Duolingo’s battle for learning in an AI world, with Luis von Ahn

Summary

Masters of Scale: Duolingo’s Battle for Learning in an AI World

Guest: Luis von Ahn, CEO and Co-Founder of Duolingo
Host: Bob Safian
Date: May 12, 2026

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Overview: Navigating Learning and AI at Scale

In this episode, Luis von Ahn discusses Duolingo’s unique approach to online learning, the challenges and lessons learned from rapidly evolving AI, and his company’s shift in 2026 from profitability to ambitious user growth. The conversation explores how Duolingo leverages fun and motivation over strict seriousness, the pitfalls of deploying AI, and what it means to aspire to educate a significant portion of humanity in the age of technological acceleration.

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Key Discussion Points & Insights

The Power of Fun and Motivation in Learning

• Duolingo’s Playful Approach:
  • The app’s playful and sometimes “unhinged” mascot (the green owl) and social stunts are deliberate tools to keep users engaged, regardless of age.
  • Luis von Ahn [04:31]: “Our belief about teaching is… it's equally or more important that we keep you entertained while you're learning, because otherwise, you know, most people just won't learn all that much.”
• Applicability Across Ages:
  • The idea that “serious” learners wouldn’t want fun learning was proven wrong by engagement data.
  • Luis von Ahn [05:20]: “Whenever we make it more fun, even the people who call themselves serious learners end up doing more.”
• Engagement vs. Learning:
  • Fun and engagement aren’t just retention tactics, they lead to more learning by getting users to spend more time on the app.
  • Online learners have lower tolerance for frustration than classroom students, so the method must be more “entertaining” to maintain commitment.
  • Luis von Ahn [06:50]: “The level of frustration we can give to users has to be lower than what a classroom does. And that probably makes it so that we probably are teaching a little less, but we just want to have a lot more time.”

Lessons from an AI Memo Backlash

• AI Integration Missteps:
  • In 2025, Luis emailed staff about requiring every team to prove AI couldn’t do a job before hiring and assessing employees on their “AIUs.” The external world saw this as a threat—stock price fell and public concern rose.
  • Luis von Ahn [08:50]: “Absolutely. I did not think this was going to be controversial, because internally, inside Duolingo, this was not controversial.”
• Clarifying Intentions:
  • Clarifies there’s been no layoffs; Duolingo actually increased headcount after the memo.
  • AI was meant to empower, not replace, people.
  • Luis von Ahn [09:56]: “Our employees are just way more productive if they use AI, and so I actually want to hire more people because they can do more.”
• Evolving Policy:
  • Evaluating everyone on AI usage led employees to use AI unnecessarily. Now, performance is based on contribution rather than specific tools.
  • Luis von Ahn [11:38]: “For most of our employees, using AI helps them contribute more… However, there may be cases where it may just not help all that much.”

The Limits and Opportunities of AI in Learning

• Quality Limits:
  • AI shines in demos and one-off cases but is unreliable when generating content at scale (e.g., 1000 stories for language lessons—20% may be low quality).
  • Luis von Ahn [13:11]: "We're just not seeing AI get to the level of creativity or the level of polish that our top people have by any means."
• AI in Coding:
  • AI can help engineers sometimes work 10x faster, but inconsistencies and debugging offset many gains.
  • Luis von Ahn [14:28]: “For the longest of times, if you would read Twitter, the vibe there was, you probably should just fire all your engineers, because AI can code way better than any human. That is just not true.”
• Golden Rule of AI at Duolingo:
  • AI’s use is justified only if it benefits learners, not just for efficiency or cost savings.

Strategic Shift: Prioritizing User Growth over Profitability

• Why User Growth Matters in 2026:
  • AI is transforming learning; with the landscape changing, maximizing reach is paramount.
  • User growth slowed slightly by late 2025; Luis wants acceleration now to capture future learning demand.
  • Luis von Ahn [15:44]: “Whenever you see that there's a huge opportunity in front of you, I think what you want to do is just capture as much of the market as possible.”
• Freemium Dynamics:
  • 90% of users don’t pay; 90% of revenue comes from 10% premium subscribers.
  • Can increase paid conversions by increasing ad load, but wary of alienating users who can’t pay.
  • Luis von Ahn [18:48]: “You're kind of driving them away.”

