are you doing this? Like, why, why, you know, like, or, or, or they, they, they look at it as like, oh yeah, you know, they're just doing it for the money or, uh, there's this suspicion. Uh, almost of, of, uh, you, you, you can't be too successful or you can't be, you shouldn't be too ambitious. And, and I think that, that, that is very detrimental to the, the European startup ecosystem.

AI assessment note: “That is great. I think for, and you know, uh, they, they, They should deserve all of our support.”

Q You mentioned you always knew that you could raise more money. I love that. What was the business model? Venture capital. Harry's like, thank God I still have a job. Um, but when you think about the fundraisings that you did, what was the hardest? A series A. Talk to me about that.

A So, so we, we started as a research project at Carnegie Mellon University, and the belief was, oh, this is, it's these two academics. Luis was a professor, and I was his PhD student. It's these two academics, and, and, and they're gonna build something that's not gonna make any money, and they're gonna sell to Google. Okay, and then That, that was kind of the belief. And by the way, that, that belief lasted until we actually made money. So for like five years, the first five years ago, oh yeah, they're, they're, you know, these, like these, these two researchers, and they're gonna build this, this thing, and, uh, they're eventually gonna sell, you know, they're not gonna become a public company or anything. And that was one reason. And then I think it was just, this was, um, we, We had a, we were raised on a prototype, and it was a website.

AI assessment note: “That was one reason. And then I think it was just”

Q Final one. On public market caps and stuff, I believe you'll probably, I don't know ownership structures, which I probably should do, I believe you'll probably be a billionaire, technically. Um, so well done. Um, my question to you is, do you think about money, and how does, Money and happiness correlate or not correlate for you?

A Yeah, and that's an entire half an hour conversation or so. Um, you know, I, I, I've also spent a lot of time thinking about this question, and, and the weird thing is that I wish I hadn't. You know, like, I feel like it's not a productive, uh, uh, It's not productive. It's like, it's like, so I, I thought a lot about this, like, you know, am I happier now than I was when I was a grad student? And, and is it because of, because of the money or is it because of the success or is it, um, because I know myself better and it is very hard to, um, disentangle the, the, all the different factors that, that go into happiness. I would say though, that. There, there's, there's different levels of, of, uh, of wealth. And, and they actually did this study, I think with, with, uh, post exit founders. And, and it was like, they, they asked him, you know, how much is enough? How much is enough? When, when, when does, when you, when do people switch their opinions? Like, okay, now this is enough. And It's, it's probably still subjective, but the answer they got was, do you know what the answer was?

AI assessment note: “it is very hard to, um, disentangle the, the, all the different factors”

Q Final one. On public market caps and stuff, I believe you'll probably, I don't know ownership structures, which I probably should do, I believe you'll probably be a billionaire, technically. Um, so well done. Um, my question to you is, do you think about money, and how does, Money and happiness correlate or not correlate for you?

A Yeah, and that's an entire half an hour conversation or so. Um, you know, I, I, I've also spent a lot of time thinking about this question, and, and the weird thing is that I wish I hadn't. You know, like, I feel like it's not a productive, uh, uh, It's not productive. It's like, it's like, so I, I thought a lot about this, like, you know, am I happier now than I was when I was a grad student? And, and is it because of, because of the money or is it because of the success or is it, um, because I know myself better and it is very hard to, um, disentangle the, the, all the different factors that, that go into happiness. I would say though, that. There, there's, there's different levels of, of, uh, of wealth. And, and they actually did this study, I think with, with, uh, post exit founders. And, and it was like, they, they asked him, you know, how much is enough? How much is enough? When, when, when does, when you, when do people switch their opinions? Like, okay, now this is enough. And It's, it's probably still subjective, but the answer they got was, do you know what the answer was?

AI assessment note: “it is very hard to, um, disentangle the, the, all the different factors”

Q But by achieving your mission, are you not disrupting Harvard?

A Yeah. We would be. Um, but one thing on the second thing, so we have not solved the social thing, right? Okay. This is what higher ed does. We have not solved the social thing, but on the number two of the credentials, One thing we're also very passionate about is, is the Duolingo score. I'm not sure if you, if you notice it within Duolingo, but we now give you a score, like how good you are at, at this language. And, and we want this to become the way people talk about language proficiency. So it's like, Hey, my Duolingo score is 61 in French. And then people know, okay, I guess you can have a, this kind of conversation, et cetera, et cetera. So, so we're getting into the credentials or the degree aspect of it with this score. So.

AI assessment note: “Yeah. We would be. Um, but one thing on the second thing”

Q Dude, I would love to start, though, with basically the news of the day. Um, I don't like the, you know, the whole context of, like, tell me your life story and normal podcast intros. Duolingo came out as being AI first the other day, and I really just wanted to start with what does that mean and what does that not mean so people have a clear understanding?

A Okay, so maybe taking a step back. Why did we start Duolingo? Like, what is our mission? So Duolingo's mission is to provide the best education and make it universally available. That's why Luis and I started this company. Okay. And from day one, if you think about it, if you want to build the best education, um, in the past, the best education was only available to the richest people, the kings that had, you know, the private tutors for the kids. And, and, you know, that was the way to learn most efficient way. And by the way, this is still true today. If you want to become the best tennis player, you hire a one-on-one tennis coach. Okay.

AI assessment note: “Okay, so maybe taking a step back. Why did we start Duolingo?”

Q Do you see what I mean by that? They're like, you know, people often think about like Manchester United. It is a, a global brand, for example, and I think it's drastically underpriced given the fact that you have that children in India, Nepal, Brazil, wearing a Man U shirt, and it's a five billion dollar company?

A Yeah, I, I, I don't, I don't know. I, I, I think the, the, the, there's like, Is a massive brand, Duolingo. So it's, it's, I think at some point we were bigger on TikTok than Nike. Which is, you know, a brand that has existed for a very long time. We all obviously know Nike. Um, so it, it is a very strong brand. And the other thing that is like, I always say it's like, we, we run the world's most efficient marketing organization. It's like people think, oh yeah, you know, they're, they're big because they, you know, they spend a lot of money on advertising and, uh, social media influence and stuff. It's actually. By impact, we must be the, the, the most efficient marketing org. It's a small team. It's a small team.

AI assessment note: “Yeah, I, I, I don't, I don't know. I, I, I think”

Q How do you think then about Synthesia, about 11 Labs, about some incredible lovable in Sweden being built from Europe?

A That is great. I think for, and you know, uh, they, they, They should deserve all of our support. And you know, the, the, the, the, the, the sad part is also, I think in, You know, in Silicon Valley is like being a tech founder is, is, is really, you know, you're, you're mostly a good person. Of course, there's also, uh, it's, it's, it's, it's aspiring, right? So, so people want to be that. I think a lot in, a lot of people in, in Europe, you, you just like, you're kind of like, why are you doing this? Like, why, why, you know, like, or, or, or they, they, they look at it as like, oh yeah, you know, they're just doing it for the money or, uh, there's this suspicion. Uh, almost of, of, uh, you, you, you can't be too successful or you can't be, you shouldn't be too ambitious. And, and I think that, that, that is very detrimental to the, the European startup ecosystem.

AI assessment note: “That is great. I think... They should deserve all of our support.”