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Notes on AI code review

Engineering write-ups, product decisions, and research from the team building Quorum. For shipped changes, see the changelog.

Product2026-05-02 · 6 min read

Why a panel of three beats one big reviewer

A single model trying to flag bugs, security risks, and architecture drift in one shot ends up doing all three poorly. Specialising the prompt — and arguing back from runtime failure modes — cuts noise dramatically.

By Quorum team

Recent posts

Engineering9 min

Deduping reviewer findings without losing signal

How we sort by severity, dedupe by (file, line, lowercased title), and only post inline comments on lines that map to a unified-diff position. Plus: what we threw out and why.

Quorum team2026-04-18
Research4 min

A confidence floor is the cheapest noise filter you have

Across 1,200 internal review runs, dropping findings below 0.75 confidence cut acknowledged-noise by 38% while removing fewer than 4% of accepted findings. The data, and the caveats.

Quorum team2026-04-04
Product5 min

AI review should be advisory by default

Why every Quorum review is posted with event:COMMENT — never request_changes — and how the advisory framing changes how teams actually use the panel.

Quorum team2026-03-19