No Priors Ep. 114 | With Duolingo CEO Luis von Ahn

Hi listeners and welcome back to No Priors. Today we're joined by Luis

Priors. Today we're joined by Luis Funon. Luis earned his PhD in computer

Funon. Luis earned his PhD in computer science from Carnegie Melon and went on to found Recapture, which was acquired by Google in 2009. He's now the co-founder and CEO of Dolingo, the

world's most popular education app with over 116 million monthly users, a market cap of 17 billion, and an owl mascot that faked its own death. We're going to talk about AI for education, why

motivation is the hardest problem in learning, taking risks with your company brand, why vibe cartooning is important, and the 16,000 AB tests that got us here. Luis, thank you so much for doing

here. Luis, thank you so much for doing this. Thank you for having me. Lots of

this. Thank you for having me. Lots of

people know what Dolingo is, but I would love to hear you describe it and in terms of, you know, beyond the uh language learning app it is today, what you want it to become. Well, it's it's a language learning app. It's the most

popular way to learn languages in the world. As of the last couple of years,

world. As of the last couple of years, we also teach math and music. And as of uh very soon, we will also teach chess.

The idea is, you know, we're trying to be an app where you can go there and learn the things that a lot of people want to learn, but that also take a long time to learn. You were a professor when

you started Duolingo in 2011. I hope it is not offensive to say that like lots of professors start companies. few of

them start like gamified consumer companies. Um how did this happen? It's

companies. Um how did this happen? It's

not like I expected to start a gamified company. The way we got started is um I

company. The way we got started is um I was a professor. Uh I had a PhD student named Severin who um is now the CTO and was a co-founder. But um we were looking

for a PhD thesis topic for him and what we agreed on is we were going to work on something related to education where computers would teach you something.

After a while, we agreed that good topic to teach was languages in particular because of learning English. In in most countries in the world, uh knowledge of English increases your income potential.

And there's like two billion people in the world learning English. So, we

thought, okay, well, let's teach languages and let's teach them with a computer. Um, and then we started

computer. Um, and then we started working on it and we ran into this problem. So, I made the first Spanish

problem. So, I made the first Spanish course because I'm a native Spanish speaker and Sever is a native German speaker and he made the first German course and we agreed that we were going to learn each other's language. The

problem that we ran into is that we couldn't get ourselves to do it because it was so boring. Oh no. I'm like, "Oh my god, I did not want to learn German.

He did not want to learn Spanish." We

were very worried because we're like, "Okay, well, if we ourselves can't get, you know, we can't get ourselves to do it, then we can't expect anybody else to do it." the solution was to um turn it

do it." the solution was to um turn it into a game as much as possible. And so

by the time we launched it was pretty fun. Um but it's it's mainly because we

fun. Um but it's it's mainly because we want we were trying to uh get ourselves to do it. And and part of the reason that that was the case is neither of us likes learning languages. We actually

are not language lovers. We don't like learning languages. And I think because

learning languages. And I think because of that, we made a product that works for the average person as opposed to for people who are obsessed with learning languages. So much there I would like to

languages. So much there I would like to unpack, but I want to go back to just initial confusion. What makes this like

initial confusion. What makes this like a good PhD topic? Like what was the computer science problem you were interested in? Uh the computer science

interested in? Uh the computer science problem was basically trying to teach things uh to people. Is that a computer science problem? Well, you know, how to get

problem? Well, you know, how to get computers to do it? There's a lot there, you know, how to do adaptive, you know, how we use the data to adapt to the to the student. Uh there's also motivation

the student. Uh there's also motivation problems and and you know, like human computer interaction. So there's there

computer interaction. So there's there was a lot there that we could have used.

And by the way, also at the time this was, you know, AI at the time was just starting to get to the point where we could have thought, you know, thought about training models to and this is not

large language models. This is just training classifiers to kind of teach better or something like that. So

there's a lot there that could have been a a PhD thesis topic. You've decided

that you need to make it easier for normal humans who do not have uh infinite motivation to learn languages from computers. What was the first thing

from computers. What was the first thing that you did that worked that like helped people get over the motivation hurdle of it being so boring? The first

thing that we did that worked was making lessons not 30 minutes long but 2 minutes long. It makes a big difference.

minutes long. It makes a big difference.

