Standing Before the AI Wave — One HK Working Man's Choice

When Everything Goes Stale

You’ve been in the workforce for a while now. Long enough for most things to lose their novelty. And somewhere in that monotony, you realise: some things in this world are beyond your control, and some things aren’t.

Technology Waves Wait for No One

From the Industrial Revolution to the AI Revolution

No one can stop technology. During the Industrial Revolution, you couldn’t stop machines from replacing human labour. You could only adapt — slowly, painfully, hoping for a long transition period. It was brutal back then. Stop working, stop eating.

History Repeats Itself, But Faster This Time

History is a cycle. It keeps repeating. We read about it in books, but when it happens in real time, we’re swept into the current whether we like it or not — witnesses to yet another technological revolution. Let progress march on while you plug your ears, and sure, you won’t hear the thunder. But that doesn’t mean the thunder isn’t there.

Running Won’t Help — Face the Fear

Don’t kid yourself. The only way out is through. We should learn how AI works — its operations, its limits. The pattern is always the same: after people tamed horses, they learned to ride. After the bicycle, they learned to pedal. After the car, they got a license. You can wait until the change is fully here and scramble to catch up, or you can start early — small steps, steady pace. Think of it like a long-running TV series. If you wait until all ten seasons drop before starting, you’ll never have the energy to finish. Better to follow along, episode by episode.

Why Learn AI

Not to Chase the Trend, But to Read the Times

Lobster (Open Claw). Hermès (Hermes Agent). Two terms that suddenly exploded in early 2026. Do you know what they are?

Rewind to 2025. Remember the DeepSeek moment? The last few years have seen AI transform at a pace that’s hard to digest. Hundreds of preprints hit arXiv every day. Projects spring up on GitHub faster than anyone can track. If we bury our heads in the sand, we fall behind — simple as that.

Hong Kong’s mobile carriers have already shut down 2G. Are you still browsing on 3G? Time to think about 4G, maybe 5G. AI is the same story.

Remember AlphaGo? That was 2016 — exactly ten years ago. Have you been paying attention since? Through COVID and beyond, AI made leaps that rewrote the rules. If you want to see where the world is heading — really see it — you need to take AI seriously.

The Real Experience of Learning on Your Own Time

It’s ideal when your company backs AI adoption with real action — you upskill during work hours, you integrate AI into actual workflows. But that’s rarely the reality. More often, management talks the talk without a clue how to execute. They’re from a generation that still struggles with email, let alone AI. So if you want to learn, it’s on you.

But how much spare time do you really have? Everyone’s situation is different. Family, chores, fitness — priorities stack up. The first step is getting your daily schedule in order. The upside of the AI era? You can use AI to learn AI. Conceptual stuff fits into碎片 time (commute, lunch break). Hands-on work needs proper planning — I’ll share my learning process in future posts. It’s slow. Not as efficient as when I was younger. But if it gets the job done, that’s enough.

Why Build This Website

Learning for its own sake isn’t the point. At this age, I’m not chasing a certificate. For me, learning means building something you can see and touch. This website — built by someone who barely knew computers, using AI agents. Watching the agent work taught me more than any tutorial ever did.

Running a site at this stage of life doesn’t cost much, either. The real motivation is simpler: learning is genuinely interesting. And on the internet, you’ll always find people who get it.

Why “TypingHand” (鍵筆)?

I won’t ask when you last wrote by hand — you’d be surprised how often you still need to sign things. But in the AI era, our pen is the keyboard. Typing is writing. The name TypingHand has a second meaning: using AI agents as the hand that writes code, opening doors that would otherwise stay shut.

Real Figures, Real Talk, Real Test — The Three Columns

The site is built around three core columns:

Real Figures (實數): Let the data speak. Neutral, pipeline-driven indices that track AI’s arrival and evolution — and its limits.

Real Talk (實話): Straight talk, written by me. Personal essays on technology, time, and the ups and downs of a Hong Kong career.

Real Test (實試): Hands-on testing. Trying out AI tools myself and documenting the results.

Two more columns are in the pipeline: Real Use (實用): Step-by-step setup guides from scratch. Real Read (實讀): AI concepts unpacked in plain language.

Neutral Witness, No Signals to Sell

My stance is simple: neutral observer. Neither cheerleader nor doomsayer. Use it when it helps, learn it while you can. I’m not here to sell you signals or hype. I call it as I see it — nothing more.

What You’ll Find Here

Regular columns under Real Figures: AI Era Watch — Weekly updates. The AI developments you shouldn’t miss, curated and contextualised. Real Figures Weekly — A custom dashboard, updated weekly, answering three questions: When does AI actually enter our daily lives? When will crypto behave like real currency? Can an AI-driven stock picker beat index investing over the long run?

Other columns update on their own schedule — when there’s something worth saying.