Learn to understand the world in your own words, not memorize others'

Imagine a person who has never been to school.

They don't know what electrical resistance, inflation, DNS, photosynthesis, or compound interest are. They don't know most of the words educated people use to describe the world around them.

But that doesn't mean they don't understand anything.

They see that wet firewood burns worse than dry. They know that some plants grow better in the shade, while others thrive in the sun. They notice that a piece of metal left in the sun gets hot faster than wood. They can read another person's mood from their face. They can predict rain from the clouds.

They already have a massive mental model of the world.

It's just that many parts of this model aren't called the same things they are in books.

And some aren't called anything at all.

That is completely normal.

In fact, sometimes it's a very good starting point for learning.

You can understand things whose names you don't know

Imagine a child who has figured out a simple thing.

If you push an empty cart, it speeds up quickly. If you load it with stones, pushing it becomes harder.

They can observe this many times. They can learn to predict quite well what will happen with different carts. They might even come up with their own explanation.

At the same time, they don't know the words "mass," "acceleration," or "inertia."

Does this mean that before learning these words, they understood nothing?

Of course not.

Understanding had already begun to emerge.

Later, someone will tell them:

— This thing you noticed is called this.

And the new word will connect to the already existing picture.

This is very different from the reverse order:

— Memorize the word. Memorize the definition. Memorize the formula. Someday later, you'll understand what it all means.

This is precisely how people very often learn.

Words are necessary, but words are not yet understanding

Humanity came up with a huge number of terms for a reason.

They allow us to communicate quickly.

Instead of explaining a phenomenon at length every time, we give it a name. People who already know that name understand what is being discussed.

This is like packaging.

A single short word sometimes conceals a massive structure.

The problem starts when a person receives the package, but inside there is nothing for them yet.

They memorize:

X is Y.

Then they are asked:

What is X?

They answer:

Y.

The exam is passed.

But if you show them a real situation where X is happening, they might not recognize it at all.

This is a very common illusion of knowledge.

We learned to correctly pronounce other people's words and decided we understood other people's thoughts.

Every person has their own internal language

When we understand something, we rarely store it in our heads as exact text from a book.

We adapt the information to fit ourselves.

One person remembers an image.

Another remembers a story.

A third pictures movement.

A fourth connects the new with an event from their own life.

A fifth invents a completely absurd name that only they understand.

And this can work wonderfully.

Suppose a person is figuring out an unfamiliar mechanism and mentally calls one part "the pusher," another "the trap," and a third "the gate."

An expert would say:

— Actually, they are called completely differently.

But if the person, using their "pusher," "trap," and "gate," correctly understands how the mechanism works, is able to predict its behavior and find a malfunction, then their internal names are doing their job.

Later, they will find the real terms useful.

Not to replace their understanding with them.

But to connect their understanding with the understanding of other people.

We are constantly packing and unpacking information

Humans are actually remarkably good at this.

We can read several pages and a year later remember one short thought.

At first glance, most of the information is lost.

But sometimes it's enough to remember that thought—and examples, connections, conclusions, and images begin to return with it.

Everyone has such internal designations.

To another person, they might mean absolutely nothing.

To us, they can conceal a huge piece of our world.

You can think of this as a kind of encryption.

We receive information from the outside, break it down, mix it with what we already know, discard some of the details, create our own images and designations, and save the result in a convenient format for ourselves.

And when we need it again, we unpack it back.

This is why two people can read the same book and take away completely different things from it.

They didn't just save different pieces of text.

They integrated what they read into two different worlds.

Good learning doesn't start with the right words

Imagine a person who saw a strange thing in their field.

On one side of the field, plants grow well, but on the other, they grow poorly.

They want to understand why.

They might try to figure out first how to ask the question "correctly."

Read the internet. Encounter unfamiliar words. Try to understand soil composition, fertilizers, acidity, moisture, plant diseases, and dozens of other things.

And then write a clever question, half the words of which they themselves barely understand.

But why?

You can start like this:

Plants grow well here, but twenty meters away they grow poorly. The soil there is a slightly different color. After rain, it stays wet here for a long time, but over there it dries out quickly. I don't know if this matters or not. Help me understand what's going on.

This is a wonderful question.

It contains no correct terms.

Instead, it contains what the person actually knows.

And what they don't know.

Don't try to sound smarter in front of AI

This is one of the strangest habits we have carried over into the new era.

People try to learn how to "talk correctly to artificial intelligence."

They look for ideal prompts. They add special words. They ask AI to "act as an expert." They copy massive instructions.

Sometimes this is useful.

