Real data decides if a project lives, not opinion. This is mission control for the whole portfolio: what's live, what got killed, and honestly why. Every number here is real.
Six independent instruments scan a repo in an isolated, no-network sandbox, then place it on the real distribution of production code — an honest 0–100 score with a percentile, a shareable scorecard and a README badge. Everyone vibecodes. Nobody measures. We do.
A security proxy in front of your LLM calls — catches PII, prompt-injection and budget overrun before they ever reach the model. Try it live on the page: paste a prompt with an SSN and watch it get blocked in real time.
Paste your support tickets, get the recurring UX friction behind them — scored by severity, with action items.
Paste a code snippet, one model rewrites it, a second model independently audits the result and flags what it disagrees with — before that change ships to your repo.
Paste your HTML before and after a UI change plus the selector that broke — AI semantically re-locates the element and tells you exactly how confident it is, honestly.
Paste your network-device inventory — it ranks the fleet by certificate-expiry risk, then writes the exact vendor/model renewal procedure for the one that fails first. Never touches your hardware.
A circuit breaker for token spend — hard-stops a runaway agent loop before it drains your API budget overnight.
SMS-first hiring for restaurants — a QR code on the window becomes a screened candidate in minutes.
One roadmap for a game release across Steam, PlayStation, Xbox, Switch and mobile — every store deadline in one shared timeline.
Records your screen and voice while you work, then turns it into a finished, numbered SOP document with the screenshots already annotated.
Photograph your fridge, get a recipe. People genuinely used it — none ever asked for more. The lesson, written down for the next build: a free-access offer doesn't earn an email; only a real value exchange does.
Every project, dead or alive, leaves one written lesson the next one has to apply. Nothing dies without teaching.
Build fast, on purpose. A small AI-driven process ships a working demo, not a mockup — real API calls, real data, day one.
Put it in front of real people. No paid ads until something proves itself organically — communities, not campaigns.
The data decides, not a hunch. A fixed, written threshold set before launch, so nothing moves the goalposts afterward.
Kill it or grow it — and write down why. Every outcome leaves a lesson the next project inherits.