Rethinking the “Unhinged” Brand and Content Offerings

• Marketing Evolution:
  • Duolingo’s social presence will balance its 80% unhinged/20% wholesome ratio, keeping fun but emphasizing effectiveness.
  • Luis von Ahn [22:41]: “We need to thread the needle here to try to continue being fun, but also move a little more towards having a message that is like, hey, you know what? Duolingo actually really works.”
• Beyond Languages:
  • Expansion into math, music, and chess—subjects that require long-term practice and are meaningful.
  • Luis von Ahn [23:56]: “We may not teach everything, but we want to teach the subjects that are meaningful to you that also take a long time to learn.”
  • Chess has been the fastest-growing non-language subject; Luis hopes math will eventually surpass chess.

Navigating Stakeholder Priorities

• Investors, Users, and Employees:
  • Their interests are sometimes oppositional: users want free quality, investors want maximized revenue, employees lie in between.
  • Luis von Ahn [26:50]: “Users… want to get the entirety of the learning as good as possible and as free as possible… investors, you just want us to charge every user as much as we can…."
• Mission vs. Profit:
  • Luis believes long-term alignment between educational impact and financial success, but not always in the short term.
  • Luis von Ahn [27:28]: “In the long term… what's going to also make the most money is a company that really is putting the education of the users first.”

AI’s Threat to Human Learning: Why Still Learn?

• Compelling Argument for Learning:
  • Even in an AI-saturated world, learning brings meaning, logic, and opportunity (e.g., learning chess after computers dominate the game).
  • Luis von Ahn [28:36]: “It would be a chaotic society if nobody learned anything… people still need to learn stuff, including math….”

The True Challenge of Teaching

• It’s All About Attention and Motivation:
  • Books can teach anything, but most people can't sustain attention. Keeping people engaged is more difficult—especially as attention spans shrink.
  • Luis von Ahn [30:10]: “A book. You can actually learn almost any subject you want… But… the vast majority of the human population does not have the stamina…”
• Personalization: Universals vs. “Cultural Differences”:
  • Some personal adaptation exists, but universal motivators (like progress bars) consistently outperform niche tweaks.
  • Luis von Ahn [30:57]: “Pretty much every human will want to fill [a progress bar] to 100%... I think there are more universal truths.”

Talent and Culture Insights

• Unconventional Interview Techniques:
  • Duolingo once asked limo drivers to report on how candidates treated them; being courteous and non-arrogant matters.
  • Luis von Ahn [32:08]: “We have this internal rule that we'd rather have a hole than an a hole.”

The Big Vision

• Long-Term Ambition:
  • Luis aspires for Duolingo to help billions—not just millions—find meaning through continual learning, resisting the specter of “doomscrolling” and disengagement.
  • Luis von Ahn [02:04/32:55]: “The type of world that I would like to have is a world where people really are bettering themselves… Will it be the case… billions of people actually learning something, as opposed to either doomscrolling or just giving up on life because AI can do everything?”

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Notable Quotes & Moments

• Luis von Ahn [06:06]: “If you want to learn Spanish and you're an English speaker, you kind of have to put in about 500 hours… It's kind of similar with exercising.”
• Luis von Ahn [11:38]: “There may be cases, projects, or particular roles where [AI] may just not help all that much. And so saying blanket statement we're going to evaluate you on the usage of AI was not needed.”
• Luis von Ahn [15:44]: “Whenever you see that there's a huge opportunity in front of you, I think what you want to do is just capture as much of the market as possible.”
• Luis von Ahn [26:50]: “Maybe in the long term they all are, but certainly in the short term… users… want… as free as possible. Investors… to charge every user as much as we can.”
• Luis von Ahn [32:08]: “We have this internal rule that we'd rather have a hole than an a hole.”
• Luis von Ahn [32:55]: “We got to more than 100 million active users, but that's too small of a fraction of humanity for me to claim victory.”

