AI coding tools move fast — and every prompt quietly steers your logic somewhere new. ONNU reads what your code does today, compares it to what you actually intended, and hands you the exact correction. Back on course, in plain English.
Speed got you to a working app. Direction decides whether it's still your app.
Drift isn't a crash — it's a hundred small, reasonable-looking edits that add up to a product that no longer matches your intent. It doesn't show up in tests, because the tests were generated from the same drifting assumptions.
Each fix solves the ticket in front of it — and quietly rewrites a rule three files away.
You never wrote down "the way it's supposed to work," so there's nothing to drift from.
The first signal is a refund request, a double charge, or a support ticket you can't explain.
ONNU doesn't drown you in a checklist. It scans wide, surfaces only the disagreements, and gives you room to think — the way a good CTO would.
An agentic sweep extracts what each function truly does — pinned to quoted lines, not guesses.
A short, frontier-style interview asks only where your intent and the code diverge. No busywork.
For every gap, a tool-agnostic prompt you paste straight into your AI editor to steer it back.
Three columns, no jargon: what the code does, what you intended, and the verdict. Misaligned rows come with the fix attached.
Most tools tell you something's wrong. ONNU tells you, then writes the exact prompt to fix it — tool-agnostic, quoting the real code, ready to drop into Cursor, Claude Code, or whatever you build with. You stay in the driver's seat; ONNU just keeps you on the road.
Connect your repo, let ONNU map the drift, and walk away with corrections you can paste today.
Course-correct my code →