And it's not because people were spending less time. It's that 2 minutes is is amazing because at any point in time you just think to yourself, "Oh, it's just 2 minutes." But the time

investment for 30 minutes, you know, if you're right now and you're like, if I ask you, do you want to do something that takes 30 minutes? You're like, oh man, I don't know about that. Even

though when the you think the time investment is only going to be 2 minutes, you may spend the 30 minutes, but it's just it's just like, yeah, I can start right now cuz I can end any time. Uh, so that's the first thing that

time. Uh, so that's the first thing that worked. Uh, we did many other things

worked. Uh, we did many other things that worked big, but that was the first thing that that really was a big big game changer. Is there anything that

game changer. Is there anything that really surprised you from a behavior perspective that worked? A few things. I

did not expect streaks to be this powerful. I mean, a streak is extremely

powerful. I mean, a streak is extremely powerful. Can you explain what that is?

powerful. Can you explain what that is?

It's just a counter that measures the number of days you've done something in a row. Um, in for Dualingo, the Dualingo

a row. Um, in for Dualingo, the Dualingo streak is the number of days that you've um used Duolingo in a row to learn a language. It's incredibly powerful.

language. It's incredibly powerful.

People really talk about their streaks.

We have 10 million uh active users that have a streak longer than 365. So that means they haven't missed a day in the last year or longer. So I did not expect streaks to

longer. So I did not expect streaks to be this powerful. The other one that I did not expect this we have these notifications to get you to come back to the product. I did not expect the

the product. I did not expect the passive aggressive ones to work so well.

This is how it went. We we were sending you notifications that just said something like, "Hey, come back to learn Spanish." Um, if you did not come back

Spanish." Um, if you did not come back the first day, we would send you a notification. If you did not come back

notification. If you did not come back the second day, we would send you a notification. But after 5 days of

notification. But after 5 days of inactivity, we stopped. At some point, it occurred to me that um, if we're stopping to send you a notification, we should probably let you know. So, we

started sending this notification the fifth date that said these reminders don't seem to be working, we're going to stop sending them for now. Um, it turns out this is very powerful at getting people to come back because they feel

like we've given up on them. I did not expect that. I mean we didn't even do

expect that. I mean we didn't even do that with with the goal of getting people to come back but it turns out that's actually very powerful. I have

not studied education and so this doesn't come from a place of knowledge but uh this idea of like making it easy and like making the you know barrier to

entry lower. I I feel like there's some

entry lower. I I feel like there's some controversy around it. It raises

questions like okay learning is hard and and like there is no way around it. Like

a smart friend of mine compared learning to like going to the gym, but for your mind like it's very simple. You just

have to do it and there's no other way besides like being willing to put the effort and think really hard about it.

How do you react to that point of view?

I would be very very happy if everybody who is working on an education app thought that way because then we will have no competitors. It just turns out

that the hardest thing about learning is motivation. By the way, I believe that

motivation. By the way, I believe that to be true of the gym, too. You know,

it's like a lot of people talk about like, you know, you can you can spend all your time debating whether an elliptical machine is better than a treadmill, but in the end, what matters is that you do it. Uh that that's like

90% of what matters. Uh it's the same with learning something. You know, you can spend all your time debating whether you should read that book or that or this book or whether you should do it through an app or you should do it to a tutor. There there's of course

tutor. There there's of course differences in how uh effective each of these are. But what matters the most is

these are. But what matters the most is that you actually do it. And if you want to get people to actually do it, you have to make it as easy as possible to get started, to get in there and to be

motivated. I believe that is the reason

motivated. I believe that is the reason why we uh have grown so much. I mean,

and in fact, it's funny. I mean, we see a lot of um language learning apps that pop up that say, "Oh, we're like Duolingo, but without the gamification."

And every time I see that I'm like great, you do that. Carry on. 99% of the world's population just is not that motivated for any activity. And um you

know there's the few people that are extremely motivated. Good for them. The

extremely motivated. Good for them. The

vast majority of people are just not. If

you are an engineer or you know in many other types of knowledge work, the idea of flow is almost holy, right? like you

need to be like in the context and understand the codebase and like be really thinking about it for a while or you won't make any progress much less like learn something new. Do you think about that at all when because if people are like I'm on the subway I'm going to

do a lingo for 2 minutes like how does that factor into the experience? We

don't really think about that too much.