But for an ordinary person in an ordinary conversation, all of this is often completely unnecessary.

If you don't know how to formulate a question properly, you can write just that:

I don't even know what this is properly called. Let me explain what is happening.

And explain it.

Or:

I don't understand anything about this. I want to get this kind of result. Help me figure out first what I actually need to learn.

This is more honest and often more useful than a very clever question.

Because a clever question might contain your mistake.

Sometimes a person asks about something completely different from what they want

Imagine the director of a small company.

They ask:

How fast can I learn to make websites? What do I need for this? I don't understand anything about it yet.

You could create an excellent plan for them.

First one thing. Then another. Then a third.

It will turn out to be dozens of topics and a year of study.

But first, it's more useful to ask:

Why do you need to learn to make websites?

And it turns out:

Well, I don't need to become a programmer. The company has an old website. I want to replace it with a new one.

This is a completely different task.

Perhaps today there are tools where you can simply describe in words what kind of website you need, and they will do most of the work themselves.

Then the director doesn't need to spend a year studying web development.

They only need to figure out a few things that will actually be needed to solve their problem.

They were asking about knowledge.

But actually, they wanted a result.

This happens all the time.

We look for a solution among the methods we already know.

Therefore, a good question to AI often starts not with:

How do I make X?

but with:

I want to get this result. I think I need to do X for this. But maybe there is an easier way. What do you think?

The difference is huge.

Don't force yourself to understand an answer in a foreign language

There is also the flip side.

Suppose you asked a simple question, and the AI replied:

The cause may be the low water-retention capacity of the soil associated with its granulometric composition.

And you didn't understand anything.

Don't reread the sentence five times.

Don't open four more pages to figure out every new word.

Say:

I don't understand these words. Explain it simpler.

Or:

Explain it using my example.

Or:

I understood you like this: this dirt simply holds water worse, which is why it dries out faster. Did I understand correctly?

The last option is especially useful.

You didn't just ask for another block of text.

You tried to reassemble what you heard in your own words.

Now the AI can reply:

Yes. For a start, this understanding is enough. But there is one important detail...

And gradually, the two sides begin to understand each other.

Didn't understand — say "didn't understand"

This seems obvious.

Habitually, however, a multitude of people behave in an entirely different manner.

If a specialist uses an unfamiliar word, a person may feel awkward admitting they don't know it.

If a book is written complexly, a person thinks the problem is with them.

If an explanation is unclear, they try to memorize it at least in that form.

With AI, all of this makes almost no sense.

It won't get bored explaining the same thing to you ten times.

You can say:

Too complicated.

I got lost after the second step.

Don't use those words for now.

Give another example.

Explain it like I'm a person who knows nothing about this at all.

I understood it like this. Where did I go wrong?

And why does this happen?

What if we do the opposite?

What will change then?

This exact kind of conversation much more frequently leads to understanding than trying to silently swallow a ready-made explanation.

Test your mental model, not your memory

There is a simple way to check if understanding has started to emerge.

Try changing the situation.

If you were explained why a certain phenomenon occurs, ask yourself:

What happens if I increase this?

What if I remove this?

What if I swap them?

Where else should something similar happen?

Can I give my own example?

If you can use your mental model and get sensible answers from it, it means something greater than a memorized phrase has appeared inside.

If everything falls apart without the source text, you may have simply memorized the text for now.

That is also normal.

It just means learning is not finished yet.

Imagination is more important than it seems

To understand a new thing, it is helpful not only to read about it.

Try to see it in your head.

Run it through.

Take it apart.

Put it back together.

Imagine a different variant.

Invent an impossible situation and see where your model breaks.

It doesn't matter how strange your internal images are.

They are meant primarily for you.

If it's convenient for you to imagine electricity as water in pipes — start with water in pipes.

When this picture stops working, a concrete question will arise:

Why is my analogy wrong here anymore?

And right then, the next piece of knowledge will answer a real problem inside your model, rather than just being added to a list of things you're supposed to know.

It's better to learn a term when you already understand why you need it

Imagine that after a long conversation, you finally understood a certain phenomenon.

Now it's useful to ask:

What is this usually called?

At this moment, the new word gets a place.

You already have an internal structure to which you can attach it.

And the term becomes extremely useful.

With it, you can search for books.

Read articles.

Talk to specialists.

Find videos.

Compare your understanding with the accumulated knowledge of other people.

In other words, conventional terms should not be rejected.

Quite the opposite.

They are one of humanity's most important inventions.

It's just that you don't always need to start with them.

First:

I see this. It seems to me it works roughly like this.

Then:

What do others call this?

