Duolingo But for Everything: Does It Actually Exist?

Somewhere around day 200 of a Duolingo streak, the same thought hits most people. This actually works. Five minutes a day taught you more Spanish than two years of high school classes ever did. So why can't you learn this way about anything else?

You search "Duolingo but for everything" and get Duolingo, a handful of flashcard apps, and a few Wikipedia summaries with a quiz stapled on. Nothing that captures what actually made the streak addictive in the first place.

This is a real, well-documented gap, not just a personal frustration. Here's what the model actually requires to work, why it took this long to build, and what genuinely exists in 2026 for people who want it applied to more than one subject.

Morso turns any topic into 5-minute lessons you'll actually finish. Try it free →

Key Takeaways

• Duolingo's streak mechanic works through loss aversion, a well-documented behavioral pattern where losses feel roughly twice as painful as equivalent gains feel good (Kahneman and Tversky, 1979)

• Duolingo's core product remains language learning, and its math and music experiments haven't matched the depth of its language track

• Real gamification requires more than decorative points, it needs immediate feedback, active retrieval, and a reason to return daily, or it doesn't produce the habit

• Building this for general knowledge is a content problem as much as a product problem, since unlike a language, there's no fixed curriculum for "things worth knowing"

Why Does Duolingo's Model Work So Well?

Most apps that try to copy Duolingo copy the surface, a streak counter and some points, without understanding the mechanics underneath.

Three things make the actual model work. First, friction is close to zero. You open the app and you're in a lesson within seconds, no course selection, no 30-minute commitment. Second, feedback is immediate. Every correct answer produces a visible reward, compared to a textbook where the reward might arrive weeks later on an exam. Third, and most powerfully, the streak exploits loss aversion: losses feel roughly twice as painful as an equivalent gain feels good, a pattern formally established by Daniel Kahneman and Amos Tversky in 1979, work that later won Kahneman the Nobel Memorial Prize in Economic Sciences. A 200-day streak stops feeling like an achievement and starts feeling like an asset you're actively protecting.

These three elements together build something most learning products never achieve: a genuine daily habit rather than a one-time course.

Why Doesn't Duolingo Just Cover Everything?

Duolingo has tested math and music courses, but its core strength remains language learning specifically, and that focus is exactly why it's so good at that one thing.

Everything you've wanted to learn that isn't a language, how memory actually works, the psychology behind bad decisions, the history behind current headlines, negotiation, sleep science, isn't a niche interest. These are the topics that come up in real conversations and shape real decisions. Until recently, the only options were long courses most people never finish, or YouTube videos forgotten by the next morning.

What Would "Duolingo for Everything" Actually Need?

If you built this from scratch, a few things would be non-negotiable.

Sessions short enough that "I don't have time" is never a valid excuse, five minutes rather than twenty. Real gamification rather than decorative points, progression that actually changes behavior, not a racing stripe on a minivan. Active recall built into every lesson, since retrieving information from memory, not just rereading it, is what makes it stick. Roediger and Karpicke's landmark 2006 study found students who tested themselves on material retained significantly more of it a week later than students who only reread it, even with identical study time. For the deeper mechanism behind why this works, see active recall: what it is and why it works. Breadth wide enough that whatever you're curious about today has a course waiting, since curiosity doesn't follow a syllabus. And a genuine reason to return daily, since content alone, without the behavioral loop around it, isn't enough.

How Does Morso Compare to Duolingo's Model?

Morso applies the same underlying mechanics Duolingo proved work, and points them at any topic instead of one fixed subject.

Type any topic into Morso, from behavioral economics to the history of a specific conflict, and get a structured course of bite-sized lessons in about 30 seconds, each one explained through analogy that connects the new idea to something you already understand, rather than presenting an isolated fact. Roughly every three lessons, a practice quiz gates your progress, re-testing material from earlier in the course and weighted specifically toward whatever you got wrong the first time, before letting you continue. Gamified with XP, streaks, and a leaderboard, the same loss-aversion mechanic that makes Duolingo's streak work. You can also upload your own PDF, DOC, Markdown, or TXT notes if you already have material rather than starting from a bare topic. Try it free on any topic.

Worth being honest about, the same way this question deserves honesty from any app answering it: Morso doesn't have a grammar syllabus or a beginner-to-advanced language track. If you're learning a language from zero next week, Duolingo remains the right tool for that specific job. Morso is built for everything else.

Why Did This Take So Long to Build?

Duolingo launched in 2012. It's 2026 now, and a genuine equivalent for general knowledge only recently became possible.

Language learning has a structural advantage most people don't think about: the content is fixed. Spanish has a defined vocabulary, defined grammar, and a clear beginner-to-advanced path. Building gamification around that content is hard, but the content itself already exists. General knowledge has no equivalent curriculum. Someone, or something, has to decide what topics matter, how deep to go, and how to structure each one accurately. That's a content-generation problem as much as a product problem, and it's genuinely hard to solve at the scale a "learn anything" app requires without either a massive human content team or a way to generate structured lessons on demand. AI made the second option viable, which is the specific reason this category only became real in the last couple of years.

For more on what active engagement actually requires beyond just testing yourself, see how to study effectively.

What Should You Actually Do?

If you're learning a language, keep using Duolingo. Nothing else matches it for that specific job, and switching away from an established streak resets progress you've already built.

For everything else, curiosity that doesn't have a fixed grammar or vocabulary to drill, add a tool built for topic breadth instead. Pick a topic that genuinely interests you for your first course, not something you feel obligated to learn. Curiosity is what gets you through the first week, and gamification takes over from there. Give it two weeks before judging the habit. The first week runs on willpower. By the second, it's closer to automatic.

The Bottom Line

The search for "Duolingo but for everything" used to return nothing useful. That's no longer true. The underlying model, near-zero friction, immediate feedback, loss-aversion-driven streaks, and active recall, works for any subject, not just language, once the content side of the problem is solved.

Morso applies that same model to any topic you type, with lessons built on analogy and a practice quiz that specifically targets your mistakes as you go. Free to try, and honest about what it isn't: if you're starting a language from zero, Duolingo is still the better first stop.

For a broader list of specific topics worth trying it on, see 100 interesting topics to learn about.

Sources

Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263-291.

Roediger, H. L. and Karpicke, J. D. (2006). Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention. Psychological Science, 17(3), 249-255.