97 · White Papers and Needles

A list of alphas. Go to the top consulting firms' websites — they release white papers. McKinsey, BCG and PwC spend over $500k per report analysing global trends, emerging industries and disruptive technologies. These are the same insights Fortune 500 CEOs use to make billion-dollar decisions — and all of it is free and public on their websites. You can access the same data that took hundreds of analysts months to compile, covering AI, renewable energy, biotech, fintech. This is public alpha: market disruption already identified by analysts, waiting on execution. They are market gaps that need filling — whoever fills them faster and better gets paid.

Job-hunting alpha for the borderless: Welcome to the Jungle — curated tech and startup postings with real company analysis. Cord — talk directly to recruiters and hiring managers. VisaSponsors.jobs — companies sponsoring visas across the UK, US and Canada. UK Visa Jobs — essential if the target is Britain; filter to sponsors only. Glassdoor — salaries, interview reviews, insider information; check before applying, always. Plus the job simulations from the top quant and finance firms.

A really important revelation that hit hard recently: something's value is always personal — almost completely irrelevant to what society labels as elite. In fact the mainstream can act against you, blurring what really matters. The channels I learn the most from have fewer than 100k subscribers, talking about their own niche, and I'm taking notes and fitting their datasets and algorithms inside me. Small community; works for me. Same for websites: poorly built, not mainstream at all — and they completely eradicate MY current bottleneck, which makes them worth all my money. When the true skill you want is metacognition, some random PDF on Amazon with four reviews might be worth far more than a famous book by a famous person.

There is some level of great alpha behind paywalls. Be willing to pay for what matters. Keep the flow going.

Quite integral: know the common language that people in physics use — same for finance, same for maths. Be willing to learn the technical terms and what they indicate; it clears so much misunderstanding when you're communicating your thought process.

See — it is a bit cumbersome to re-memorise all the terms I used to know in Korean and now must learn in English. It's almost like a new universe I didn't know existed. And it's worth it: the terms are the handles on the tools.

I'm technically trying to get PhD-level maths, physics, CS and finance within a very constrained window — transcending Fields Medal and Nobel scale in my mid-twenties. Get used to tolerating more knowledge in a day than is comfortable. The ideal day: a twelve-hour course on Kubernetes, plus two or three textbooks, plus hundreds of financial statements and documents. Gradually scale the throughput and robustness — read more, learn more, integrate more — and build the projects the same day you learn the material. Volume-wise, at peak, I was understanding, memorising and integrating about two dictionaries a day for two months. The scale is trainable. That's the entire secret of the library: it isn't talent, it's tonnage.