AI verification failure: What to do after Verify rejects it

A person holding two pages up to the light to compare them

After an ai verification failure, read Verify's findings, locate the failed check, revise the deliverable, then send the changed work through the relevant checks again. Record the result against the revision that was checked.

What should you do first after Verify rejects work?

Start with the findings, not with an edit. Read what Verify rejected and establish which deliverable and revision the findings refer to. A rejection is a result against the work that was checked, not a general verdict on the person or the whole project.

Separate what the finding says from what you think caused it. A failed requirement may point to a line, a missing detail, or a mismatch with an acceptance criterion. Your explanation for why it happened is an inference until the evidence supports it. Keep those two things distinct so you do not revise the wrong part.

Open the reviewable diff and inspect the exact lines called out. Brainis shows deliverables as a diff between old and new work, with inline threads and Verify findings on exact lines before the work counts as done. That gives you a place to compare the finding with the text it concerns. The Verify product page describes this review flow.

Confirm which revision Verify checked before you rely on the result. Keep the rejected revision available while you investigate and make changes. If the work has changed since the check, the earlier result does not establish whether the newer work passes.

For a detailed account of rejection handling, read the Verify rejections report. Treat the findings as evidence about the checked work. Do not fill gaps in the findings with a confident story about the cause.

How do you find the check that failed?

Trace each finding to the acceptance criterion or quality check it concerns. This keeps a rejection specific. It also makes the next edit easier to assess: you can tell what requirement the change needs to satisfy.

Use any exact-line finding to locate the affected part of the deliverable, then compare that part with the criterion. Ask whether the work fails a stated requirement, or whether the criterion itself is unclear or incomplete. Those are different problems. A revision can fix a failure against a clear criterion; an unclear criterion may first need a decision about what acceptable work means.

Brainis can turn your acceptance criteria into Verify checks, compose them into libraries, and enforce them by domain. Independent quality agents verify work against acceptance criteria and can reject it. This gives the reviewer a check to trace, rather than a broad impression to debate. The post on defining done for AI work covers how to make those criteria usable.

Keep verification separate from production. The producer of a deliverable does not solely verify it, and high-risk work uses a different model family. That separation matters because the person or agent that made the change may miss the same issue when checking it. Read why the agent should not grade its own work for more on that distinction.

If you cannot tell which criterion a finding concerns, do not guess and label the work fixed. Clarify the requirement or ask the responsible reviewer to identify the check. A clear path from finding to criterion makes the correction testable.

Two developers reviewing code together at one screen

How should you revise after an AI verification failure?

Make a focused change to the part of the deliverable tied to the failed check. Use the finding and the acceptance criterion to decide what needs to change. Avoid rewriting unrelated sections unless the evidence shows they also affect the failed requirement.

Then review the diff. Compare the rejected work with the revision and identify both what changed and what stayed the same. A small, traceable change gives the next reviewer a clear question to answer: does this correction meet the criterion? A broad rewrite can obscure whether the issue was addressed.

An ai verification failure is not resolved by making the document look more complete. It is resolved when the relevant requirement is met and the check can assess that work. If the finding points to missing support, add the support the criterion requires. If it points to a contradiction, correct the conflicting statements. If the criterion is unclear, settle that ambiguity before treating a wording change as a fix.

Brainis presents the changed work as a reviewable diff, so reviewers can compare old and new content and inspect findings on exact lines. Use that comparison to make the correction visible, not to claim that every edit is relevant. The Verify product page explains how the reviewable diff fits into checking work.

Before resubmitting, check that the revision still says what it needs to say and that the edit has not broken a nearby requirement. That is a review of the change, not proof that Verify will pass it. Let the relevant check decide whether the criterion is met.

What should you send through the checks again?

Identify which checks apply to the changed work, then send the revised deliverable through those relevant checks. Do not assume that every check is relevant to every edit, and do not skip a check that covers the requirement you changed. The acceptance criteria should guide the route.

Read the new findings when they arrive. The earlier rejection describes the earlier checked work; it does not tell you whether the revision passes. The new result may confirm that the correction meets the criterion, or it may identify an issue that remains. Treat that result as evidence about the revision actually reviewed.

If Verify shows a verified seal, confirm that it belongs to the exact revision under review. Brainis renders the seal only for the revision Verify checked. Changed work shows that it was verified at an earlier revision and has changed since, rather than displaying a stale seal. This distinction prevents an old check from standing in for a new one.

A recheck is useful when it answers a specific question: did the changed work meet the failed criterion? Keep the diff and the new findings together so the reviewer can see the correction and its outcome. The Verify product page and the Verify rejections report provide more context on the review and rejection process.

Do not treat a clean-looking diff as a pass. The relevant checks need to assess the revised work. If another check raises a separate issue, record it as a separate finding and follow its requirement rather than folding it into the original explanation.

A careful hand placing a seal of approval on a stack of work

What should you do next after the recheck?

Record the recheck result and the revision it applies to. Keep the finding, the relevant criterion, the correction, and the outcome together in the deliverable's review record. That gives the next person a way to understand what was checked and what changed.

If a check still fails, return to its findings and identify the remaining issue. Compare the new finding with the criterion and the latest diff. Decide whether the work still misses a clear requirement or whether the requirement needs clarification. Then revise the relevant part and run the applicable checks again.

If the relevant checks pass, keep that result with the checked revision. Do not carry the result forward as proof for later changes. When the deliverable changes, the review record should make that distinction visible.

Brainis records predicted and actual outcomes in the Decision Ledger, where they improve the next recommendation. Keeping the recheck outcome tied to the revision gives later reviews a record of what the check found and what followed. The memory product page and the post on writing predictions down offer related reading.

The close of an ai verification failure is not the moment someone says the work looks fine. It is the point where the relevant checks have assessed the revised work and the result is recorded against that revision. If a check remains open, keep the issue visible and name who will resolve it next.