An Age When Intuition, Not Knowledge, Becomes the Competitive Edge

The sweltering days have continued without relief.

Even after night falls, the heat gathered by the city throughout the day refuses to fade. When I open the window, humidity and hot air rush into the room together. When I close it, the quiet hum of a small fan fills the space instead. The breeze is weak, but it does not stop. Without that faint rotation, the night would feel unbearably hot—too still, too suspended.

On my desk sits a half-cooled Americano. Most of the ice has melted, and the coffee has turned lukewarm. Drops of condensation slowly slide down the side of the cup, as though they mark the traces of a hand that reached for it several times, only to pull away again.

An unfamiliar screen is open on the monitor.

It is a terminal window.

AWS Lambda function deployed successfully.
CloudFront distribution updated.
Domain propagation in progress.

White letters race across a black screen.

I stare at those lines for a long time.

What exactly am I doing right now?

A person who has spent his life planning content, analyzing policy, and discussing corporate risk is now sitting in front of a terminal window. Reading AWS deployment logs. Checking whether a domain is properly connected. Copying error messages and asking AI about them again.

To some people, it may seem like an unfamiliar sight.

But strangely, it does not feel unfamiliar to me at all.

At times, it feels as though I have wanted to do this for a very long time—to build, with my own hands, the services that had only drifted around inside my head; to give them names; to bring them onto a screen; to quietly launch them somewhere on the internet.

I thought the world had changed.

But to put it more precisely, it was not only the world that had changed.

I was changing, too.

I Closed the Naver Search Box

At some point, opening a search box began to feel tiring.

At first, I assumed it was simply because I was exhausted. After spending an entire day reviewing information, reading meeting materials, scanning articles, and flipping through reports, even typing a search query can begin to feel like a chore.

But the next day was the same.

And the day after that, nothing changed.

Now, before I open a search engine, I open AI first.

When I see a product I like, I take a photo and ask:

“What product is this?”
“Roughly how much does it cost?”
“Are there any similar models?”

Sometimes I take a picture of what I am wearing and ask:

“What kind of tie would go with this jacket?”
“Would these shoes look too much?”
“Would it work to wear this shirt color with the rest of the outfit?”

In the past, I would have started by thinking about the right keywords.

Brand name. Product name. Color. Model number. Reviews. Price comparisons. Styling recommendations.

To search effectively, I first had to construct an effective search query. I had to think about what exactly to ask and how to phrase it in order to get closer to the answer I wanted.

But now, I simply take a screenshot or a photo and show it to AI.

It is faster.

It is less tiring.

And, more often than I expected, it is more accurate.

When I type something into the Naver search box, there are often things waiting for me before the answer I actually want.

Sponsored links. Advertisements. Paid promotions. Affiliate content. Recommendations.

The labels may differ slightly, but in many cases, someone else’s marketing budget greets me before the information I came looking for.

I enter in search of information, only to realize that I am gradually being persuaded by someone.

“Buy this.”
“Read this article.”
“This company is the best.”
“Click this link.”

Too often, the article I enter “just to see” does not contain the information I was actually looking for. Instead, it is filled with long sentences written for search-engine optimization, draped over thin substance. There are many words, but little information. The title sounds convincing, but almost nothing remains after reading it.

There is no real information.

Only text.

Google once felt different, but these days even that feels like an old story. Search results are increasingly filled with pages that look as though they were mass-produced by AI. Articles from years ago sometimes appear near the top as though they were current information.

The act of distinguishing real information from imitation has itself become work.

YouTube is no different.

I enter because I want to find a particular video, but the algorithm shows me first the content most likely to keep me watching longer. It often seems to understand better than I do not what I want to know, but how long I can be held in front of a screen.

News websites are not much better.

I go there to read an article, but advertisements crowd the space below the headline, between paragraphs, beside the text, and beneath the screen. The flow of reading is interrupted again and again. The page shows me advertising before it lets me focus on the story.

At some point, I stopped being someone who simply searches for information.

I became someone who has to avoid advertisements in order to find it.

That fatigue accumulated slowly.

And one day, I began asking AI instead of opening a search box.

“What are the current trends in startup investment?”
“Find the clauses in this contract that could create risk.”
“What is the precise difference between Cloudflare and AWS?”
“What are the weak points in this business idea?”
“Is there a question I am failing to ask?”

AI does not place advertising in front of me.

