Intent–Outcome Alignment for AI Agents
Your agent’s checks pass. We find the runs you’d still reject.
We match it with real users and the experts whose job it does — and turn their judgment into fixes that hold.
2-week pilotfixed fee, scoped firstfind nothing, it ends there
Specimen τ0417 · illustrative
An expert — someone who does this job — read the same run and rejected it in nine seconds. That gap is what we surface.
task“add rate-limiting to /export”
checks47/47 green — tests · lint · types · deploy
diff+312 −9 · 14 files touched · 3 unrelated
reviewreject — “works — and it rewrote the retry layer nobody asked for”
meantthe smallest change that adds the limit
“I saw it and knew — we never wanted that.”
“I’d never thought about it. Now I can’t unsee it.”
The marketplace
You bring the agent. We match both to it, stage the scenarios most likely to surface improvements, and ask the right questions.
reviewerconfirmedratingpay
rating follows confirmed findings · pay follows rating · illustrative
Reviewers are rated on findings that prove out — higher rating, higher pay. Trust is the product.
The pipeline
Every confirmed idea reaches you as feedback → why → what your agent looks like after. Then we build the harness change and verify it holds.
the match
your agent meets its users + expertsfirst improvement
feedback · why · after — you confirmreport + repairs
what changed · why · verifiedThe terms
A clean report says one thing: no false success found at our budget. A bound on our search — not a promise of perfection, and we don’t sell those.
The gap is the part you never wrote down — and the team that wrote the checks can’t independently falsify them. Your users’ experience of the agent isn’t visible from inside it.
More capability means more valid-looking paths through your checks, and more authority behind each unnoticed miss. The problem grows with capability instead of being solved by it.
People who do the job your agent does — software engineers for a coding agent, teachers for a teaching one — plus its real users. Findings that prove out raise a reviewer’s rating, and rating raises pay.
Nobody can honestly promise that. You get confirmed findings at a stated budget, a ledger of what was searched and not found, and the conditions that expire the evidence.
Traces, agent configuration, sandbox or staging access. We learn the pattern, never the secret.