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Major Segments & Timestamps

• [02:04]: Luis discusses his vision for meaningful learning in the age of AI.
• [04:31] – [07:13]: Playfulness, engagement, and the science of motivation in learning.
• [08:21] – [09:56]: The internal AI memo, controversy, and clarifying Duolingo’s AI policy.
• [13:11] – [15:28]: Where AI fails in content generation and coding; lessons for tech leaders.
• [15:44] – [18:48]: Duolingo’s 2026 pivot to user growth over profit; freemium model dynamics.
• [22:41] – [24:47]: Marketing, expansion beyond languages, and the strategy for new subjects.
• [26:05] – [28:17]: Stakeholder conflicts; mission vs. profit; how Luis sees the CEO role post-IPO.
• [28:36] – [30:10]: Why humans will still learn in an AI world; the deeper meaning of learning vs. convenience.
• [30:10] – [31:52]: The centrality of motivation and engagement in effective education.
• [32:08]: Culture fit in hiring and the “no a-holes” policy.
• [32:55] – [34:29]: Reflection on vision, scale, and the real meaning of “success” in learning.

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Summary Tone

The episode is candid, pragmatic, and optimistic, blending Luis von Ahn’s dry humor, deep insights, and personal reflections on risk, strategy, and mission.

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For Listeners: Why This Episode Is Vital

This conversation is an essential listen (or read) for entrepreneurs, educators, technologists, and anyone wrestling with how to balance progress, equity, and meaning in an AI-disrupted world. Von Ahn’s mix of data-driven decisions, humility about mistakes, and aspiration for social impact set a tone for leaders everywhere.

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Transcript

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[Luis Von Ahn]

hey

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[Luis Von Ahn]

what kind of world are we going to have? The type of world that I would like to have is a world where people really are bettering themselves. That is one way in which they find meaning in life. Will it be the case that in 10 years we can get a significant fraction of humanity's population, billions of people actually learning something, as opposed to either doom scrolling or just giving up on life because AI can do everything we got to more than 100 million active users, but that's too small of a fraction of humanity.

[Bob Safian]

That's Luis Von Ahn, CEO and co founder of Duolingo, the language learning app that crossed a billion dollars in annual reven last year. Duolingo is known on social media for its slightly unhinged owl mascot, but it was Lewis himself who went viral last year over an internal AI memo that sparked intense public controversy. Today, we talk through his tough lessons from that experience and what he's learned about the limitations of AI since that memo. We also talk about why he's made a strategic shift in 2026, emphasizing user growth over revenue growth, even though 90% of Duolingo's users are currently non paying. Plus, in the spirit of Duo the Owl, we talk about fun as a learning strategy, whether you're teaching languages, chess or new business ideas. So let's get to it. I'm Bob Safian and this is Rapid Response. I'm Bob Safian. I'm here with Luis Von Ahn, CEO and co founder of Duolingo. Lewis, great to have you with us.

[Luis Von Ahn]

I'm very happy to be here. Thank you for having me.

[Bob Safian]

You first hit my radar when I was editor of Fast Company. You helped invent Captcha and then Recaptcha, the security word puzzles that became kind of ubiquitous across the web. And then you launched Duolingo, which is this sort of playful but pragmatic language learning system that really took off and now it's crossed a billion dollars in annual revenue last year. Duolingo has always been unexpected. Certainly your social media campaigns have gotten a lot of attention. How important is the unexpected and playful to what Duolingo does?

[Luis Von Ahn]

I mean, ultimately, it's pretty, pretty important. I mean, what we want to do is we want to teach people and we want to literally teach billions of people. Most people will tell you they want to learn something, but what people say and what people do happens to be very different. Certainly trying to be a fun brand, an unhinged brand that gets people to learn. And so, you know, our belief about teaching is that it's really important that we teach you something well, but it's equally or more important that we keep you entertained while you're learning, because otherwise, you know, most people just won't learn all that much.

[Bob Safian]

And I mean, a lot of your users are adults, so it's not just kids that you're trying to get to be playful. And it's just important for those of us who are trying to be lifelong learners.

[Luis Von Ahn]

Yeah, a lot of our users are adults. Basically. Our users are the whole range from age. They need to know how to read. So, you know, age, call it 6, 7 to like 100. When we started Duolingo, there were people that would say, no, no, no, no, serious learners are not going to want this because, because it has to be serious, et cetera. We have just never found that making something less fun helps. Whenever we make it more fun. Even the people who call themselves serious learners end up doing more.

[Bob Safian]

And the decisions you make about duolingo, like, is there ever a distinction between engagement and learning? There are, you know, some parts of the tech world where there's sort of been blowback about emphasizing engagement too much.

