The Owl Who Cried AI: From Slop to Flop and Back Again

Not long ago, Duolingo joined the growing list of tech companies chanting the new gospel: AI-first. Out came a memo, full of visionary phrasing and vague promises about scale, innovation, and how AI was going to unlock “the future of learning."

(Translation: we’re firing the humans but in a way that sounds exciting.)

The owl had spoken. The future was here.

And it spoke fluent buzzword.

What followed was a familiar plotline: cautious applause from investors, quiet dread from internal Slack channels, and a sinking feeling for the creatives, educators, and contractors who’d helped build the platform into what it was warm, weird, and widely loved.

The same people who gave Duolingo its voice a brand that somehow blended Sesame Street with mild emotional blackmail were now left wondering if that voice was being handed off to a large language model that thinks “¿Dónde está el baño?” is peak comedy.

“The humans are being deprecated. But don’t worry, the owl is still watching.”

AI Slop Enters the Chat

The results? Mixed at best. AI-generated content filled gaps, sure but also widened a few. What once felt playful and oddly personal began to feel templated. Lessons lost their spark. Social posts read like interns trying too hard, only the intern was an algorithm fed 30,000 Reddit comments and a dream.

Behind the scenes, Duolingo boasted about building 100 courses in under a year a staggering feat compared to the ten it took to build the first hundred.

Think of it like assembling 100 IKEA bookshelves in a weekend: technically impressive, but don’t lean on them too hard.

A hundred new courses in under a year. Quantity flex. Quality TBD.

Because for those actually trying to learn a language, speed doesn’t always mean progress. Sometimes it just means more walls to walk into before you find the door.

And as for the voice that made Duolingo famous the charmingly unhinged, slightly threatening owl? It didn’t translate well to AI. Instead of motivating guilt trips and inside jokes, we got safe sentences and sanitised tone. The same feeling you get when a fast food chain tweets something "relatable." It’s trying you can tell but you can also tell someone deleted all the weird bits in revision.

"It’s giving ‘How do you do, fellow kids?’ energy. But in Duolingo green."

Enter Corporate Clarity Guy

Before the walk-back, there was the memo.

Leaked to the press and later confirmed, it laid out a five-point plan for how Duolingo would “align the business around AI.” On paper, it sounded visionary. In practice, it read like a slow-motion goodbye to the human scaffolding that made the app work.

Duolingo CEO Luis von Ahn outlined five “constructive constraints”:

  • "We'll gradually stop using contractors to do work that AI can handle"

  • "AI use will be part of what we look for in hiring"

  • "AI use will be part of what we evaluate in performance reviews"

  • "Headcount will only be approved if a team can’t automate more of its workload"

  • "Most functions will have specific initiatives to fundamentally change how they work"

If that sounds less like a strategy and more like an existential performance review for anyone with a salary you’re not wrong.

This isn’t an enhancement strategy. It’s a soft restructuring plan.

"The future is bright. Unless you're human."

Then came the video.

A kind of non-apology wrapped in CEO sincerity equal parts reassurance and reputation control. Von Ahn, speaking directly to camera, reframed the whole thing:

“One of the most important things leaders can do is provide clarity. When I released my AI memo… I didn’t do that well.”

He goes on to say that AI won’t replace workers, that Duolingo is still hiring, and that employees will be “empowered” to learn and adapt. He reassures the audience that the owl is still here to help not automate you out of relevance.

“I don’t know exactly what’s going to happen with AI… but the sooner we learn how to use it responsibly, the better off we will be.”

It’s calm. Measured. Thoughtful.

And it lands about six PowerPoint slides away from the original plan that said headcount would only be granted if a team couldn’t automate more of their work.

“The owl says AI is here to help. But if you squint, you can still see the memo behind the smile.”

Your AI usage streak is in danger. Let’s fix that before it affects your performance review 💚

You Can’t Walk Back the Hype (and Google’s Breathing Down Your Neck)

There’s a trap in calling yourself “AI-first.” You’re not just experimenting you’re committing. You’re placing a bet, publicly, that AI is not only the future but your future. And when that doesn’t land? When the vibes go missing, the lessons feel hollow, and your users start asking why Duo now sounds like a customer support bot for a smart fridge?

You can’t just hit undo. You need a narrative detour. You need Clarity Guy with a whiteboard explaining that “AI-first” really meant “AI-curious but people-powered.”

But behind that PR spin was something else: Google. Specifically, Google Translate now increasingly dabbling in interactive learning. It doesn’t take a strategist to see the impending doom: a tech giant with a near-endless war chest and one of the largest translation datasets on Earth suddenly deciding it wants your users.

Duolingo wasn’t just chasing innovation. It was racing the clock. If they didn’t stake their claim now, they risked becoming the quirky owl-shaped startup that got eaten by a search bar.

"I used to teach. Now I prompt-engineer."

