Luis, you told your team that nobody gets hired unless it improves AI can do the work first. Can you tell me how you actually track that as a founder?
Our goal here is to use AI to benefit our users. Internally we have this golden rule: we're only going to use AI to benefit our learners. Some people may imagine that some companies may be firing people and having AI do their job. That's not what we're doing whatsoever. Our team has gotten significantly better at using AI over the last couple of years and has allowed us to do a lot more. It has allowed us to put out a lot more content, a lot more learning content, etc. We as a management team are not necessarily tracking like, 'Oh, are you doing something that AI can do or not?' We're just really trying to tell everyone to try to be as efficient as possible with AI, and our employees are doing that.
And can you give me some of the best examples from the team for someone who's watching this and they're like, 'Okay, my manager tells me to start using AI but I've no idea how to do it.' Do you have like best case examples?
It depends on what your job role is. I think most of our engineers have basically really changed their workflows. They're using AI coding tools. A lot of our product managers, what they've decided to do is using AI to make prototypes of things. So the product manager may not be implementing the thing in the full production app, but rather than coming to us with a written document, they come with a prototype now. That's way better because it allows for much better decision making. So if somebody comes to me with a written proposal and says, 'I'm going to do a way to teach Spanish better,' it's hard for me to know what that actually means. But if they just show me the prototype and I can see that it really does seem to teach Spanish better, it's much easier to give approval to that type of thing. So it depends a lot on the role.
Do you give them any guidance like, 'Okay, instead of doing this, do that next time' or how how do they even find out they can do these things with AI?
We try to do some things in the whole company to try to, you know, we had for example a few months ago we had a day where everybody in the company had to vibe code something. Not just engineers, every person, people from HR, people from the finance team, everybody had to vibe code something. So, everybody could see the power of it. We also have a lot of documentation about best practices. But, generally, people here in Duolingo are pretty smart. They're always finding new things. And I think what happens is rather than management telling them what to do, they tell each other what to do. There We have a lot of Slack channels.
I smile and laugh because as he's saying that he implements to where his workforce has to take a day of doing vibe coding, I think of all the parents who do not realize that your child is in the bedroom vibe coding. While they are on Minecraft and they are setting up these extravagant worlds, they are vibe coding. Talk to your kid about it. Ask them, what do they know about vibe coding? And drop it in the comments.
You know, one of them is called best AI practices. And so, people are just saying stuff. We also have another one that's called AI fails, which is all the times all the things that people try. It is an incredible thing, very empowering for people. They're like, 'Oh my god, I made'—usually they're very small apps, but it's like 'I made an app.' One of the things that has happened inside this company is everybody now has made their own dashboard.
That's super impressive. Is that how you track AI proficiency? Because now it's part of performance reviews, right, at Duolingo?
For a while, it was part of performance reviews. We just—I don't know if you know what a KPI is, it's a key performance indicator—decided not to do that and I'll tell you why. I sent a memo to the company that said, you know, part of your performance review is going to be usage of AI. And we found that people were—I don't know if they were doing that—but they were kind of asking like, 'Do you just want us to use AI for AI's sake?' And at the end, we backtracked and we said, 'No, look, the most important thing in your performance is that you are doing, you know, whatever your job is as well as possible. A lot of times, AI can help you with that, but if it can't, I'm not going to force you to do that.' So, I think we backtracked from that because it really felt like rather than being held accountable for the actual outcome, we're trying to just push something that in some cases did not fit.
And do you have a specific example where somebody did something in a week without AI and then with AI they kind of multiplied the output?
We now teach chess on Duolingo, so you know, for a long time we only taught languages, now we teach a few other things. Chess is the latest course we added. This course got started by two people. Neither of whom knew chess. Neither of whom knew how to program. They basically live coded the first prototype of it. Now, the final version that is actually in the app, of course we put some engineers in there etc. but they really got very far. In a span of about 6 months they created the whole curriculum for chess. They created a prototype of the app all entirely with AI and again, these people did not know any chess.
And whose idea was that? Was it their idea?
It was their idea to do that. They also—it was well, they're the ones who wanted to add chess. By the way, they came to me a year earlier to say we want to add chess. I said I don't want to add chess because it's just a game and we're an education app. But what happened was that a few months later I talked to the Minister of Education of my country, I'm from Guatemala, and she said to me, 'Our education system, our public education system in Guatemala is so broken that I'm considering sending every student a chess board so that at least they'll learn logical thinking.' And when she said that to me, I thought, 'Oh, wow, okay, this is actually yes.' So then this is when I told him, 'Okay, you can add the chess course.' But I said to them, 'But I don't have any engineers to give you, so go ahead.' And they they figured it out. 6 months, right? About 6 months, yeah.