[Luis Von Ahn]

They mostly go hand in hand because the most important thing is that people spend the time learning. If you want to learn Spanish and you're an English speaker, you kind of have to put in about 500 hours. Like, that's. That's basically it. It's kind of similar with exercising. I mean, whether you're doing the elliptical, the treadmill, it probably matters a little bit. But what matters the most is that you're actually doing it a certain amount of time every day. When people are learning on duolingo, the setting is a little different than a classroom. In a classroom, I think you can frustrate users, in this case the learner, a little more because they kind of have to be in the classroom.

[Bob Safian]

It's not so easy for them to get up and walk away.

[Luis Von Ahn]

Whereas in duolingo, we are always one click away From Instagram or TikTok or whatever, whatever you want. So the level of frustration we can give to users has to be lower than what a classroom does. And that probably makes it so that we probably are teaching a little less, but we just want to have a lot more time. And so in the end, it actually ends up being good for learning.

[Bob Safian]

I mean, right now, a lot of the. The learning that business people are being forced to do is technological is about AI. I know that that's not been the focus of what the learning is on duolingo, but are there things about the way we should be approaching learning about this new technology that you would take away from what you do? With duolingo, it certainly isn't often framed to us as being fun.

[Luis Von Ahn]

I think the most important thing I would say for learning anything, it doesn't have to be fun. It just has to be that it keeps people motivated. There are multiple ways to keep people motivated. With duolingo, we've chosen mainly fun. That's the main thing we've chosen. But you don't have to do that. I mean, for example, seeing results keeps people motivated. In the case of learning AI, I would say that's probably a better motivator of the form, like, I'm going to learn AI, but the first thing that I'm going to do is make myself a dashboard or like a mini dashboard or something. But I Think it just. If you find the right motivation, you know, that helps a lot.

[Bob Safian]

I mean, I have to ask you, because last year at this time, you sent out this all hands email about AI. That rattled things a bit, right? No new hires unless teams showed that AI couldn't do the job and existing places assessed on their AIUs. And it really sparked this blowback on social and the stock price. You're not unfamiliar with taking risks. Was this a bigger risk than you realized at the time?

[Luis Von Ahn]

Absolutely. I did not think this was going to be controversial, because internally, inside Duolingo, this was not controversial. We started as a technology company and, you know, I used to be a computer science professor that actually taught the AI class at Carnegie Mellon University. So we've. We've always used AI in as much as we can. So internally, this was not controversial at all. Externally, I think I was not very clear. And given how I wrote it, and without giving it more context, I opened it up to people thinking that what I was trying to do was to fire a lot of our employees. But that was never the intention. I mean, we've never done a layoff. We still have never done a layoff. In fact, last year when I sent that memo, we increased our number of employees, not decreased our number of employees. There was that misunderstanding because I think there's. There's a lot of fear that AI is going to substitute jobs, et cetera, et cetera. The way I see it here is our employees are just way more productive if they use AI, and so I actually want to hire more people because they can do more.

[Bob Safian]

It also seemed a little bit like you were sort of forcing people, you weren't making it playful to learn how to use AI. You were sort of like. It was almost like a bludgeon, right? Which. Which I guess wasn't the intent necessarily either, but. But I do think it's something a lot of folks are struggling with. Like, how do you get the people on your team who are more resistant to this new technology to. To get on board?

[Luis Von Ahn]

Yeah, I mean, the good news here is at Duolingo, we just. We hire a lot of people who are pretty young. I mean, we hire a lot of people who are straight out of college, and we have just not found a lot of resistance here. Internally, we have this thing we call the golden rule of AI usage, which is you have to use AI for the benefit of our learners. Like, everything we do with AI should be for the benefit of our learners. So, for example, if it helps you be more efficient at putting out More features. That's for the benefit of our learners. If we put out a feature that helps our learners learn better because they're now, for example, interacting with an AI to practice conversation, that's for the benefit of our learners. Sometimes when we use AI, we're able to save costs, but that is not the goal of our usage of AI. That is an okay thing, but it is not the primary goal. It has to be about helping our learners versus we're going to use AI to save 10 million bucks. That's just not all that motivating.

[Bob Safian]

And I just want to make sure everyone, because there have been some reports about you kind of walking back some of the things you said in that memo. You're clearly still a believer in AI, right? There's no doubt from, from you that sort of this is the direction the business has to continue to go.