I mean I understand the concept and it makes sense but I mean for us the single most important thing is to get people time on the app. You know, we know turns out for an English speaker getting to a

pretty good spot in Spanish takes about 500 hours. Oh wow. Okay. We just got to

500 hours. Oh wow. Okay. We just got to clock those 500 hours. We just got to clock those. Like that's it. And you

clock those. Like that's it. And you

know, is it 600 hours because you're not as uh you know, in flow or is it 400 hours because you're like really in flow? Sure, there's probably a variance

flow? Sure, there's probably a variance there, but in the end, we have to clock something like 500 hours for you to get to a good spot in Spanish. And by the way, that same number for Chinese is

2,000 hours. Yes. Um, as somebody with

2,000 hours. Yes. Um, as somebody with a, you know, master's degree in Chinese lit, it's not a language meant to be learned.

It really doesn't seem to be. I find

your perspective on the human behavior around education both like a little bit dark like not particularly idealistic and yet incredibly inspiring to me as a

sort of enduser because I am working I'm engaged in the work I have three kids I theoretically do some other things and yet the thing I would like most be interested in doing with my free time is

skill acquisition right like be a better chess player improve my Chinese as like you know fruitless as that seems to be or um learn more math, many different

things. And yet uh if you ask me, are

things. And yet uh if you ask me, are you going to carve out, you know, an hour and a half at the end of a day where you've been attempting to be productive for 16 hours and do more of

that in a really painful way? The answer

is clearly no, right? Right. And yet, if you ask me, could you imagine putting 600 hours into it, 2 minutes at a time over the next few years, like actually

that seems doable. After working enough in in consumer products, you realize a number of things. I mean, um, people don't read, they just don't. Um, people

are lazy. Uh, and if given the choice, they may tell you all kinds of things, but the reality is that if given the choice, they'd rather scroll on Instagram or Tik Tok. like that's just

that's just reality. The thing that is positive in all of this is like you can take some of that behavior and do do something useful with it. Anyway,

perhaps that's what we're trying to do with Dualingo. I mean, that's that's

with Dualingo. I mean, that's that's what we're trying to do is to use a lot of the the same tricks that are used uh to keep people engaged with with mobile games or whatever it is, but to get them

to learn something. I mean, that's that's really at the crux of what we do at Dualingo. Dolingo has a a pretty

at Dualingo. Dolingo has a a pretty unique position in that you were a company with some scale when the uh

capabilities in machine learning started sort of accelerating in their progress and expanding. How did you handle that

and expanding. How did you handle that and sort of how did you react internally as a product organization? I mean for us it's been really positive. Um the fact

that you know they are language models um you know and we teach languages it's a really perfect application. Um they've

been really positive in two ways to teach something. One of the things you

teach something. One of the things you have to do is create a lot of content because it's the content that you're trying to teach. We used to make that content kind of half by hand automatically. like it was kind of by

automatically. like it was kind of by hand, but it there was all kinds of automation around it to to make people to make the the people that were creating the content go faster, but still this was going relatively slow.

Over the last couple of years, what we did is we've retoled this whole content creation pipeline to be entirely based on large language models. I mean, it's

all based on AI. So, humans are not involved any longer uh or or very little if if if at all. And what that has allowed us to do is just create massive amounts of content that were just not

possible before. So we're just we're

possible before. So we're just we're creating many more courses. So for

example, that's one of the things that we're that we're doing right now. Um and

we're just launching it right now. We

used to have we teach 40 languages. But

the way we teach languages is we teach, for example, we teach Spanish for English speakers, which is a different course than Spanish for German speakers, which is a different course than Spanish for Chinese speakers, etc. So, we used

to teach 40 languages, but for English speakers. So, if you were a native uh

speakers. So, if you were a native uh German speaker, you could only learn like four of them. What we're able to do with AI now is because we can go so much faster. At this point, we basically

faster. At this point, we basically teach the 40 languages to every base language and we're we're that that's that's a major increase in the number of courses. Um, so that's that's an example

courses. Um, so that's that's an example of something that we can do. The other

example of something that we can do now uh that we couldn't do before is practicing conversation. You know,

practicing conversation. You know, historically we could teach you vocabulary, how to read, but this actual conversation, the only way we knew how to practice it was with another human.

