AI ships the code – the pipeline proves it works
The bottleneck of AI-assisted development is not writing code – it is proving the code works. I run this one myself: it is built on a client ticketing platform and on this very site, whose build loop shipped its last epic behind a 1,107-test end-to-end battery, 45 visual baselines and a 1.00 Lighthouse score measured in August 2026. So the proof is what we automated.
How it works
Four steps, and the fourth is a full stop. The loop proves its own work and then hands the merge decision back to a human.
A real browser, real data
An agent walks the affected user flows in a live browser against freshly seeded data – clicks, forms, auth tiers – and verifies the mutations in the database, not just the pixels.
The failing test comes first
For a found bug, a failing test is written first – and it must fail for the right reason, referencing the finding, before any fix is attempted.
Inside a fence
The fix may only touch an allow-listed surface; the failing test itself is byte-frozen so the fix cannot quietly rewrite the exam it is taking.
Merging stays human
Green gates plus an adversarial review panel produce a report bundle. Then it stops. Merging is a human decision – auto-merge is forbidden in code, not in a guideline.
What you gain
- Catches what unit tests structurally cannot: the flow, not the function
- Flaky findings die at a reproduce-gate (three runs, reseeded) before they cost anyone attention
- Every fix arrives with its own proof attached
- Undocumented user flows get discovered by persona-driven exploration and turned into reviewable candidate tests
Honest limits
- Runs against local and staging environments only – it refuses non-local databases in code
- Money flows, permission systems and migrations are hard-refused surfaces until safety is separately proven
- Honest status: the deterministic core of the autonomous fix loop is built and covered by 64 green tests; its first live run on a real finding is still gated on a cost approval. This card will say so until that changes
indicative, not a quoted delivery date
Who clicks through the app after your AI ships a feature?
Tell me on a 30-minute call – if the answer is you, that is the hour this pays back first.