title: "On conviction" type: essay slug: writing/on-conviction date: 2026-04-19

On conviction

The hardest part of investing isn't picking winners. It's calibrating how much you actually know about each pick.

I've watched myself for a few years now. Patterns:

I'm right more often than I think on early-stage product-market-fit calls. The retroactive look is consistent — when I had a strong feeling in the first meeting, I was right ~70% of the time across the cohorts I've tracked. I should probably trust those gut calls more, not less.

I'm worse than I think on geographic claims. The "this won't work outside SF" prior fires too often and is wrong about 60% of the time. The geography-overconfidence pattern is real and I should de-rate every geography-flavored take I make.

I'm worse than I think on macro timing. I've called the AI hype cycle peak three times in the last 18 months and been wrong every time. Three strikes. I should stop making macro-timing predictions until I have a better track record.

I'm well-calibrated on competitive moat questions. The 5-year retrospect on my moat calls is essentially at parity with the market. I can keep trusting those.

What I'm betting on next:

Vertical-AI valuations will compress within 18 months. Moderate conviction, ~0.6 — and I'm going to de-rate this further given the macro-timing pattern above.
The next big platform shift is going to come from agent-orchestration primitives, not model providers. Strong conviction, ~0.75.
At least one major SaaS public market exit happens by mid-2027. Conviction ~0.55 — close to coin-flip.