AI tutors are solving the wrong problem

Your 10-year-old stares at their math homework, pencil hovering over a word problem about trains traveling at different speeds. They know they need help, but can't quite articulate what they don't understand. Is it the concept of relative velocity? The way the problem is worded? Or something more fundamental about how distance, time, and speed relate?

Meanwhile, across the country, an AI tutor waits patiently for the perfect question that would unlock the perfect explanation.

This is the central tension in how we're building educational technology: we keep trying to automate teaching when what students actually need is help learning.

The seductive promise of AI teachers

Everyone's building AI tutors with the same pitch: "Ask me anything, I'll teach you." The market opportunity is massive - $20 billion by 2027 - and the promise feels revolutionary. Finally, every child could have access to infinite, personalized instruction.

But watch a real kid try to use these tools. They type "I don't get this" and receive a lengthy explanation that somehow misses exactly what's confusing them. Or they ask for help with homework and get a generic lesson that doesn't connect to what they're supposed to be learning.

The fundamental issue isn't the quality of the AI's explanations. It's that we're optimizing for the wrong part of the learning process.

Learning isn't a consumption problem

Here's what we get wrong: we treat learning like information delivery. Student has question, AI provides answer. But learning happens when students wrestle with ideas, make connections, and build understanding through practice and feedback.

The bottleneck in education isn't access to explanations. It's the gap between "I sort of understand this" and "I can actually do this." It's the difference between recognizing a concept and being able to apply it in new situations.

What actually needs automating

Instead of automating teaching, we should be automating the scaffolding that helps students learn independently:

• Practice generation: Taking any material and creating relevant exercises at the right difficulty level
• Progress tracking: Understanding what a student actually knows vs. what they think they know
• Feedback loops: Providing immediate, specific responses to student work
• Metacognitive support: Helping students understand their own learning process

This isn't about replacing teachers. It's about giving students tools that work when teachers aren't available - which is most of the time they're actually learning.

The real opportunity

The most exciting educational technology doesn't try to be a teacher. It amplifies what students already do: take notes, practice problems, test their understanding, get feedback on their work.

When we build tools that enhance these natural learning behaviors, we create something genuinely useful. Students can learn from their own materials, practice at their own pace, and get support that actually matches where they are and what they need.

That's the technology that will actually change education: not artificial teachers, but authentic learning support.