FAQ

I think about this more than the question implies.

I'm not sure exactly what will be different, and I think that's actually the right starting point. Markets are shaped by local culture, regulation, and consumer context, and the UK is genuinely different from Korea in ways I'm still learning about.

That said, the underlying human behaviours tend to travel better than the market context does. People everywhere read reviews before buying. They hesitate when they don't trust the information in front of them. They respond to social signals. They make decisions they can't fully explain. Those patterns didn't change when I moved from growth work at Kurly to content systems at Musinsa. I don't expect them to disappear when I move to London.

What I'm bringing isn't "Korean e-commerce experience." It's a way of structuring messy user behaviour problems into product decisions, built across review systems, content platforms, full-journey CX, and brand advertising. The domain names change. The thinking process stays fairly consistent.

The gaps are real, and I'll need time to close them. But I'd rather say that directly than pretend they aren't there.

Most communication problems I've encountered weren't really about language.

Even in Korean, working with engineers who think in systems and PMs who think in user journeys, I'd often end up drawing flows on paper or sketching in a notebook mid-conversation, just to make sure we were pointing at the same thing. It helped. We were sometimes using the same word to mean completely different things.

Working with an Indian financial analyst and a US-based vendor, the hard part wasn't writing grammatically correct emails. It was adapting to financial terminology I didn't know, aligning on workflows that operated differently, and building enough trust that people would tell me when something wasn't working.

Collaboration is less of a language test and more of a process of understanding how someone else thinks. What words do they reach for naturally? What do they prioritise without thinking about it? How do they make decisions? Small talk helps with this more than most people expect. Not because it makes things friendly (though that helps too), but because it reveals how someone thinks before you're in the middle of a disagreement.

On a more personal note: I've lived with my Australian partner for seven years. We've never had a serious problem caused by language. We have, however, had a fairly involved debate about the most efficient way to do the dishes. That was a human problem.

I'll need time to learn new jargon and new contexts. I don't find that particularly daunting. What matters is whether you're willing to ask when you don't know something, and whether you keep aligning until things actually make sense.

Yes, technically. Though I'm less sure the line is where it's usually drawn.

The industry was talking about personalisation, recommendation systems, automation, and behavioural prediction long before "AI" became the word for all of it. The framing changes faster than the underlying problems do.

I studied NLP and text mining at university. My first product experience was designing an AI curation service. Since then I've worked on recommendation algorithms, behavioural segmentation, automated merchandising systems, and personalised push logic. These are the technical ancestors of what's now called AI-powered product features.

What I've consistently been interested in isn't the model itself. It's the question of how technology changes the way people make decisions and what they pay attention to. That question is getting more interesting, not less.

Where I think AI product design is actually going: the competitive edge will matter less at the model layer and more at the interaction layer. How do users calibrate trust in AI recommendations? When does automation feel helpful versus intrusive? How do you design for confident users and uncertain ones at the same time? These feel like the hard problems, and they're closer to the work I've been doing than the technical gap might suggest.

I'm not claiming to have solved them. I'm saying I find them worth working on.

I understand why it reads that way on paper.

My own experience of it was more like following a single question across different angles than moving between unrelated things.

At Musinsa, I started with reviews. But the longer I worked on them, the more I noticed that users weren't just extracting information from reviews. They were browsing them the way they'd browse style content. A review with good photos wasn't really a review anymore. It was fashion media. That observation eventually led to working on Snap, Musinsa's style content platform.

What made Snap interesting was its structural position in the product. It had its own profile system, upload flows, and discovery logic, enough to feel like an independent platform, but it was also woven into the shopping app's PDP, PLP, cart, and order history. Designing for it meant working across brand teams, influencer relationships, regular users, and commerce goals that sometimes pulled in different directions.

That's probably why the organisation started asking me to work on problems outside a single surface. CX TF was the whole purchase journey. Discovery was brand advertising and revenue. I reported directly to the Chairman on the CX work.

Looking back, I think I was following the same thread the whole time: how does human behaviour become content, become community, become a purchase decision, become a business? I just kept finding that the next part of the question was in a different team.

The through-line is probably that I'm drawn to problems at the edges of things, where a feature connects to a system, or where a user behaviour has product implications that haven't been fully worked out yet.