Duolingo Today is Like Amazon 20 Years Ago.

In the abstract, Duolingo’s business is about producing content and tweaking it to optimise user lifetime value. This is true all the way from the content they produce to acquire new customers (such as the recent market campaign, in which Duolingo’s owl faked his own death), to the content they produce to engage users across tiers. AI fundamentally permeates this stack and makes its iteration exponentially more efficient. As time goes by, the stack generates additional data which then speeds up the iteration even further.

For instance, improving Duolingo’s monetisation is about figuring out what content to put into what tier in order to maximise the value to price ratio. That’s essentially a function of running many A/B tests and finally implementing the modifications that optimise outcomes. Enhancing user engagement throughout various courses and across educational verticals (from languages, to math, music and chess currently) is fundamentally the same.

For example, see Duolingo CFO Matt Skarupa’s remarks on why they decided to launch Duolingo Max:

"We are optimizing for platform LTV. And so when we run our A/B tests, we have to take into account, are these Max subs incremental or not in figuring out the overall impact on platform LTV.

And that’s why we launched Max is because we ran enough of the experiment to figure out that they were incremental.

There [was] enough incrementality to it that it was platform LTV positive. And we still think that’s true. And in fact, we think it will become more true over time."

Hence, I believe that Duolingo’s earning power will broadly track the evolution of AI models going forward. The business will get bigger and stronger as AI models get better. As I explain in this video, Duolingo is what I call a Singularity Scaler.