Hobby Capital - H. Jun Huh H. Jun Huh Hobby Capital<br>July 7, 2026<br>Translated by Claude Opus 4.8<br>1. In the AI era, knowledge work loses its value while domain knowledge becomes what matters.

Knowledge gets produced fast and consumed fast. We now live in an age where AI automatically collects and summarizes primary data, making information delivery trivial. AI creates content and AI reads content. This age arrived a long time ago.

Agentic AI is replacing not just knowledge but the actions built on top of it. AI can interpret medical knowledge, legal knowledge, and even physical domains, and it can hand you a set of instructions to act on.

What AI doesn’t have is domain knowledge. Every industry (finance, hobbies, medicine, you name it) has high-context areas. The raw data AI gathers on its own doesn’t explain them.

Agentic AI that rides on top of domain knowledge can actually run useful work.1 If you get AI to collect high-context information and build an action workflow around it, you end up doing things that neither an ordinary person nor an ordinary AI could pull off.

You have to go after human-dependent fields. The go-to examples are Karrot (physical relationships), Hervey (licensing barriers), and Anduril (defense). In these fields, an AI workflow creates a compounding structure.

So does each individual person’s data matter? No. Personal context data isn’t a moat. Information about a single person’s life, their behavioral patterns, and so on migrates easily. When a new service comes along and you want to switch from ChatGPT to another LLM, you just ask GPT for the information it has about you. Personal context data is easy to extract.2

You have to separate declarative knowledge from tacit knowledge. Take pour-over coffee. A preference like “I like coffee with acidity” is verbalized, so it moves easily between LLMs, but the feel for reading how much the grounds bloom when you pour water and adjusting the thickness and speed of your next pour accordingly can’t be verbalized at all, which makes it impossible to extract.

2. Hobbies are the domain knowledge that’s about to take off.

A hobby is an activity you have to acquire through your own body, where the point is the process itself rather than the result, and where value only arises when the person doing it is you. That’s why most hobbies live in the physical realm. And the physical realm isn’t something AI can easily replicate.3

Sports, instruments, exhibitions, being a barista, going to shows, wine: most of the hobby fields we know of are physical.

With work, the result is the point, so you can swap out who does it and the value holds. With a hobby, the process and the experience of “I do it myself” are the point, so the moment you swap out who does it, the value disappears. Even if a robot finished a hike for you, it would mean nothing. In other words, humanoids don’t replace hobbies. They take away your work and give you back your hobby time.

Hobbies have depth. The knowledge you’ve acquired through your own body becomes the barrier to entry. It functions as a kind of self-satisfaction. Like the “easy to learn, hard to master” structure in game design, the easier you make it to get started, the more people flow in, and the pyramid of mastery above them actually grows larger. The reason lowering the barrier to entry (which I’ll get to below) is itself a business opportunity also comes from “easy to learn.”

A hobby isn’t knowledge work. The goal isn’t productivity, it’s pure fun. And that feeling is something AI can’t deliver.

Hobbies come with identity and community. The core of it is the fun of spreading a hobby and talking about it with other people.

3. Going forward, the goal is to lower the barrier to entry for hobbies.

A clear example: over the past few years, the share of live classical performances has gone up.4 People increasingly want and enjoy high-context hobbies of a serious caliber. Even so, you need to understand why classical music is hard, and there are three big reasons.5

You have to understand the history.

You have to know the historical backdrop against which the composer wrote the piece, who the composer is and what kind of life they lived, who’s conducting it now, what the world’s famous orchestras are (the Vienna Philharmonic, the Berlin Philharmonic, the Royal Concertgebouw Orchestra), and which recordings are the great ones. This isn’t about memorizing facts. You have to approach it as if you’re living in that era yourself.

You have to understand form and theory.

You have to understand the basic movement structures of classical music: sonata, ternary form, scherzo, rondo, and so on. There’s a fun in matching the form as you listen and understanding it, and it helps you catch the hidden meaning in a piece. On top of that, you have to know the multi-movement forms like the symphony, the concerto, and chamber music.

You have to enjoy the music itself.

This part is a hobby from the very start. Even if you know...