And we experimented with doing that. Um,

but it turns out most people don't want to talk to another human in a language that they are not very comfortable with because it feels bad. It feels bad. It's

it gives you shame. It gives you, you know, it's not good. But now with large language models, you can actually practice conversation with an AI and then you you do so without feeling

judged. Um, and so we're seeing a lot of

judged. Um, and so we're seeing a lot of uptake on that. Um, so it's it's it's been really good for us. What else are you excited about in terms of like AI

changing the product itself like role play and explain my answer and of these things like what do you think matters or works so far? You know, I'm excited about uh generally practicing real world

language like conversation. I'm I'm I'm excited about that. Outside of language, I'm really excited about teaching math.

We can do a much better job at teaching math with large language models. And we

have a math course. Um but it is is, you know, we're completely retooling it um to be a lot more like a tutor. Now, you

know, again, I'll go back to tutors.

Tutors can be really good at kind of learning outcomes. They have this one

learning outcomes. They have this one big problem. They're really boring.

big problem. They're really boring.

So, we're trying to find ways to make it a quote unquote tutor, but that is also gified. Just turns out most people would

gified. Just turns out most people would rather play Candy Crush than sit there in front of a tutor. So, we're trying to come up with something that is as effective as a tutor, but as fun as Candy Crush. The reality is we'll

Candy Crush. The reality is we'll probably come up with something that is 90% as effective as a tutor and 90% as fun as Candy Crush, but at least the combo of this will be a lot more

effective. So, math, music, uh, chess,

effective. So, math, music, uh, chess, chess now. Chess now. Yes. How do you

chess now. Chess now. Yes. How do you decide what Dolingo can teach beyond languages? What we're looking at for

languages? What we're looking at for subjects to teach are one, we're looking at very large audience. So we need something that hundreds of millions of

people want to learn. There's a reason for that and it's because we're an app at the end of the day and we cannot charge $30,000 to each user. we charge you 10

bucks in order to make a significant amount of money from a a new subject. It

has to be learned by a lot of people. Uh

otherwise these very niche subjects just you know if we charge you 10 bucks and there's only 100 people learning it, this is just not worth our time. Um so

they have to be they have to be a large potential audience. Uh the other thing

potential audience. Uh the other thing is we look for things that take a long time to learn. uh you know if you can learn something in two hours you probably should just go watch a YouTube video and that does a perfectly good job

if it's just like two hours we look for things that really take hundreds of hours to learn um and then things that we think are uh are good for the world and we can do a good job with a mobile

app. Oh there's one extra thing which is

app. Oh there's one extra thing which is internally we need to have somebody that's really excited about it. Um so

this has been true for all of these other subjects. you know there's

other subjects. you know there's somebody that's very excited about music, somebody is very excited about chess and that that's what has done it.

Okay. Even beyond like what makes sense for Dolingo as a business from a technology perspective, do you think there are things that are like hard to

teach with computers for now? I don't

know if there are there's things that are different that certainly different from what we do at Dualingo. So for

example, history, the way you teach history is not with these drills. You

know, the Dualingo is really good at drills. The way you teach history is

drills. The way you teach history is probably with really well produced videos. It's probably the best way to do

videos. It's probably the best way to do it. And maybe AI can get better at that,

it. And maybe AI can get better at that, but uh so I think there are just things that are different than Dualingo, but ultimately I'm not sure that there's anything that computers can't really teach you. I think overall we we'll be

teach you. I think overall we we'll be able to teach everything really well with computers. Do you think there's any

with computers. Do you think there's any version of the world where AI is a threat? Like large language models are a

threat? Like large language models are a threat to Dolingo? I mean, sure, they're a threat to I mean, you know, that's one of the things that is scary about the world that we live in with with AI and large language models.

We're undergoing a platform shift. I

mean, of of some sort. Um, I don't know what's going to happen on the other side. I'm not super worried, but you

side. I'm not super worried, but you just never know. And it's not just for Dualingo. It's could be all kinds of

Dualingo. It's could be all kinds of things, right? I mean, could be a threat

things, right? I mean, could be a threat for Netflix. Like, it could be that just

for Netflix. Like, it could be that just a large language model just press a button and it makes you the perfect movie. And then, so, you know, I don't

movie. And then, so, you know, I don't know if that will happen or not, right?

