Jason A. Hoffman

I have started and sold several companies. I am still a technologist and an operator, but I now have more ways to help than I did when I was younger: investor, advisor, first customer, partner, recruiter of the person who should run it. Capital and time are both things I allocate now. Starting a company…

What is it about human beings that we keep arguing against Jevons’ paradox? In 1865, William Stanley Jevons published The Coal Question and observed that more efficient steam engines had not reduced Britain’s coal consumption. They had increased it. Efficiency lowered the cost of work done with coal, the lower cost admitted new uses, and…

A senior executive who joins a company still run by its founder often arrives with credentials, a playbook, a network, and a reflex: find what is broken and fix it. In a strong founder-led company, that reflex can destroy the very advantage the executive was hired to extend. Almost no one catches the mistake in…

A commitment to a course of action under certainty is a plan. Under uncertainty, it is a decision. Decision analysis is statistical at its foundation. This post is about the structure of what makes decisions hard, the recurring decisions that define a company’s trajectory, and what decision support could actually become.

KPIs are simple. That is their virtue and their failure mode. The tension is real: simple becomes simplistic, complex becomes complicated. The discipline is staying in the useful middle of both.

This is not a post about prompting. It is a post about thinking. The techniques I use with AI models are not new. Adversarial analysis, dialectical argument, Socratic questioning, pre-mortems, steelmanning, red teaming: these are critical thinking disciplines that predate computers.

In February 2025, Claude Code launched and I switched back to CLI and git. Within months, Codex CLI and Gemini CLI followed. The question shifted from “which model” to “how do I use all of them together.” Here is what a year of that looks like.

The number is always wrong in the same way. Burn-in failure rates are 3–8%. Total manufacturing attrition is 15–25%. In-service failure runs ~9% per year. Three different numbers measuring three different things.

I attended the GTC 2026 keynote in person. At the highest level, this keynote was more newly explicit than fundamentally new. Here is what I think matters most, and why.

Part 12 in the series. The hardest skill in engineering is not technical. It’s emotional. Most people cannot sit with not knowing the full state of things. The desire for control is the root of most bad architecture — in software, in organizations, and in life.