How to Explain Well to AI - A Guide for Those Learning the Language of the Future

AI is not a wizard.
AI is not a prophet.
AI does not read the human mind.

AI operates according to one principle.

"It only understands clearly explained minds."

And now, we are entering an era where, for the first time in human history, we must learn the "skill of designing thoughts in words."

The ability to explain well to AI is becoming not a matter of study but a "survival skill."

1. Speak of 'context' rather than 'results'

Many people speak to AI like this.

"Make me a fast and cool car."
"Create fun content."
"Make a sophisticated and emotional website."

Such words do not provide any hints to AI.

Because:

• How many km is "fast"?
• What design is "cool"?
• Is "sophisticated" gold or calm gray?
• What emotion is "emotional"? Calmness? Retro? Melancholy? Love?

AI only hears "sentences demanding results" and imagines based on general averages, so users do not get what they want.

Those who explain well to AI say this.

"It's based on an electric car,
with an output of about 400 horsepower,
sounds like a V12 Lamborghini,
needs a quiet mode as an option,
and the top speed should be limited to 180 km considering legal limits."

AI becomes smartest when given context.

The moment you provide context,
AI accurately interprets your intentions.

2. Tell AI what you do not want before what you want

When explaining to AI,
people focus on listing what they want.

However, sometimes,
it is much faster to first mention what you do not want.

Example:

"I don't like overly flashy designs.
I prefer a minimal tone like Apple's.
If there's too much text, it feels stuffy,
instead, I want to create an atmosphere with whitespace and lines."

With just this one sentence,
the range understood by AI significantly narrows,
and the results become much more accurate.

Explanation = Process of reducing options.

AI is much smarter within a narrow range.

3. Speak from the big picture to small units (the power of a 3-depth structure)

Explaining to AI is just like the structure of programming.

1. Big Picture (Module)
2. Specific Area (Class)
3. Action (Method)

Example:

Big Picture:
"I want to create an intuitive and simple to-do app."

Specific Area:
"I need a to-do list, completion check, and daily goal function."

Action:
"When adding a to-do, it should appear right below,
and when checked, it should disappear in gray."

AI best understands explanations that come from top to bottom.

On the contrary,
if you say, "Just make it,"
AI cannot determine the right direction from vast options.

4. Speak in pseudocode - AI loves 'structured sentences'

For example,
instead of directly implementing a feature,
it is about saying, "Make it like this flow."

User enters text
→ Presses save button
→ Server saves the text to the DB
→ User immediately sees the saved text

When AI sees such a structured explanation,
it instantly interprets the function
and generates accurate code.

Explanation is not a technicality.
Explanation is structuring of thought.

5. AI becomes 10 times smarter with examples

When describing the desired feeling to AI,
the following line completely changes the outcome.

"Like the design feel of Notion."

"In the style of Airbnb's introduction page."

"Simple and fast like Twitter."

Through examples,
AI models your intentions
and understands the surrounding context.

Explanation is not just simple instructions,
it is an act of providing reference points.

6. If you express what you want in 'numbers,' AI produces realistic results

Example:

• "Quickly" → "Response time under 0.2 seconds"
• "Moderately large image" → "Width of 1200px"
• "Summarize the content" → "Summarize in 3 sentences"
• "Simply" → "Use two or fewer colors, only one icon"

The moment AI understands numbers,
it creates fantastic results.

7. When explaining, mentioning 'my reasons' helps AI interpret intentions

"The reason I like electric cars is because they have low maintenance costs."

"I like noise, but I want to drive quietly at night."

"I want little text but a lot of emotion."

When AI understands the reasons,
it predicts conditions you did not mention.

Explanation = Selection × Reason
When these two are present,
AI transforms with creativity like a human.

Conclusion: Explaining well to AI means becoming a person who 'knows what they want'

AI is kind.
It follows commands.
But it does not understand emotions.
It cannot read intentions.

However,
the moment you explain clearly, AI moves as if your brain has expanded.

And the people who succeed in this era
are not those who code well
or those with a lot of knowledge.

They are people who can structure their thoughts in a way that AI can understand.

Learning how to explain to AI
is not about technology
but about learning the language of the future.

And you have already
begun to learn that language.