I spent 14 years building digital products before I started Supergood — enough time in standups, roadmap reviews, and "quick syncs that ran an hour" to develop a very specific allergy: watching smart, capable people spend their days on work that shouldn't require a human anymore. Copy-pasting between spreadsheets. Building reports nobody reads. Waiting on a handoff that a well-designed system could clear in seconds. That allergy is the whole reason this company exists.
Where the experience comes from
Product roles across travel, live entertainment, and consumer hardware — different industries, but the same underlying problem everywhere: good people, buried in process that outgrew its usefulness years ago.
What carries over from all three isn't a specific technology — it's judgment about which problems are actually worth solving. AI can automate a report. It can't tell you which reports matter, which workflow is a genuine bottleneck versus a symptom of something else, or when the honest answer is "don't build this." That judgment is the part of consulting that doesn't show up in a tools list.
Why Supergood, and why now
Two things are true at once in 2026: most teams are still drowning in the same manual busywork they were five years ago, and most "AI agent" pilots die in the demo stage because nobody built the architecture, evals, or guardrails to let them run unsupervised. Supergood exists to fix both — sometimes in the same engagement. The name is a small joke about being pretty good at things, said with a straight face until people start believing it, which turns out to be a decent description of consulting in general.
How I work
Every engagement follows the same shape: audit honestly (including telling you when the answer is "you don't need this"), build with the tools you already pay for wherever possible, and govern what ships so it survives contact with real data and real stakes — not just a demo. Pricing is flat and published, not a mystery you have to book a call to learn. See the full breakdown on the AI Consulting page.
What I write about
The blog is where the actual expertise lives — 90+ posts on the stuff that determines whether an AI agent survives production: architecture decisions, eval design, guardrails, observability, cost control, and the failure modes nobody puts in the launch announcement.