A single “review this PR” prompt gets distracted. PR Quorum splits review into Correctness, Security, and Architecture so each reviewer can stay sharp and the aggregator can keep the final comment clean.
The obvious shape for an AI code reviewer is one prompt, one model, one pass over the diff. It looks tidy in a demo. In real repos, it gets distracted. A generic "review this PR" prompt asks the model to juggle bugs, security, design taste, tests, framework conventions, and style at the same time. The loudest change tends to win.
On a refactor PR, a single reviewer often notices naming, extracted helpers, and maintainability shape. That is useful, but it can crowd out the off-by-one in a loop bound or the unsafe input that crosses into a query builder two files later. Those need a different stance: adversarial, runtime-first, and less impressed by tidy abstractions.
The biggest product lesson is that maintainers do not want three separate AI review posts. The dedup-and-aggregate step matters as much as the parallel fan-out. Two reviewers flagging the same line is a strong signal; we sort it toward the top. Three reviewers each picking different battles can become overwhelming, so PR Quorum caps inline comments and keeps the rest in run history.
A panel beats a generalist when the work splits cleanly into specialities. Code review does. Most other reasoning tasks do not — be careful about copy-pasting this pattern.
If you are building reviewer tooling: start by writing the focus lists, not the prompts. The prompts fall out of the focus lists, and the focus lists are what your maintainers will actually argue about.
PR Quorum turns specialist reviewer output into one clean GitHub review, with noise controls and predictable usage caps.