[Luis Von Ahn]

I'm a big believer in AI, but that comes with some, you know, it definitely comes with asterisks and learnings. I mean, for example, my initial memo said that we were going to evaluate every employee on their usage of AI. I don't think that was right. Many people came to me and said, look, for the job that I'm doing, I'm finding that I'm just using AI for AI sake, because you're going to evaluate me on that. But it's not because I actually think that for this particular thing, we can do it better. And I think ultimately in the case of performance reviews, what you should evaluate is how much that particular employee is contributing to the company. It turns out for most of our employees, using AI helps them contribute more to the company. That is true. However, there may be cases, projects, or particular roles where it may just not help all that much. And so saying blanket statement we're going to evaluate you on the usage of AI was not needed. And so we've removed that. The other important thing that I think is important to mention when it comes to AI is that we're trying to use AI as much as possible, but we really don't want to decrease quality. For some things, AI is quite ready to do high quality stuff. For some things, it's just not. And so we're not going to decrease quality just for the sake of using AI.

[Bob Safian]

So where are you seeing AI not able to deliver that kind of quality?

[Luis Von Ahn]

In a lot of places, for example, we hire a lot of artists and designers and our app is very high craft on design, et cetera. We're just not seeing AI get to the level of creativity or the level of polish that our top people have by any means. The other place where I think it's just not the highest quality. One of the biggest problems, I think, with AI is that it demos really well. So what do I mean by that? It's just like, look, it can write a story, and if you see one story, probably wrote a really good story, like the one story they showed you, and my God, it wrote a story. But when you go, and in our case, we may need to write 1,000 different stories for people to learn a language, then you'll find that, I don't know, 20% of the things were just pure slop. Whenever we scale a lot with things with AI, we have to really be careful that slop doesn't get through. And if the quality is just not high enough, even though AI is really nice in that it can do it pretty fast, we just don't go for it.

[Bob Safian]

Yeah, I mean, I've heard some of that with coding, too. Like, it can be terrific in writing code, and then it can produce stuff that, like. Well, that just doesn't work. And you need to dig into that to test all of those uses. Yeah.

[Luis Von Ahn]

For the longest of times, if you would read Twitter, the vibe there was, you probably should just fire all your engineers, because AI can code way better than any human. That is just not true. Internally, you would see that your engineers were all using AI, but somehow you hadn't seen a speed up in engineering progress. Like the number of features we put out every month or whatever was just not increasing. And when you went to see why that was, you would see that, oh, it turns out in some cases, it does something amazing. And then the other cases, just like you said, it kind of doesn't work. But even worse, it's so hard to figure out why it didn't work, that you spend about as much time as you saved on the cases that it worked, figuring out why the other thing didn't work. It's getting a little better because coding agents are getting better. You can find a project with one engineer that maybe was 10 times faster, but overall, this is just not yet true.

[Bob Safian]

In 2026, you've sort of signaled a strategic shift for duolingo, prioritizing user growth over profitability, which seems like another risk, especially for investors. So why make this move and why now?

[Luis Von Ahn]

I decided that this year we would really spend it trying to work much more on user growth rather than revenue growth. And the reason for that is there's a number of reasons, but probably the biggest one is I really think that over the next few years, the way most people learn is going to change. I mean, AI is just going to allow us to teach significantly better than we have in the past. And we're already seeing it. Our product today in terms of teaching is way better than it was four years ago. We do studies to see how well our product is teaching. It's just getting better every year. So I think there's a huge opportunity in front of us. And because of that, whenever you see that there's a huge opportunity in front of you, I think what you want to do is just capture as much of the market as possible. The other thing that happened was that our user growth, particularly towards the end of 2025, did slow. It doesn't mean that we're not growing. We're still growing. We're still growing exponentially. But it did slow. And I sat here and I thought, wow, at a time when we should be actually accelerating user growth, it seems to be slightly decelerating. I really don't like that. So we're going to make that change. Now, of course, whenever you go out to the stock market and you say, this year we are going to lower our estimates for revenue, the stock market no likey. We knew this was going to happen. We knew. But I really do believe that this is the right thing to do for the long term of the business.

[Bob Safian]

And just so I'm sure that I and our listeners understand your business model. Most of your users are free users already supported by ads that come after a lesson. Most of your revenue is from premium users or premium fees. And so user growth means more emphasis on the free level.