Fancy words are especially dangerous where you know nothing

If you already understand a field well, professional language saves an enormous amount of time.

But in a completely new field, it sometimes does the opposite.

Every unfamiliar word requires another explanation.

The explanation introduces three more unfamiliar words.

Within a few minutes, the original simple question disappears under a pile of terms.

This is especially visible on the internet today.

Around almost any simple human task, there exist specialists, products, services, advertisements, articles, and thousands of new names.

A person wants:

For clients to stop asking the same thing every day.

And the internet answers them with words:

chatbot, CRM, workflow automation, knowledge base, RAG, omnichannel support, AI agent, integration...

The person feels like their problem is incredibly complex.

Although the problem itself remained the same:

People ask the same questions. I want to be able to answer them automatically.

You have to start from here.

The internet knows many more words than you need to know

This used to be a serious problem.

To find information, you often first had to find out what what you were looking for was called.

Don't know the right word — don't know what to type in the search.

Don't know the name of the technology — don't find the technology.

Don't know the professional language — it's hard to enter the professional field.

A vicious circle arose:

To find knowledge, I already need to possess a little of this knowledge.

For the first time, AI allows us to break this circle in many cases.

Now you can start not with the name.

You can start with a description.

I have this kind of thing.

It behaves like this.

I want this to happen.

I tried this.

It didn't work.

I don't know what all this is properly called.

This may already be enough to start moving.

Therefore, don't learn to write ideal questions

Learn to honestly describe your state.

What do you see?

What do you already understand?

What are you doubting?

What have you tried?

What do you want to get?

Why do you need this?

If you already have a proposed solution, it's useful to mention that too:

I'm thinking of doing it this way, but I'm not sure if I'm even heading in the right direction.

This gives the interlocutor the opportunity not only to improve your plan, but also to suggest a completely different one.

Sometimes the best answer to the question:

How to learn X faster?

will be:

You might not need to learn X at all.

And this can save months or years.

And don't learn to memorize ideal answers

The same rule applies to answers.

Don't ask yourself:

Will I be able to repeat this?

Better ask:

Can I explain this to myself?

Can I say this simpler?

Can I give my own example?

Can I use this thought in another situation?

What in it is still unclear to me?

If you can't — keep the conversation going.

You don't have to move on just because the answer text has ended.

Your wrong words can be right for you

Sometimes a person thinks:

I understand, but I'm explaining it in some kind of clumsy way.

This is not necessarily a problem.

Let it be clumsy for now.

Let your mental model be called whatever.

The main thing is that you can use it.

Over time, you will encounter more precise words. Somewhere you'll spot a mistake. Somewhere you'll replace an old picture with a new one. Somewhere you'll realize that specialists separate into two things what you considered one. And somewhere, conversely, you'll discover that five complex names conceal one simple idea.

Your internal language will change along with your understanding.

That's how it should be.

For the first time, we have an interlocutor who can adapt to our language

Throughout almost all of history, humans had to do the opposite.

To read a scientific book, one had to master its language.

To work with a computer — the computer's language.

To use a program — understand its interface.

To find information — learn how to search correctly.

To talk to a specialist — master their terms at least a little bit.

This was inevitable.

A book cannot ask:

What exactly do you not understand here?

A search bar couldn't converse with you for a long time, gradually figuring out what you were even trying to find.

An ordinary computer program didn't understand the phrase:

I don't know what this is called, but I want roughly like this.

Now that opportunity has appeared.

It is far from ideal yet. AI makes mistakes. It can misunderstand you. It can confidently tell untruths. It can suggest a bad solution.

Therefore, you also need to talk with it, argue, check, and clarify.

But the capability itself is new and very important:

you no longer have to learn the system's language first to start talking to it.

Start with yourself

When you want to learn something new, don't think first:

What is the correct name for my problem?

Start with:

What is happening to me?

What do I see?

What don't I understand?

What do I want to achieve?

Tell it in your own words.

If you receive an incomprehensible answer — don't try to immediately master its language.

Bring the conversation back:

I didn't understand. Say it simpler.

Explain it using my example.

I understood it like this. Is that correct?

Build your mental model.

Play with it.

Try applying it to another situation.

Find the place where it stops working.

And only then gradually connect it to the vast world of knowledge that humanity has already created.

Learn names.

Read books.

Study definitions.

Master professional language if you really need it.

But don't confuse this language with understanding itself.

Words help people share thoughts. They do not have to be the material from which your thoughts are built.

Therefore, the next time you encounter a completely unfamiliar topic, don't be afraid that you don't know the right words.

Start with the ones you already have.

Learn to understand the world in your own words, not memorize others'.