Two consumer products in production, built and operated by self-improving agents on one operating system Johnny designed. One person sets the direction; the machine ships, fixes, deploys and gets better every day. See for yourself ↓
larry match hit a review wall on a thursday. by friday morning he'd sent the first prompt for what you doing tonight — a locals-first nightly events paper for new york. the repo, the board, the domain and the deploy landed the same day, because the operating system that built larry match was already running. he just pointed it at a new product.
don't worry about larry. he's coming back soon.
Automated daily algorithmic options trading — multi-factor models, Monte Carlo simulation, backtesting, automated execution, real risk controls. Built like a real desk. It didn't do too well paper trading, so he moved on to bigger and better things.
The Evidence-Native PMO — an AI-native program office for a Fortune-class financial-technology transformation. Eighty knowledge-transfer reports in week one. The honest part: the gap between what's possible and what enterprises are structured to absorb is enormous. That gap is the opportunity. He's ready when they are.
Johnny moved from LA to New York. The movers wanted an inventory spreadsheet. He one-shotted an inventory app the same afternoon — and offered it to the moving company. That's the real point: the harness already exists. Flipping the switch on a new app takes him a day, not a quarter.
Old enough to remember the free-range internet. Young enough to be AI-native. Fifteen years operating through economic cycles, media environments, and platform shifts — before the tools finally caught up to the ambition.
A decade in management consulting: five countries, 100-person programs, Fortune 500 technology transformations from the inside — strategy through delivery.
Columbia MBA. Runs a 25-person firm — full P&L, payroll, the whole machine. Chief of staff to the CTO of a 24,000-person company.
Builds a pearl jewelry brand from scratch — product, sourcing, sales. Runs a grassroots campaign — 2,000 doors knocked, 4,000 calls made. Determination, grit, building from the ground up.
AI rewrites what one person can build. He teaches himself the entire stack — design, code, infrastructure, agents — and becomes the expert other experts call.
All of it since March 2026. Classical software-cost models (COCOMO) price this output at 100+ person-years. Bumble runs 300+ engineers. A dating-app MVP alone is quoted at a 5–7 person team over 8–14 months — for swipe-and-chat. The models were written before someone handed one stubborn consultant a fleet of AI agents.
Maybe you hire him. Maybe he hires you. Maybe you invest. The direction matters less than the momentum — share the expertise, build the thing, make everyone involved more successful.
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