What you deploy
The research-discipline layer from my trading platforms, generalized. You tell it what you want to study — the instruments or data, the hypotheses, how you’ll measure them — and it builds the scaffolding to test them without fooling yourself.
What it does for you
It stops you from talking yourself into an edge that isn’t there. Every idea starts as a pre-registered hypothesis with kill criteria written down in advance. It gets backtested, then forward-tested on fresh data in a shadow tier, and only graduates once it clears gates you set before you saw the results.
What you can build from there
Trading is my proven use case, but nothing about the harness is trading-specific. Any domain where you’re tempted to trust a pattern too early — research, ops experiments, product bets — can run through the same register-test-gate loop.
Deployment shape
A repo plus a config that describes what you’re researching and where the data comes from.
Where it stands
In the lab. This is the biggest lift of everything here — pulling the discipline out of my trading code and making it domain-agnostic is real work, and it’s honestly still in progress. No overpromises: join the waitlist and I’ll show you the generalization as it comes together.