Why Korea Embraced Claude Blue: The FOMO Pattern
Koreans are not like this only with AI. It was the same with Bitcoin, the same with real estate, the same every time a new platform opened.
People were not excited because they were curious about Silicon Valley trends. The feeling of falling behind if they skipped this was already there.
This post is based on a conversation with tech and entertainment critic Woojin Cha.
Feeding decades of columns to a model
As a non-developer, he started digging into AI seriously last September. Engineers around him advised that it was still a transitional period and he could catch up once things settled, so he let it go for a while. Then word came that a new model had jumped in capability, he picked it back up, and now runs about ten projects at once.
One of them stood out. He fed the model every column he has written over decades, and because those columns were never written to a fixed theory or formula, he asked the model to work backwards and theorize them. The old process was gathering sources and insights, making notes, building a skeleton, finishing the column. Once that theorization becomes an agent, the middle disappears: notes go in, a column comes out.
The next experiment is persona mixing. Like a DJ, blend your own insight and writing style with those of someone else to create a third expert persona. It used to take years for a philosophy person to write about mechanical engineering: study the field deeply, then fuse two disciplines. Now you can borrow the expertise of each field and combine, like producing infinite remixes of a track. He compared AI to a gifted child, and said his biggest question these days is how to use that boundless potential.
Ethics came down to the individual
That led to why personal AI ethics now matters more. Ethics used to be the responsibility of leaders and executives. With every individual using AI, the burden has come down to the individual level.
Training on your own writing seems ethically clean, though someone could still question its purity. Use the writing of others as material and the boundary blurs further. The real issue is that AI users all over the world are doing the same thing: mixing each other and making something new. The conclusion was that the AI era needs a rebuilt definition of what is ethical, a new normal for ethics. Declaring that ethics matters is not enough.
It was the same with Bitcoin
We asked why it spread so intensely in Korea in particular. The answer was crisp: Koreans are not like this only with AI. People who entered Bitcoin and NFTs early actually made money, and people who entered late lost it. Live through that once and the instinct to follow fast, unconditionally, hardens.
The YouTube market is already late, so when a new platform opens, the same scene repeats: day-one guides to ten thousand followers pour out. The sense that money goes to whoever enters the new space first was learned in real estate before Bitcoin ever arrived. Search AI today and the thumbnails overflow: skip this and regret it forever, a once-in-a-century opportunity. Anyone carrying memories of missed chances feels the clock start ticking.
Leave the track and you cannot return
Why is Korea especially sensitive? The sense that once you leave the track you can never get back on runs deep, so people strain not to fall out of the mainstream. Cha saw it similarly: Korea is unusually hurried, and people in their thirties struggle most. A longer life could mean more chances, but instead it reads as: live long, and failing to board early becomes catastrophic.
So the conclusion settled like this. People were not excited about Silicon Valley trends, and not amazed by AI. The feeling of falling behind already lived in everyone. It finally got a name.
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