I I just don't know. So, it's it's kind of a similar thing. Like, who knows what will happen. Um, at the moment, it

will happen. Um, at the moment, it doesn't look like it's it's a major threat but um your guess is as good as mine. I

think I mean, you guys have a huge amount of distribution and a huge amount of data and the interest in engineering culture to go after it. So, the way we see it is we have large distribution. We

have data on how people are learning languages that is unique. I mean, we have the you know, a lot of people. It's

also the case that brand ends up mattering quite a bit. Um, and we do have a good brand for language learning.

Uh, so the combination of all of this we're hoping will be good for us. Can we

talk about brand for a minute? Because

it it is um, Duolingo has a very unique one. There is perhaps more risk and more

one. There is perhaps more risk and more distinctiveness in brand voice uh, than the vast majority of public companies might take. You are of course a consumer

might take. You are of course a consumer company, but there are plenty of companies who um don't don't take those risks. Like where does that come from

risks. Like where does that come from for you guys? Why did the owl die? He

didn't die. He just faked his death.

Okay, that's even weirder. Uh this it's not like we on day one decided, you know, we're going to have a brand that is unhinged that where the owl does weird stuff. It just kind of evolved

weird stuff. It just kind of evolved over time. Our brand voice evolved over

over time. Our brand voice evolved over time. Uh what happened was in the

time. Uh what happened was in the product the owl was a little pushy to get you to do your lessons and then the internet uh just started coming up with

memes about the owl doing crazy stuff like you know um they started coming up like you know with uh the owls willing to kidnap your family for you to do a

your lesson. That all was invented by

your lesson. That all was invented by the internet not by us. Um, but as we saw that that was happening, we started leaning into it, we thought, why not?

And, um, the more we lean into it, the better it worked. Um, and so we just found something that resonated. You

know, that got us going. Then a few years ago, um, we had a very junior marketing employee that we had just hired who said, "Hey, uh, we have this old owl suit here that we had used for

like events inside the company and just said, "Hey, can I make some Tik Toks out of it?" Um, and I actually was against

of it?" Um, and I actually was against it. I'm like, m I don't I don't know if

it. I'm like, m I don't I don't know if anybody's going to be interested in this. Um, and it turned out that when we

this. Um, and it turned out that when we put it on TikTok and the owl was, it really was just the owl doing really dumb stuff. Um, like, you know, twerking

dumb stuff. Um, like, you know, twerking and falling down or whatever. Um, a lot of these videos started going viral. And

it was interesting because none of the videos said, you know, learn a language on Dualingo or, uh, subscribe to Duolingo, anything. It really was just

Duolingo, anything. It really was just the owl doing weird stuff. It just, you know, it took a life of its own. We

formalized a lot of it. and we have a pretty good idea of the types of risks we're willing to take, but we do take more risks than most companies certainly than most public companies. Um, one of the thing that I think helps us, so it

helps us that we have a mascot, but I think it also helps us that we're an education company because, you know, ultimately education, you can't really say that education's bad. It's hard to argue against education. So, that allows

us to that allows our marketing to do things where we can't be criticized that much. If we were if we were a company

much. If we were if we were a company that was trying to like just really extract your money or like you know we were like a a vaping company or something probably people would would um

you know push back more on our marketing but given that we're an education company I think it it gives us a little more leeway. Given this like unique

more leeway. Given this like unique scale of Dolingo I think it's uh more than 100 million people monthly. Is that

right? Yeah. Yeah. What do you know about how people learn that other other humans don't that you think is interesting? A lot of it is just

interesting? A lot of it is just codified on what the algorithms have adapted to. I mean, we have adaptive

adapted to. I mean, we have adaptive algorithms that try to figure out how to teach. And I think it's hard to

teach. And I think it's hard to verbalize a lot of it. I mean, we know a few things that are that are that you can verbalize um that, you know, may not be that surprising, but the farther your

language is from your native language, the harder it is to learn. We have a model that can predict whether you're going to get an exercise right or wrong.

And we're actually extremely accurate.

So, when we give you an exercise, we know if you're going to get it right or wrong. We're very accurate. Um, and the

wrong. We're very accurate. Um, and the way the way we do that is we just watch everything you're doing and we see what you're good at and what you're bad at.

