AI × FinTech Builder
把投资方法论，做成 AI 能执行的工具。
I work where AI meets financial technology. I use Claude Code to turn investment research methods into skills an AI can execute, and I built and shipped an English-learning mini-program on my own with AI. My hope is to create value through AI — putting professional-grade investment research within everyone's reach.
Featured · Mini-program
WeChat mini-program · one person + AI
Learn English from Buffett and Munger
An English-practice mini-program built and shipped by one person + AI: practise with real quotes from Buffett, Munger and other great investors, get instant AI pronunciation scoring, and absorb investing wisdom while you learn.
40s→8sAI scoring wait time (tested in this project)
Builds
Method
Each step is handled by a dedicated subagent; seven agents work together to produce a complete company analysis report.
股票分析：新华人寿, 601336.SH“True financial democratization is, at its core, the spread of equity and ownership.”
Watch · Douyin
Writing · WeChat “Vega二向箔”
Would you hand your brokerage account to an AI agent trading 24/7? Following Robinhood's experiments, three layers of logic: from tool to agent, where alpha comes from when everyone uses AI, and why so many people resent AI — a lack of skin in the game.
Read more →Notes on Caixin's cover story on the token economy: as AI moves from answering a question to finishing a whole job, enterprise bills, model pricing, industry profits and the battle for the office are all shifting. Growth and profit must be counted separately; ordinary people's opportunity lies in getting things done.
Read more →95% of enterprise AI projects fail — what do the other 5% do? Unpacking the playbook of OpenAI FDE lead Colin Jarvis: decide whether you earn service fees or product revenue, eat pain and excrete product, avoid premature generalisation, and the Klarna and Morgan Stanley cases — the hard part is the data layer.
Read more →An LLM that can write factor formulas is not a usable quant research agent. Factor-Agent wires PandaAI's data, factor computation, backtesting and QuantSkills into a verifiable, traceable, iterative research loop: the LLM only proposes hypotheses; evidence from backtests, out-of-sample tests and overfitting gates decides what gets promoted.
Read more →About
AI × FinTech — hoping to create more value through AI.
I'm yanglaiyang, author of the WeChat Official Account Vega二向箔. I focus on where AI meets financial technology: handing investment research methods to AI to execute, and turning institutional-grade capabilities into tools ordinary people can use. From a stock-analysis skill and a Xueqiu daily digest to Value Speak, a mini-program I shipped as one person + AI, I believe AI matters most when it creates value for more people. Happy to talk about AI investment research, agent development and collaboration.