[Luis Von Ahn]

Yeah, that's the main thing that helps us grow users. About 90% of our monthly active users are not paying us, and about 10% pay us. But the amount of money we make is flipped. So about 90% of the amount of money we make comes from the 10% that pay us. So most of the money we make comes from. From subscriptions. Increasing the fraction of people who pay is actually not that hard for us. And we can do it at any point in time. If at the end of a lesson, I give you one ad versus if I give you two ads, that makes a huge difference in the number of people that pay.

[Bob Safian]

So it's not just that you get extra revenue from having two ads, it's that for me as a user, I'm like, I don't want to listen to the ads or want to watch the

[Luis Von Ahn]

ads and you end up subscribing. Yes. But the thing is Again, we're trying to be a long term business and it does come at a cost because maybe two ads is not that annoying. But at some point, you know, if you're playing 17 ads at the end of a lesson, people are probably just gonna leave.

[Bob Safian]

Particularly for your users who can't afford the premium, right? Correct. You're kind of driving them away.

[Luis Von Ahn]

Correct. So that's why we don't pull that lever. But it is an easy lever to pull. And again, it's not just ads. You can do a lot of things.

[Bob Safian]

Almost every freemium business eventually piles on ads. Netflix did it. YouTube did it. The question isn't whether Duolingo will pull that lever in 2026, as much as how big it can grow before it has to, and what that says about the future of education. We'll talk about that more after the break. Stay with.

[Jeff Berman]

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[Jeff Berman]

There's going to be two types of

[Bob Safian]

companies those are great at AI and those that went out of business because they weren't.

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[Bob Safian]

Before the break, Duolingo's Luis Von Ahn shared his missteps and learnings about AI and why Duolingo is DE emphasizing revenue growth in 2026. Now we dig into the limits of unhinged marketing. What happens when stakeholders don't speak the same language, as Luis puts it, and what not to do. If you want to get hired at Duolingo, let's jump back in. As you're going to try to, like, open up this top of the funnel, really bring. Bring more people in. Does that mean, like, more of the social media stunts that Duolingo is kind of known for? You know, I mean, I'm remembering sort of staging the death of your mascot, the Green Owl duo, last year. But I also saw something your chief marketing officer said, that social output that was 80% unhinged and 20% wholesome, that now is going to become more balanced.

[Luis Von Ahn]

Historically, our social media has been an incredible growth lever. Our mascot has become really popular and to the point where we don't have much control over him. Like you said, he staged his own death. But we really do think that it is important to also convey some things in our marketing that I think historically we just have not because it was actually quite effective. If you go look, it's about as effective as a classroom. That's just not something we have really said a lot in our marketing because we spent a lot of our marketing doing stunts, unhinged things. Having the owl twerking, which has been successful in its own right. We need to thread the needle here to try to continue being fun, but also move a little more towards having a message that is like, hey, you know what?

[Bob Safian]

Duolingo actually really works in this user expansion. Like, how much of the plan is around expanding what you teach? I mean, I've always thought of Duolingo as for languages, but, you know, courses on math and music and chess. Like, why did you add those areas? And sort of is your vision of Duolingo's future to be more expansive?

[Luis Von Ahn]

Yeah, we may not teach everything, but we want to teach the subjects that are meaningful to you that also take a long time to learn. Math is an example. Languages is an example. Music is an example. Chess. Even though it's our newest subject, has gotten the most traction outside of languages.

[Bob Safian]

Interesting.

[Luis Von Ahn]

Languages by far are still the biggest. And languages. The other thing that sometimes people in the United States may not understand is just how big language learning is in the world. There's about 2 billion people in the world learning English. I don't know of a subject, including math, that has as many people learning math. There's about a billion people learning math. So language is the largest thing. Chess is the second largest for now for us. But I believe that over time, math is going to overtake chess. That's my hope at the moment. No numbers support my hope, but that's my hope.

[Bob Safian]

As you're talking, I'm thinking about another digital learning platform, Khan Academy, that rose up alongside Duolingo. I've had Sal Khan, the founder and CEO on the show, also an early AI believer, recently teamed up with Ted to offer a degree in AI skills. Will Duolingo become more like Khan Academy in subject range? I mean, it's almost like the two businesses are converging. Do you and Sal ever talk about that?

