Duolingo vs. the Translation Machines – Will AI Kill Language Learning & If So, When?
How Meta’s big reveal reframes the risk – and why the green owl isn’t dead yet
When I pull up a 5-year price chart of Duolingo, it’s hard not to notice how much of the story depends on where you set the starting point. At one end, you see a stock that has returned 107% – a decent run, outperforming the S&P by around 700 bps. But, if you adjust the timeframe by just a few days (see the chart below), the number drops to ~36%. That's the nature of endpoint sensitivity.
It makes for a great snap sentiment check, because it reminds me how quickly the market’s narrative around a name can swing from “untouchable compounder” (August 2021-May 2025 performance = 277%!) to “overhyped edtech” … and back again.
That’s exactly why Duolingo is back on my radar. By most operating metrics, the business has been firing on all cylinders – DAUs at record highs, revenue growth well into the double digits, free cash flow margins climbing steadily.
Yet the stock has pulled back meaningfully from its highs. That alone doesn’t make a stock interesting. But when the business and the stock diverge, it usually signals a point where deeper work pays off.
“We believe we’re still early in our user growth journey. We’ve delivered innovation while growing profitability—through strong performance across all subscription tiers, continued investment in our core product, and new subjects that help us increase engagement. We remain focused on building for long-term engagement and growth.” - Luis von Ahn, Co-Founder and CEO of Duolingo
For me, the hook came from Meta Connect 2025. Watching the live demo of their AI-powered translation glasses, I couldn’t help but think about the existential bear case I’ve carried for Duolingo for years: what if the very need to learn another language gets eroded away by technology? That’s not the same as competition – it’s problem shrinkage. If AI makes language barriers melt away in real time, then what happens to a company whose entire existence is tied to helping people cross those barriers the old-fashioned way, through practice and study?
The thing is, the Meta Connect demo didn’t quite deliver on that fear. In fact, it may have pushed the threat timeline further into the future. Which is exactly why now feels like a moment worth re-examining Duolingo. Not to dismiss the bear case – far from it. But to test how durable it really is, what the company has built to defend itself, and whether the valuation makes sense once you frame the disruption risk realistically rather than hypothetically.
That’s the journey I want to take you through in this post: start with the default bearish lens I apply to Duolingo, stress-test the assumptions behind it, dig into what Meta’s latest moves actually mean, and then see how the bullish arguments stack up. Along the way, I’ll look at Duolingo’s brand, its data advantage, its optionality beyond language learning, and finally sketch out a few scenarios for how this could play out.
Paying subscribers get access to the entire post (around 5,500 words) featuring:
My default bearish filter – applying Bill Ackman’s principle of avoiding businesses exposed to uncontrollable extrinsic risks; why language learning feels like a fragile beachhead; parallels to Tesla’s robotaxi pitch and the risk of “problem erosion” rather than competition.
Meta Connect 2025 as a reality check – what Meta actually showed with its translation demo, what the “hiccups” signal Duolingo investors, and how user anecdotes (e.g. Mostly Borrowed Ideas) confirm reliability challenges; why the timeline for disruption likely shifted out.
What true disruption would require – four pillars; plus the human and market frictions of privacy, cost, comfort, and social acceptance.
The case for Duolingo – founder-operator intensity, a brand that has become synonymous with its category, behavior design that engineers habit formation, proprietary data at scale, monetization lanes (subscriptions, ads, English Test, future adjacencies), and why the market may be overestimating disruption.
Proprietary data in an AI world – how Duolingo’s granular learning data could become/remain a moat and a growth engine; potential applications
Scenario analysis – probabilistic timelines for when AR-driven translation could hit mainstream
Before we dive into the analysis …
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