And for example, we know we know for each user, this particular user is bad at the past tense. Um, one of the things you may think at first that the right thing to do is because this user is bad

at the past tense, we should give them more past tense. And that's roughly true, but it's not exactly true because if all we did was give you lessons that of things that you're bad at, these

would be very, very, very horrible lessons for you. So, there's a whole uh, you know, I was going to say arts, but it's actually more of a science. There's

a more of a science about when to give you the things that you're bad at. And,

and for example, um, whenever we give you an exercise, the right thing to do is to give you an exercise that you're about 83% chance of getting it correct. Uh,

turns out that maximizes enjoyment. And

maximum enjoyment means I'm going to get to my five or six hundred hours and that's really the outcome. Exactly. And

it just keeps you it keeps you motivated. Um, and and it's funny, it's

motivated. Um, and and it's funny, it's not it's not 100% because 100% is too easy. It's just But it's also not 50%.

easy. It's just But it's also not 50%.

It really is closer to 100%. You got to mostly win. Um, and that that seems to

mostly win. Um, and that that seems to be um what works. What do you think are some of the implications of what you guys are doing or learning for uh

traditional education and schooling?

First of all, I do think that education is going to change over the next some number of years. I can't say one year, but it's it's probably less than 20 years. Some things going to change and

years. Some things going to change and and the reason for that is um it's just a lot more scalable to teach with with AI than with teachers. And by the way, that doesn't mean the teachers are going to go away. You still need people to

take care of the students and you still need I also don't think schools are going to go away because you still need child care in your view like schools could be child care but everybody's dual lingoing. I think it's going to be

lingoing. I think it's going to be something like that. It may not be dualingo but I think it's going to be something where there's one teacher and like 30 students. Each teacher cannot give individualized attention to each

student but the computer can. And really

the computer can actually know with with very precise uh uh knowledge. It can

have very precise knowledge about what you you this one student is good at and bad at that the teacher just has no chance of having because there's 30 students and they just cannot give you that. So I do think that it it would be

that. So I do think that it it would be more effective if some of that time is being spent with essentially an AI teaching you. Um I do think it's going

teaching you. Um I do think it's going to get to that. It's also the case that, you know, there are extremely good teachers for sure, but there's not very many of them and certainly most everybody in the world doesn't have

access to a good one. So, I think that there's going to be some some change like that. I do think it's going to take

like that. I do think it's going to take a while because, you know, changes in education are very slow. Um, but I I do think it's going to be like that. I

think a lot of what we're doing will apply uh in terms of keeping people motivated, etc. Uh, I do think that in a formal education setting, some things do need to be different. you have a little more control over the students actually

doing this stuff when they're in school.

So you can probably make them kind of instead of uh expecting that they're only going to do 2 minutes, you can probably expect that they're going to do 20. Uh so so there's some differences in

20. Uh so so there's some differences in the school setting, but I think a lot of what we're learning here will apply. Is

there anything um you feel like people misunderstand about Dolingo? When we

became a publicly traded company, investors thought we were a co phenomenon. Um turns out we were not.

phenomenon. Um turns out we were not.

The biggest misunderstandings are how important motivation is. I really don't think people understand the I mean even our competitors even even not just competitors for language learning like people who do education companies. It is

amazing to me that really most everybody that we talk to does not seem to understand how important um motivation is. I think that's one thing. I think

is. I think that's one thing. I think

another one is just how much sophistication there is. uh a consumer may not know because the app is so cutesy and like you know little animations and everything there's a lot

of sophistication about when to give you even the animation. Uh so there's a lot of sophistication about that and I don't think people understand just how many you know the Dualingo is the result I checked the other day um we have run

over the history of the company we have run 16,000 AB tests and I don't think people understand that it has taken 16,000 AB tests to get to this point.

Um, yeah, I think that's probably the biggest misunderstandings. Any

biggest misunderstandings. Any predictions about what the large-scale changes in learning uh mean for society or or even how you might uh encourage people to think about learning for

themselves or their children. The good

news, I don't know good or bad news, maybe probably bad news for Duolingo, but good news is this change is going to be slow. I don't think you're going to

be slow. I don't think you're going to see a change where like next year everybody's learning completely different. So, I think we'll have some

different. So, I think we'll have some time to adapt. What's the drag force? I

feel like that's actually a controversial point of view that it's going to be slow. Oh, go to a real school. They're doing stuff from like 30

school. They're doing stuff from like 30 years ago.