It does not begin with sponsorship labels.

It does not answer a completely different question.

It does not try to sell me something.

If it uses language that is too technical for me to understand, it explains again. If I ask for a simpler explanation, it rewrites the answer in simpler terms. Even when I ask a clumsy question, it somehow gives me a remarkably fitting answer.

I do not feel anxious when I ask.

I do not have to worry about which keywords to use, how to combine search terms, or where I should begin looking. I now know, almost physically, that the experience feels far more comfortable than search.

Naver Search is not completely dead.

But it is losing trust.

And AI is filling the space it leaves behind.

AI Grows by Consuming Knowledge

That raises another question.

What did AI consume in order to become so intelligent?

Someone may have spent the night reporting a story.

Someone may have turned decades of accumulated experience into sentences.

Someone may have recorded a personal analysis in a small blog.

Someone may have spent months gathering materials to complete a single report.

Someone may have written an essay after passing through the hardest period of their life.

Someone may have held onto their own failures, regrets, thoughts, and emotions for a long time before finally turning them into writing.

AI reads those things.

It reads, learns, summarizes, and recombines them.

Then it gives the user an answer.

“This is how you should do it.”
“This is the key point.”
“These are your options.”

For users, it is convenient.

For me, too, it is convenient.

But when I think from the perspective of someone who creates content, a small part of me becomes uneasy.

Did AI read my writing?

If it did, where was it used?

How many people saw it?

Was my name preserved?

Did anyone visit my website even once?

Traditional search engines, at the very least, left a path back to the original source.

When users clicked a result, they were taken to the writer’s website or the original article page. There, they could see the author’s name, read more of that person’s work, subscribe to the site, or view advertisements. It was not perfect, but there remained at least a possibility that readers could find their way back to the person who created the content.

There was a content creator.

There was a person looking for content.

And the search engine served as the passage connecting the two.

But in the AI era, that passage may become narrower—or disappear without anyone noticing.

My writing may be absorbed into an AI response, and I may never know it happened. A piece I spent days researching, revising, and shaping may be answering someone’s question somewhere, while that person never sees my name.

They may never visit my site.

It may become difficult even to know where my content is being used, how often it is being used, or in what form.

The user receives an answer.

But the person who created the content may receive no traffic, no response, and no reward.

At that point, the issue of content is no longer merely philosophical.

It becomes a business-model issue.

To put it more bluntly, it becomes a question of survival.

This is an era in which media companies can enter court receivership. The advertising market has been unstable for a long time, and building a reliable revenue stream through subscriptions alone is far from easy. Writing good journalism, conducting long investigations, and checking facts carefully do not necessarily lead to sufficient income.

Content does not simply appear on the internet by itself one day.

Reporting costs money.

Writing takes time.

Video requires human labor.

Someone has to visit the scene.

Someone has to verify materials repeatedly.

Someone has to examine the errors and context hidden behind every sentence until the very end.

If the content created through that work is consumed only inside AI responses, while the path back to the original source weakens, then the motivation to create the next piece of content will weaken as well.

That is why the question in the AI era cannot simply be, “Should AI be allowed to read content?”

We also need to ask who receives the value generated from the content AI reads, and how that value returns to the people who create the next piece of content.

Following that question leads to a more fundamental issue.

Choice.

I may want my writing to appear in search results.

I may want someone to discover my story by chance.

But that does not necessarily mean I have given blanket permission for my content to be used for AI training, absorbed into AI-generated responses, and distributed in ways that never return value to me.

Appearing in search results and being used by AI are not the same thing.

There is a difference between someone knowing the address of my home and coming to visit, and someone entering my home, browsing through my bookshelves, then going outside and retelling the contents in their own words.

That was why the title of a Cloudflare press release I happened to see on July 1 stayed with me so powerfully:

“Your Content, Your Rules.”

Your content.

Your rules.

This is not simply a story about security settings.

It feels closer to a declaration.

“I have the right to speak about who can read what I create, for what purpose it can be used, and how the value it generates should be shared.”

When an AI agent visits my website, I should now be able to ask:

“Whom are you representing?”
“What are you trying to take?”
“Where are you going to use it?”
“Who receives the value in return?”

This is not an argument for blocking AI.

It is an argument for ensuring that content creators do not lose their place in the AI era.

Of Course, AI Has Changed Me Completely

To be honest, I cannot think of AI reading and taking content as something purely negative.

