Make the Reviewer Prove the Finding

Every finding needs four parts: the changed behavior, the consequence, a way to reproduce it and the smallest decision that can resolve it. The reviewer should point to the relevant change and explain what can now happen that should not, or what can no longer happen that should.

Start with the consequence because severity labels are not explanations. A comment that says a function may race gives the builder a theory. A comment that shows two requests can overwrite the newer value gives the factory a claim it can test. The difference is not more prose. It is a path from the change to an observable failure.

Keep the reproduction beside the claim. Name the starting state, the action and the result. If the reviewer cannot reproduce the concern, it should say which assumption still needs proof instead of presenting suspicion as a release blocker. That preserves useful doubt without pretending the evidence is complete.

A plausible warning is not enough because a builder can spend hours repairing a story that the code never tells. AI reviewers can produce convincing explanations at the same speed builders produce changes. If every convincing explanation becomes mandatory work, review turns generation speed into rework speed.

This does not mean dismissing uncertain findings. It means routing them honestly. Confirmed failures can block the change. Unconfirmed risks can trigger a focused test, a product question or a separate investigation. Your AI reviewer needs a scope limit because unrelated or unproved concerns should not quietly expand one change until nobody can tell what it was meant to deliver.

The reviewer also needs to show that the issue came from the proposed change. Existing defects matter, but attaching them to the nearest pull request hides ownership and corrupts the review record. Compare the candidate with the accepted baseline under the same conditions. If both fail, open owned work unless the existing failure makes this release unsafe.

The release policy decides whether a finding blocks, and a person owns that policy. The reviewer supplies evidence. It should not invent authority from the confidence of its own wording or lower the standard when the builder offers a persuasive explanation.

Map recurring consequences to explicit gates. A demonstrated permission bypass, lost write or broken required path can stop the line automatically. A disputed product behavior should go to the person who owns that decision. A maintainability preference can remain advice unless the repository has already made it a rule.

That separation keeps the reviewer useful without making it sovereign. The proof must outrank the builder, but proof also has to answer to an accepted definition of correct. A second model does not get release authority merely because it speaks after the first one.

Keep AI review from becoming noise by measuring findings after the comment is written. Record whether each one was reproduced, accepted, dismissed or turned into different work. Then use those outcomes to narrow prompts, routes and gates instead of asking the same reviewer to be more careful next time.

Repeated false alarms need a changed boundary. Exclude a generated surface, supply the missing architecture rule or require a reproduction before the comment reaches the builder. Repeated confirmed misses need a new check or a different review route. The useful unit is not comments produced. It is consequential defects caught before release without burying the line in avoidable repair work.

Do not reward a reviewer for volume. Reward the route for decisions that become clearer. A green gate can still miss the change, so preserve what the reviewer inspected as well as what it concluded. A finding only earns authority when the factory can show the changed surface, the evidence and the rule that gave the evidence consequence.

Engineers stop spending their review time translating vague alarms into possible bugs. The factory handles reproducible inspection, routes ordinary failures back to the builder and retains the result. People take the calls that machinery cannot: whether the intended behavior is right and whether an unresolved consequence is acceptable.

That is the standard Gunner Technology recommends: no naked warning labels, no severity without consequence and no blocker without a route to proof. Make the reviewer show its work. Then let the release policy, not the reviewer's tone, decide what happens next.