[Luis Von Ahn]

We do. I know Sal. We do. I don't know if we're going to exactly converge. Who we are trying to reach in many cases is pretty different. Sal has this incredible videos that explain subjects incredibly well. Our approach is to be more like a mobile game. So, you know, in some sense, they're quite complementary. Khan Academy has been mostly geared towards kind of schools and school usage, et cetera. Whereas where, you know, many schools do use us, but we're, you know, really for the whole population.

[Bob Safian]

I mean, Khan Academy is also a nonprofit. Duolingo is not. You're a publicly traded company worth more than four and a half billion dollars. You went public in 2021. How has your role as CEO changed since taking Duolingo public?

[Luis Von Ahn]

I would say the first couple of years, it didn't change all that much. But I think it has changed more recently, especially when I had to say that we were going to have a different strategy. Now, as a publicly traded company, I have to convince the board, the employees, and public market investors, who I don't have a direct conversation line. To the vast majority of them, they're just people on the Internet. And there's our users, probably the most important constituency, but there's also our employees, also our investors, and they are not really aligned. Maybe in the long term they all are, but certainly in the short term, I mean, users, what they want is to get the entirety of the learning as good as possible and as free. As possible.

[Bob Safian]

Right.

[Luis Von Ahn]

And again, this is a caricature, but investors, you just want us to charge every user as much as we can. And employees are somewhere in the middle. Employees probably want us to give Duolingo entirely for free, but they also want to make a lot of money.

[Bob Safian]

They say that you get the investors you deserve. Right. I mean, if you talk too much about delivering results today, you get a lot of short term investors. And there's that issue of, you know, are you in business to make as much money as possible versus having a sort of more social mission. Is teaching people a conduit to making money, or is making money a conduit to teaching people?

[Luis Von Ahn]

It's a really good question. And I may be an incredible optimist and it may be that I'm wrong, but it is my belief that if you look, in the long term, these two are the same, but not in the short term. I agree. In the short term, you know, it really, it really matters which one you're prioritizing. But I think in the long term, what's going to matter the most and what's going to also make the most money is a company that really is putting the education of the users first. I think that will be the larger company in the long term. Now, can I prove that to you? I can't. But that is my optimistic thinking that in the long term, these two are actually aligned.

[Bob Safian]

How much of the decision to sort of broaden beyond languages and is prompted by, by new AI tools that enable instant live translation across languages. Like, do you worry that people won't be as motivated to learn a language as time goes by?

[Luis Von Ahn]

No, I don't worry about that. So we have two big buckets of users. The first is people who are just hobbyists. And, you know, if they're learning language as a hobby, whether a computer can do it or not doesn't seem to matter to them. It's similar to, by the way, we also teach chess. You know, a computer beat the world chess champion in something like 1997. It turns out humans are just not particularly good at playing chess when it comes to computers, we're just not. But that's still the case. There's millions of people learning chess because it's a hobby. Similarly, languages, you know, a big group of our users is a hobby, and I don't think they're going to change. And then the other huge group of our users are people who are learning English either for a job that they want to get or to come study here in the US or in the uk, et cetera. And in that case, they actually need to learn it themselves. It's an even bigger question, which is some people have said, well, with AI, why do you need to learn anything? I mean, it would be a chaotic society if nobody learned anything. I mean, people still need to learn stuff. So I. I do think that what people are going to learn is probably going to change some, and I don't know exactly how. But again, people still do need to learn stuff, including math. They need to learn math just so that they can learn, you know, logical thinking.

[Bob Safian]

I mean, you've been a professor teaching in the classroom. You've now run duolingo for. For more than a decade. What do you think people misunderstand about learning about teaching? Like, what makes it hard, what turns people off, what turns people on?

[Luis Von Ahn]

In my experience, the hardest thing is keeping people motivated. There's been a technology that teaches any subject really well that has existed for a very long time, which is called a book. A book. You can actually learn almost any subject you want. I mean, you can learn quantum physics by just reading books. You can do that. But it just turns out the vast majority of the human population does not have the stamina to do that. That is just not a thing that they would do. So I think the hard thing is getting people's attention, and I do think it's getting harder and harder because people's attention spans are getting shorter and shorter. I think that is the hardest thing about teaching somebody, keeping them engaged.

[Bob Safian]

And different people can also learn better in different ways, right? I mean, is that part of the challenge?