AI has changed me completely, too.

For years, I have planned content, analyzed policy, and interpreted the risks companies face. Content planning, policy analysis, and risk management have long been both my expertise and my means of survival.

Now I talk to companies about AX transformation.

I explain how AI can change organizations, what risks may be hidden within that change, and what companies need to prepare for.

But ironically, I have become one of the people most dramatically transformed by AI itself.

These days, I ask Claude Code questions like these:

“How do I connect a Lambda function to API Gateway?”
“Why am I getting this error message?”
“CloudFront cache is not refreshing. Where should I look?”
“How can I check whether my DNS records are properly connected?”
“Could this structure create a security problem?”

Then the AI on the screen answers calmly:

“Check this part first.”
“Change this setting.”
“The cause of the error is most likely here.”
“Try running this command.”

I follow the explanation.

I click one thing at a time.

I change settings.

I save.

When an error occurs, I copy the screen exactly as it is and ask again.

When the explanation feels difficult, I ask it to make things simpler.

“Where am I stuck right now?”
“Explain this so that even a beginner can understand it.”
“Start again from the beginning.”

Then, at some point, lines like these appear on the screen:

Build successful.
Deploy complete.

The feeling I get when I see those short sentences is more than simple satisfaction.

It feels as though I have opened the door to an unfamiliar country.

It feels as though I am cautiously stepping into a world I once believed I could never enter.

These were questions I would once have asked a developer.

I would have needed someone else’s time.

I would have had to search through technical documentation for hours.

In many cases, they were tasks I might have postponed before even beginning, overwhelmed by the uncertainty in front of me.

But now, I ask AI first.

If I do not know, I ask.

If I get it wrong, I ask again.

If I do not understand, I ask for a simpler explanation.

AI was not merely a tool that handed me answers.

It was closer to a guide that lowered the threshold of a world I had never entered before.

The moment a service I had imagined under the name “Jinny Lab” appeared somewhere on the real internet, I became certain.

The world really has changed.

This is now an era in which we can directly build, even in a small form, the things we once only imagined.

Last month, I planned and built a technology-media platform called META-X, from the front end to the back end.

I also added an AI-generation feature to the article editor.

And I confirmed for myself that it may be entirely possible to build AI-agent functions as well.

That confidence led me to create a website for an international metaverse association and build a platform for academic events. For people around me who needed websites or service platforms, I began experimenting with small services one by one.

Now, I design DynamoDB tables.

I connect Lambda functions.

I adjust CloudFront distribution settings.

I check Cloudflare WAF rules.

I deploy through Amplify.

I modify DNS records myself.

If I had shown this sentence to myself one year ago, I probably would have laughed.

“Why would I do that?”
“Is that even possible?”
“I am not a developer.”

But now it makes sense.

Because of AI.

I did not get here by earning AWS certifications.

I did not attend a coding boot camp.

I did not spend months studying code while holding onto thick technical books.

I simply asked.

When I did not know, I asked.

When I made mistakes, I asked again.

When I could not understand, I asked for a simpler explanation.

There was only one thing I contributed to that process.

I knew what I wanted to create.

While building Jinny Lab, I learned through experience that this may be the most important ability human beings need in the AI era.

Differentiation Is Not Knowledge. It Is Intuition.

When I talk with companies about AX transformation, I am often asked the same question.

“What should our company compete on in the AI era?”

These days, I answer like this:

The era of competing through knowledge alone is coming to an end.

In the past, the people who knew more were ahead.

Those with more information found opportunities first.

Organizations with broader knowledge developed better strategies.

Knowledge was a barrier to entry.

But now things are different.

When we do not know something, we can ask AI.

AI can help us find materials, compare information, organize data, prepare drafts, design code structures, and analyze markets.

That does not mean we no longer need to study.

It does not mean experts are unnecessary.

In fact, the opposite is true.

The ability to judge what we should study, what we should believe, and how far we should use AI has become more important than ever.

We are now living in a time when anyone with a single AI subscription can produce a substantial result.

The age of building businesses merely by imitating or copying what others have done is ending.

Even with a small idea, we must think intensely about where differentiation will come from.

I believe the answer is intuition.

Creation has always begun with imitation.

Human beings have learned from what already exists, absorbed it, connected it, and recombined it to create something new.

AI is not entirely different.

It learns from the knowledge humanity has accumulated, finds patterns within it, and assembles the most plausible answer.

