There’s a second account I run that I haven’t mentioned here either: a Chinese-language Xiaohongshu account about value investing, built almost entirely with AI as my study partner.
I want to explain why I built it in Chinese before ever writing about investing in English, because the reasoning says something about how I think AI is actually useful — not as a tool that gives you answers, but as a tool that’s patient enough to teach you for ten months straight.
Ten Months, One Patient Tutor
About ten months ago, I started using Gemini to learn value investing seriously. Not videos, not paid courses — just long, repeated conversations, asking the same kinds of questions in different ways until concepts actually stuck. A friend who’s been investing far longer than me, using a similar AI-assisted approach, became something like an informal mentor along the way, pointing me toward better questions to ask.
What came out of those ten months wasn’t a stock pick. It was a framework — three things I now check before I even start looking at numbers:
– Can this business repeat what made it successful, in new markets or product lines?
– Does it have the pricing power to raise prices without losing customers?
– Is there real room left to expand?
And on the buying side, three habits: buy when sentiment is darkest and the price doesn’t reflect the business, reinvest dividends instead of spending them, and then — the hardest one — sit still and stop checking the price every day.
The Losses That Taught Me More Than the Wins
I’m not going to pretend this framework saved me from every mistake. I’ve taken real losses on real positions, including stocks where I cut losses after realizing I’d misjudged the business case. Those losses are part of why the framework exists now — it was built backward from “what would have stopped me from making that mistake,” not forward from a textbook.
That’s also why I built the account around honesty rather than performance. No price targets, no “buy this now,” nothing implying I know what happens next. Just the actual reasoning, including the parts where the reasoning was wrong.
Why Chinese, Why First
I write in Chinese first for a simple reason: it’s the language I think in when I’m doing the actual work of valuing a business, and most of the people in my situation — ordinary people learning this without a finance background, using AI to fill the gaps — are reading and writing in Chinese too. There’s also genuinely less honest, framework-first investing content in that language than in English, where value investing has a much longer publishing tradition. It felt like the more useful place to put the effort first.
The account is still tiny. The first real post went up and picked up a modest number of followers in the first day — nothing dramatic, just a sign that a few people found the framework useful enough to stick around for more.
What Success Actually Looks Like Here
If you’d asked me a year ago what success on an account like this would mean, I probably would have said “growing followers” or “monetizing it somehow.” Ten months in, my answer has quietly changed: success is mostly about not feeling anxious anymore. Not checking prices compulsively. Having a process I trust enough that a red day doesn’t wreck my afternoon.
I have a son starting high school, and somewhere in those ten months of conversations with AI, the project quietly turned into something I half-hope he’ll read one day — not stock tips, just the reasoning, written down honestly enough that it still makes sense years later.
That’s most of why this exists. The English blog you’re reading is about AI and side hustles. The Chinese account is about AI and patience. Different language, same underlying habit: use AI as a tutor that never gets tired of your questions, then do the hard part — the actual thinking — yourself.
If you’ve used AI to learn something slow and unglamorous — not a quick skill, but something that takes months to actually sink in — I’d like to hear what that process looked like for you.