Investor Identity
Vincent isn't betting on AI. He's betting on what AI does to everything else.
He thinks AI gets way bigger than people expect. He also thinks the best returns won't come from the companies building the AI itself.
They'll come from the choke points. The stuff every AI company has to buy, rent, or get permission to use.
Power, memory, fiber, chip materials, business software, payment rails, healthcare and robots.
That looks like eight different bets. To Vincent it's one bet seen from eight angles.
Where he plays
Everywhere AI shows up except the AI models themselves. Power, memory, connectivity, chip materials, business software, payment rails, healthcare, robotics, and crypto.
Background
Vincent is an AI markets analyst and Milk Road AI PRO researcher.
He studies AI as an economic system and publishes deep-dive research on the companies shaping the AI economy, while also advising C-level teams on AI adoption across multiple industries.
Portfolio Structure
How he invests
A handful of big positions he really believes in, plus some small lottery tickets and crypto around the edges.
Long-term by default, but never on autopilot. Every position gets ranked against every other one, constantly. Nothing stays just because it's already there.
There's no maximum position size. Size comes down to three questions. How sure is he? How soon does it pay off? And how lopsided is the upside versus the downside?
A company with proven demand, limited supply, real earnings coming, and a beaten-down price can become a very big position. Something great but years away stays small, no matter how good the story sounds.
What he's looking for (and what he avoids)
Four boxes to tick:
- AI has to be genuinely changing this business.
- The market can't have priced it in yet.
- There has to be proof it's happening, not just a story.
- The company has to actually be able to make money from it.
His favorite setup is the old, boring, misunderstood company that AI quietly turns into a growth business. Best of all when a temporary panic knocks the price down while nothing has actually gone wrong.
Selling is a judgment call, not a formula. He splits it into two buckets, and the difference is the whole point:
- Price risk is when the stock drops. That's a reason to take another look, and often a reason to buy more.
- Thesis risk is when the company gets worse at capturing the opportunity. That's when he sells.
He'll also trim when the good news is fully priced in, when the stock needs everything to go perfectly to work, or when something better comes along.