But human beings can ask an entirely different question in the space between those answers.

AI lists possibilities.

A human being points to one of them and says:

“This is it.”

Perhaps what humans must truly do in the AI era is not memorize more answers, but discover their own eureka.

The more information, options, polished drafts, and refined analyses pour in front of us, the more important it becomes to recognize what truly matters to us right now.

AI can show us dozens of possibilities.

It can organize the safest option, the most efficient path, similar cases, and expected outcomes.

But deciding which answer to hold onto still belongs to human beings.

Which problem should we pursue until the end?

Which discomfort should we refuse to overlook?

What can we discover anew in information that everyone else already knows?

What is needed in that moment may not be more knowledge, but the instinct to say:

“This is exactly it.”

There is a word: Eureka.

It comes from the story of the ancient Greek mathematician Archimedes, who is said to have discovered the principle of buoyancy while noticing water overflow during a bath.

Today, it is closer to the cry of someone who has struggled with an unsolved problem for a long time, only to suddenly find the first clue to an answer.

Eureka may appear to be an accident.

But it is not simply a flash of inspiration falling from the sky.

It arrives when a problem we have observed for a long time, questions we have failed at repeatedly, and curiosity we refused to abandon finally connect in a single direction.

The humans who matter in the AI era will not necessarily be those who know the most.

They will be those who discover their own questions among countless possibilities—and then carry those questions into reality.

To put it simply:

AI organizes data.

Humans sense why that data matters now.

AI shows countless cases.

Humans discover unnamed patterns between those cases.

AI learns patterns.

Humans sometimes break them.

That is intuition.

It is inspiration.

It is insight.

And perhaps it is the kind of instinct that comes from having lived for a long time.

Corporate AX transformation is ultimately the same story.

A company does not become competitive simply because it has introduced AI.

What will it ask AI?

What does it want to see?

Which problem is it trying to solve?

What kind of insight will it draw from that process?

The quality of those questions will ultimately determine a company’s future.

The Rules I Am Building for My Life in the AI Era

The night has grown late.

Only the light from the monitor illuminates the room.

Outside the window, the quiet road of a Sunday evening is faintly visible between the glow of streetlights. A few lights remain in the windows of the building across the street. In the distance, car headlights stretch across the wet road and disappear.

Even at this late hour, the city cannot sleep completely.

Somewhere, an air-conditioner compressor is running.

Somewhere, someone has still not gone home from work.

I look at the Jinny Lab dashboard.

There are still unfinished screens.

Features that need to be connected.

Bugs that need to be fixed.

Questions I will have to ask Claude Code again tomorrow.

But strangely, it does not feel heavy.

In fact, it feels like the opposite.

I feel as though I am moving forward, little by little.

The fact that it is unfinished does not make me anxious.

It feels like proof that there is still more I can build.

I find myself thinking that I am living through my own AI era.

An era in which a content planner can build a service directly.

An era in which a policy expert can operate a platform directly.

An era in which someone who consults organizations on AX can experiment with AX in his own life.

An era in which someone with an idea can try to carry it all the way into implementation.

The words that have quietly settled inside me keep repeating themselves.

My content.
My rules.

I think to myself:

It is not entirely bad that AI reads my content. Because of AI, I have already come much farther. I have begun to understand worlds I once knew nothing about, and I have started building services I had previously only imagined. Things I would once have waited for someone else to help me with are now things I can ask about directly, attempt directly, fix directly, and move forward with directly.

But that does not mean I want to surrender control over my content.

I decide what I create.

I decide whom I open it to.

I decide under what conditions I share it.

That is what it means to live in the AI era according to my own rules.

It is not a defensive move meant to push AI away.

Rather, it is the work of establishing the standards I need to protect in order to go farther with AI.

The world is changing too quickly.

And in order not to be swept away by that change, I want to decide where I stand first.

The cursor blinks steadily on the Brunch writing screen.

I begin writing down the rules I believe in.

The things I want to create in the AI era.

The things I want to protect.

And the things I do not want to give away too easily.

Differentiation in the AI era is not knowledge.

The era in which the person who knows more automatically wins is fading.

This is becoming an era in which those who feel more sharply, ask more deeply, and establish their own rules move ahead.

That is why I keep thinking.

My content.

My own rules.

And my own intuition.

Written by Gwanghwamun Deok, July 5, 2026.