PROOF
Real proof vs. green checkmarks
Do your tests execute the code, or just assert against mocks?
Running coding agents in parallel is native now. Trusting what they produce is the part the tooling doesn’t solve. Plumbline is the verification layer that keeps them honest.
Every test asserted against a mock. None of them ran the code. It shipped broken anyway — and no dashboard ever showed it. That quiet gap is exactly what we measure.
A teardown of your agentic build that tells you exactly where you’re exposed — and how to fix it. The whole engagement runs through a relay you control. We never touch your infrastructure or your data.
Do your tests execute the code, or just assert against mocks?
Does what your agents committed actually match what you meant to build?
Can a fresh session reconstruct the truth, or is it locked in one person’s head?
Where can an agent touch sensitive code or data with no human in the loop?
Is there a single mechanical check that stops a bad change before it ships?
Are your parallel agents truly isolated, or quietly clobbering each other?
Does a fresh clone with no cache build and migrate from zero — or does it only “work” on a machine that’s already warm? The seam where a control passes every test, then never runs on the real production build.
Would a broken build actually turn this test red? Are the proof’s data preconditions established, not assumed — and is there a case that fails if the capability is missing? A check that can’t fail isn’t proof; it’s decoration.
What’s verified, what isn’t, and precisely where you’re exposed.
What to fix first, ranked by risk and effort — yours to keep.
We walk your team through every finding, line by line.
The same blind spot keeps surfacing — each time the suite was all green, and each time the real defect sat one boundary past what the tests actually exercised. Two of them:
43 passing tests, every one asserting against a mock. Nothing executed the code against a real database. It shipped broken — and no dashboard ever showed it.
53 passing tests on a migration that switches on row-level security — tenant isolation, the control that keeps one customer’s data away from another’s. The tests checked the schema’s shape; none ran the migration against a live database. On a clean production build it would have failed and rolled the whole thing back — no isolation, discovered at go-live.
Three ways a green pipeline lies to you: a proxy-coverage gap — your test hits a mock or a stand-in while the real driver behaves differently; a reproducibility gap — it “works,” but only on state a clean rebuild can’t reproduce; and a falsifiability gap — the test passes, but nothing about a broken system would have turned it red. The Drift Audit is built to surface all three.
Ask any green check one question: what would I have seen if this were broken? If the answer is “the same thing,” the check is decorative.
Plumbline’s method comes from running a HIPAA-grade, verification-first agent build system — a no-shell architect that physically can’t fudge state, live-execution proof on anything that touches data, and a human gate on every dangerous change. We understand high-trust stakes from the inside, not from a checklist. And because we never hold your systems or data, the rigor is built into how we work, not bolted on.
The most recent proof: an eleven-session build of a HIPAA-grade, multi-tenant system — Postgres row-level security for tenant isolation, JWT-to-tenant auth, and a deployed service that proved it end-to-end against real Postgres: same-tenant read, cross-tenant isolation, fail-closed denial, zero mocks. That’s the layer that, built wrong, leaks one practice’s patient data into another’s — not glamorous, not the product, and the thing you can’t retrofit.
A plumb line checks against a true vertical — not an eyeballed guess. We test against the true reference, not a convenient proxy.
If not, that’s worth fixing before it costs you.
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