They're the drag the drag is just, you know, it's like government. Uh the it's just slow. If you live in, you know, New

just slow. If you live in, you know, New York or Silicon Valley, you'll see that, you know, there are schools that are doing really progressive stuff, etc. But the vast majority of the education system, it's very slow to make changes

like this. school systems are

like this. school systems are um regulated. You know, in Texas,

um regulated. You know, in Texas, they're trying to not teach evolution.

Like, there's just weird stuff that goes on in school systems. So, I think in general, it's going to take some time to do this. You probably will see some

do this. You probably will see some private schools um move there faster.

There's also an interesting thing about private schools, the very fancy private schools. You pay 50,000 bucks a year to

schools. You pay 50,000 bucks a year to go to a private school. It's hard for them to say, "Well, what our kids do is use Dolingo.

because it's like, well, why am I paying you 50,000 bucks? Um, so it's so it's an interesting uh, you know, dynamics that's going to happen, but I do think that some of the private schools are probably going to be the first ones to

start really kind of moving to toward towards this. And I think you'll just

towards this. And I think you'll just see a lot better learning outcomes um, in general. Um, the other place where

in general. Um, the other place where where you may start seeing is there may be some countries that leaprog um, some countries that are at the moment probably a little behind. you know for them this is the only way in which they

can sca they can scale their education so you may see that yeah I tend to think um very tactically also about impact on the like entrepreneurial ecosystem and maybe it was all about finding the idea

but you studied math and then you studied CS you got a PhD and you were a professor and had done some body of work before you became an entrepreneur including starting another company actually a really interesting one

recapture but one of the things that is interesting to me even like let's say 15 years into the technology ecosystem in

my own career is uh people are becoming experts at much younger ages. Oh yeah. I

think obviously if you can set yourself on a learning journey like first it was just because of you know the internet right you can learn from just content and forums and finding community and

whatever else um but when I think about some of the dropouts that we work with who are like well I wrote a textbook on wireless technology as a sophomore and

I'm like man I I waitressed at Outback Steakhouse when I was 16 right right one of the things that I I think would be really exciting As you know, we look

forward five or 10 years. Actually, if

people can get to skill acquisition and learning outcomes that are much cheaper, broadly accessible, and easier to motivate, you know, you you will get experts that are um uh doing really

interesting things by the time they're 15, 20. Yes. And not only will they that

15, 20. Yes. And not only will they that will be true, but I think they'll be experts and they'll have the tool of AI.

Mhm. So I think it'll be the case at least in the foreseeable future that'll just magnify their expertise. So they're

they're experts and in addition to that they can go a lot faster or they so yeah I mean compared to you know waitressing at Outback Steakhouse or you know

whatever dumb thing it is that I was doing when I was I mean I did not have access to the first time I had access to the internet. I I must have been like 15

the internet. I I must have been like 15 years old. I don't know what I was doing

years old. I don't know what I was doing before that. But I think I was playing

before that. But I think I was playing with like Legos. Uh I mean that's that's basically what I was doing. So yeah, I think there's we're going to see a lot

of that. So it sounds like course

of that. So it sounds like course authoring is a place that Dolingo's gotten a lot of leverage. When you think about just using AI broadly as a tool

within your company, be it building product or everything else you do. Um

where else do you think it can have the most impact? The visual style of

most impact? The visual style of Dualingo. We're very I mean unlike most

Dualingo. We're very I mean unlike most well I mean a lot of apps are are kind of you know well designed that's for sure but we're very animated like a

we're like a cartoon I mean dueling was like a a cartoon making that has required a lot of um human effort uh it turns out we can

do a lot of that with computers now it now that doesn't mean we're not going to employ um the artists the artists are still here but they are going so much faster. What one artist could do before

faster. What one artist could do before in like a month now they can do in like a day. It's really unleashing their

a day. It's really unleashing their creativity because they're not spending their time on the mechanics of like is this is this shadow just right? No,

they're just they're just unleashing their creativity. And I think that's

their creativity. And I think that's that's that's pretty awesome. And so

we're seeing a lot of that. Um you know, a lot of our animations and a lot of illustrations are um now computerenerated. That's not what I

computerenerated. That's not what I expect you to say, but I um am really thrilled for the future of math and chess and 140ome new languages and vibe

cartooning for Duolingo. It'll be great.

Yes. Thank you so much for doing this, Luis. Yeah, thank you. Thank you, Sarah.

Luis. Yeah, thank you. Thank you, Sarah.

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