---
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.
