From signal to real-world impact.
A disciplined, end-to-end sequence — and the roster of specialised AI profiles that runs it, with human judgement setting the boundaries.
Discover
Problems are sourced, not invented. The first ones came from my own desk — the admin that ate the same hours every week. The rest come from operators complaining about something specific, unprompted, and from the gap between what a market says it wants and what it already pays for.Leaves this stage: a written problem statement, and who has it.
Verify
Independent research against the claim. Desk research, pricing teardowns, and conversations with people who have the problem now. The question is narrow: does someone already pay to solve this, badly?Leaves this stage: evidence, or a documented reason to stop.
Challenge
A red team attacks the case before any code is written, and it can stop the venture outright. Only written evidence against the specific objection restarts it — not a better argument, and not conviction.Leaves this stage: the surviving assumptions, named.
Build
The minimum credible product — credible meaning a real user could run their real work through it, not a demo. Scope is whatever tests the surviving assumptions fastest, and most of the feature list gets deleted here.Leaves this stage: something in a customer’s hands.
Deliver
Real users, real support, real failure modes. This is where most assumptions die and the useful ones get sharper. Nothing graduates on projections.Leaves this stage: outcomes a customer would confirm.
Learn
What worked becomes reusable — a pattern, a component, a piece of the operating system. What did not gets written down so the next venture does not pay for it twice.Leaves this stage: a compounding asset, not a post-mortem.
A team of specialised AI agents, working as one.
Ten profiles, each with a narrow remit and a defined handoff. One orchestrator holds the sequence together.
Find opportunities worth building.
Turn insight into real traction.
Deliver, review and compound.
Agents propose. A person decides.
The operating system is an accelerant, not an authority. Agents gather evidence, argue against each other, draft and build. They do not get to decide what SUNVEX ships, what it charges, or what it says to a customer.
Three decisions never leave the human. Whether a venture advances a stage. What a customer is promised. What gets spent.
Those three are not on the list because the model is bad at them. They are there because being wrong about them is unrecoverable, and nothing in the model carries the consequence.
Everything else is delegated on purpose — that is where the speed comes from — and every delegation leaves a written trail, so a decision can be audited after the fact rather than reconstructed from memory.
What ten agents are good at, and what went back to a person