#AI

Part 1 mapped what the incumbents are building for. This piece looks for the holes they leave. The door is free and the meter is going free, so I'd back what agents buy and the risk of what they do, at prices a realistic exit can repay.

The agent-payment protocols are free, and the open ones carry almost no money. The return sits with whoever issues the agent's credential and writes the rule for who eats a bad payment, mostly card networks and issuers, and with whoever owns the shopper's attention.

A ground-truth read on the fuel, the generation, and the equipment behind the AI build-out: what's physically available, where the constraints exist, and where capital can earn a return

A follow-up on Conrad, my autonomous GTM agent. This round he learned to grade his own work, run his own A/B tests, and rewrite his own playbook when the numbers slip. Here is what I built, what broke, and what I want to try next.

Four months after modeling three scenarios for US gas scarcity, all three are obsolete. The Strait of Hormuz is closed, 19% of global LNG supply is offline, and the era of "and" ended on February 28, 2026. Here's the revised thesis.

I built Conrad: a fully autonomous, self-improving AI agent that discovers investors, drafts outreach, processes inbound replies, turns user feedback into GitHub PRs, and updates itself every day. Here's the full technical breakdown of how it works, end to end.

A five-line bash script is devouring the old paradigm of AI-assisted development

What a time to be alive! I built an AI executive assistant in ~3 hours. Not because I needed one, but because I wanted one.

The United States is building two generational infrastructure booms simultaneously, and they're about to collide. AI datacenters and LNG exports are betting on the same finite resource: American natural gas.