A controlled experiment tested writer-reviewer pipelines using Claude Opus 4.7 and Codex GPT-5.5 on 116 Python tasks from LiveCodeBench. Claude alone scored 91.4%, but having Codex review its output dropped accuracy to 82.8% — Codex fixed only 3 of Claude's failures while breaking 13 correct solutions. The reverse pairing (Claude reviewing Codex) improved results. The key finding: hierarchy matters in multi-agent setups, just like in human teams — a less capable model reviewing a more capable one degrades quality. Adding a second reviewer also more than doubled cost ($0.19 to $0.44 per task) and nearly tripled latency (38.5 to 112.4 seconds), making the tradeoff context-dependent for engineering leaders.
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