[Luis Von Ahn]

It is definitely the case that different people do learn in different ways. And we do personalize. Whenever you start a lesson on duolingo, it is personalized to you. But I will say I think that is exaggerated. It is rare that we find changes that only apply for this group of people versus that group of people. You hear these things that are like, oh, no, no, no, no. But people in China are very different. They use apps very differently, or people in whatever, France are very different, etc. It's very rare that you find a feature that works in one country but not in another one. That's very rare. Typically, most people are pretty similar. For example, if you have a progress bar that you're filling up and it's 3/4 filled, pretty much every human will want to fill it to 100%. That is just a universal truth. And there's just. I think there are more universal truths than. There are kind of very specific differences

[Bob Safian]

between People, you are not shy about unconventional ways of approaching things. I was looking at this viral clip of you telling a story that you paid a taxi driver to report on how job candidates treat them during the ride to interviews, which is a particularly

[Luis Von Ahn]

tricky way to learn A little clarification, by the way. I don't know how this got. It wasn't a taxi driver. We would send them like a limo driver. That works for us. And by the way, it's not like I sat there paying this person. All that happened is that at the end of an interview we would go ask just this person, did they treat you nicely? And that it turned out there was signaling that in most cases they were treated nicely. But there were some cases, particularly one case where we were about to make an offer and the person said, no, they really were not very nice and we didn't make an offer. When you're trying to hire somebody, it's usually because there's a hole in the organization that you're trying to fill. We have this internal rule that we'd rather have a hole than an a hole. That is what gave rise to that.

[Bob Safian]

So what's at stake for Duolingo right

[Luis Von Ahn]

now, what we're trying to achieve, especially because of AI, is, you know, what kind of world are we going to have? The type of world that I would like to have is a world where people really are bettering themselves. That is one way in which they find meaning in life, et cetera. Will it be the case that in 10 years we can get a significant fraction of humanity's population, billions of people actually learning something, as opposed to either doom scrolling or just giving up on life? Because AI can do everything. What I'm hoping we can do is to just add meaning to that many people. At the moment we have north of 100 million active users, which is nice. That's nice. Good job, Luis. We got to more than 100 million active users, but that's too small of a fraction of humanity for me to claim victory. I'm hoping that we'll have billions of people learning meaningful things in 10 years.

[Bob Safian]

You're not easy on yourself. I mean, 100 million people, that. That does deserve a pat on the back. Not enough.

[Luis Von Ahn]

Yeah, I mean, look, it's good. If you look at education, it's unheard of to have something that is teaching more than 100 million people willingly, that's kind of unheard of. But still, I just think that there should be a world where really people are spending some amount of their time on the screen doing more meaningful things than, you know, scrolling forever. It's not like I'm against social media companies. I'm not necessarily against them or anything, but like, it seems kind of not all that meaningful to me.

[Bob Safian]

Well, Luis, this was great. Thanks for coming on and talking.

[Luis Von Ahn]

Thank you. Excellent questions.

[Bob Safian]

Luis is an optimist, as he says. His bet is that in the long run, AI will deepen our love of learning, not replace it. I hope he's right. So far, the story is different. Layoffs, hiring freezes, universities pleading with students to write one sentence on their own. But as Luis argues about company values, too, the long term is what matters. We have the agency to impact how the story unfolds on AI from here, if we put in the work the 500 hours or whatever it takes. AI may be fluent in almost any language, but it can't replace the learning we get from doing something the hard way. I'm Bob Saffron. Ian, thanks for listening. Hey, listeners. Bob here. If you listen to Rapid Response on Masters of Scale, you may be missing half the show because every Friday we release a second Rapid Response exclusively in the Rapid Response feed. The guests and topics are just as compelling and timely for from Ford's CEO to NASA's administrator to the lessons from the Devil Wears Prada, it takes about 10 seconds to find. Just search Rapid Response wherever you listen to podcasts and hit follow to make sure you never miss an episode. I hope to see you there. Rapid Response is a Wait. What? Original I'm Bob Safian. Our executive producer is Eve Trow. Our senior producer is Alex Morgan Morris and our associate producer is Masha Makutonina. Mixing and mastering by Aaron Bastinelli and Brian Pugh. Our theme music is by Ryan Holiday. Our head of podcasts is Lital Molad. For more, visit rapidresponseshow.com.