Learning has always been hard, especially as we grow older. This difficulty comes from effort, which we often confuse with pain. It’s hard to internalize new concepts and deal with the mental load and the frustration, but that effort is usually part of learning.

Lately we’ve found an easy way around that resistance. We no longer need to try over and over to reach the solution, or review the solution in detail to see what we’re missing; language models take care of lightening that challenge. What the calculator once was, an agent is now, with the difference that the calculator did the math, but the reasoning was still ours. The agent promises to do both.

We have feared that technology would affect our intelligence ever since tools have existed. And I don’t want us to fear agents. On the contrary, used the right way they can speed up learning. AI took away the friction that used to come free with learning. Now we have to seek it out on purpose. The good news is that AI itself can help us, if we ask it for questions instead of answers.

The value of mistakes

Learning happens in the struggle to solve a problem, getting it wrong and trying again. Our brain predicts and looks for patterns by instinct. It does so with fast thinking, the intuitive kind, the kind that doesn’t ask permission. To activate slow thinking, the deliberate kind, we need to stop assuming our model is the right one. Get it wrong. This forces us to stop and think seriously.

This has a name: desirable difficulties. They make studying slower and more uncomfortable, but what we learn lasts longer. Something similar happens with what we generate ourselves. We remember it better than what we only read, even if our first attempt is wrong. Mind you, afterwards you have to check the correct answer. Otherwise, the mistake stays with us.

Beware of the illusion of competence. We read something, understand it effortlessly and think we already know it. Until the test comes and we can’t explain it. Rereading your notes feels productive, but almost never is.

In practice, this translates into three habits:

1. Get it wrong first. Before starting a topic, a class or a tutorial, try to answer without knowing. You’ll fail, and that’s what gives the theory the weight of an alarm bell.
2. Don’t reread, explain. After reading, close the material and explain what you understood in your own words, out loud, like you’d explain it to a five-year-old. Wherever you get stuck is the path to follow.
3. Answer before looking. When you test yourself, always write down what you think the answer is before seeing the correct one.

Learning should feel clumsy. Clumsier than doing it with your feet.

Using AI to learn

These practices take discipline, and discipline is hard when the answer is one message away. While AI can be what blocks us, it can also be the answer. An AI that answers takes the effort away from us, whereas an AI that asks gives it back.

We can learn from many sources or from a single tutor. Many sources give more perspectives, but they scatter our attention and force us to find material, organize it and verify it. An AI tutor can gather those perspectives and hand them to us in one place. That way the friction leaves the logistics of studying and stays where it belongs: in the moment of learning.

A cycle that works:

1. Diagnosis. Ask the agent to quiz you until it finds where what you know ends.
2. Material. With that, have it generate study material adjusted to your level: not so easy that you get bored, not so hard that you give up.
3. Test. Have it test you, and you answer before seeing the solution.
4. Repeat. If you fail, go back to the material. If you get it right, move on to the next topic.

This way we can use an agent as a private tutor and aim the difficulty at the right spot.

Closing

For centuries, learning hurt without anyone asking for it. Now the effort is optional and, like almost everything optional, it’s very easy to skip.

AI can give us all the answers. The hard part is asking it for the questions. So the next time you open a chat to understand something, do the counterintuitive thing: ask it to test you, get it wrong with confidence and explain the topic to it as if it were a five-year-old.

Let’s not outsource our critical thinking. And if learning feels clumsy, you’re doing fine.