Prototype Studio

The original product was a sixteen-module gamified course teaching an AI-native shipping method. It was built, it was coherent, and it answered a question the audience was not asking.

People who already know how to think about product did not need sixteen modules. They needed someone to sit with them for two hours and get the agent system actually running against their own repository — and then leave them with something that kept working on Monday.

So the course became the artifact and the working session became the product. Saying this plainly costs nothing and explains more than a launch post would: the pivot is the evidence that the method is real, because a method that never contradicts you is not being tested.

Working sessions are hands-on and specific to the participant's own codebase. Guides cover the parts that generalize — repository conventions, spec structure, review agents, what to validate on commit.

Agent-system setup is the piece people most often cannot do alone: standing up reviewer roles, decision logs, and the validation that makes an AI-assisted repository trustworthy rather than merely fast.

The audience is people who are fluent in the problem domain and slow at the shipping — not engineers looking for another framework. The measure of success is whether they ship something real afterward without help.

The site is live and the services are real. Feature work is paused while attention sits elsewhere in the portfolio, and the status says so rather than implying momentum that is not there.