Language Is Human (And I'm Living Proof)

Language is weird. It’s full of nuance, timing, sarcasm, and culture. You don’t just learn a language you absorb it. Through mistakes, repetition, and the occasional stranger correcting your grammar mid-sentence with a kind smile or a look of sheer pity.

AI can generate sentences. Hundreds, even. But it doesn’t know what it’s teaching. It doesn’t get why “I want to eat, grandma” is different from “I want to eat grandma.” It doesn’t know how to gently motivate someone who’s burnt out or how to slip a joke into just the right sentence to make it stick.

And users are starting to notice:

“I’m a paid Super Duolingo customer with a 1463-day streak,” wrote one user on LinkedIn. “But they gutted the Esperanto course and removed the humans who maintained it. Now it’s dying on the vine.”

Another flagged the Spanish-via-Telugu course: “The content is ungrammatical and frankly misleading. Please don’t fire your human translators.”

I can relate. As someone learning Spanish with a Peruvian partner, Duolingo helped me build the foundation the first 2,000 words I needed to communicate, argue, laugh, and survive awkward family dinners. That wasn’t magic. It was consistency. Gentle repetition. Human-tested content that understood how brains actually work when learning a second language: lazily.

But vocabulary is the easy part. The real wall is listening catching full-speed sentences in real-world context, no subtitles, no mercy. Unless you’re learning Japanese (where every syllable is lovingly pronounced like a stage actor doing warmups), most languages hit your ears like a blender on fast-forward.

That’s why the Duolingo podcasts were such a gift. Real voices. Real pacing. Real stories. They weren’t just content they were immersion. And they taught me far more than any AI-generated multiple-choice quiz ever could.

"The best way to learn a language? Forget you're learning it."

Your brain will default to what it knows unless you force it not to. That’s why I had to delete Google Translate too tempting. It became a crutch, not a tool. Karaoke in Spanish helped more than most apps ever did. So did being stranded in a Spanish town with no help, no Wi-Fi, and no choice but to figure it out.

That’s what language learning is. It’s immersion, struggle, and sometimes embarrassment not a five-minute “Learn Spanish with AI!” PDF and a pat on the head.

And here’s the real danger: if we keep pushing AI-first language solutions, we may stop learning altogether. We’ll just outsource it.

Why study, when your voice assistant can whisper the answer into your ear in real time?

Why wrestle with conjugations, when your AI agent is already replying to theirs?

That’s not fluency. That’s just automation dressed up as connection.

Because when a user gets an answer marked wrong even when it’s clearly right that’s not just a glitch. That’s a failure of trust. And once people lose confidence in your app as a teacher, it doesn’t matter how fast you can scale.

You’ve taught them the wrong lesson.

“Looks like you missed your Spanish practice... again. But it’s okay. The AI model’s improving without you.”

The Owl’s Redemption Arc

So here we are. The owl blinked. The memo got massaged. The people are back mostly. The company line now reads somewhere between “AI will enhance us” and “please ignore the previous memo.”

“I’m not mad. I’m just disappointed you didn’t train the model today.”

And if you’ve opened the app lately, you’ll know: they’re hustling. That Super Duolingo free trial offer? It’s not a suggestion anymore. It’s a recurring dream. You open the app to review a verb tense and within seconds, you’re being asked to upgrade like you’ve walked into a very polite hostage situation.

Upgrade to Super Duolingo™ to keep one human editor employed.

And honestly? Let them. Someone has to pay the AI bill. GPT-4 isn’t cheap, and Corporate Clarity Guy’s whiteboards don’t fund themselves.

Because in the end, Duolingo taught us a lesson far more important than how to say “Where is the bathroom?” in Spanish.

The future might be built with AI.
But the parts that stick the ones we laugh at, learn from, and remember those are still human.

And maybe that’s the real lesson.

Not just how to say “Where is the bathroom?”

But when to pause, ask why, and remember that language like learning works best when it’s a little messy, a little human, and absolutely not automated end-to-end.

“You missed your Spanish lesson. But don’t worry the model’s fine.
You’re the one we’re losing.”
The Owl, softly, from the push notification abyss

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Written by

Daniel Philip Johnson
Daniel Philip Johnson

Daniel Philip Johnson | Fullstack Developer | E-commerce & Fintech Specialist | React, Tailwind, TypeScript | Node.js, Golang, Django REST Hi there! I'm Daniel Philip Johnson, a passionate Fullstack Developer with 4 years of experience specializing in e-commerce and recently diving into the fintech space. I thrive on building intuitive and responsive user interfaces using React, Tailwind CSS, SASS/SCSS, and TypeScript, ensuring seamless and engaging user experiences. On the backend, I leverage technologies like Node.js, Golang, and Django REST to develop robust and scalable APIs that power modern web applications. My journey has equipped me with a versatile skill set, allowing me to navigate complex projects from concept to deployment with ease. When I'm not coding, I enjoy nurturing my bonsai collection, sharing my knowledge through tutorials, writing about the latest trends in web development, and exploring new technologies to stay ahead in this ever-evolving field.