Rodin
6af8a6ee10
Break the monolithic 3249-line findings file into 29 individual files, one per experiment. Each file is named YYYY-MM-DD-NN-slug.md for easy chronological sorting and discovery. No content changes — purely structural reorganization.
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Finding 5: Sonnet is fast and catches structural issues; GPT-5 is slow and catches semantic issues
Date: 2026-04-26 Task: Dual review across PRs #372, #375, #378, #380, #382 How we used them: Same pr-review skill, same context (diff + files + issue + AC), same sub-agent pattern. Only variable: model. Both got rich context. Both ran the full 7-phase review skill.
- Sonnet consistently finishes first, catches formatting, broken links, structural problems (missing sections, dangling refs)
- GPT-5 takes longer, catches meaning-level problems (verdict mismatches, classification inconsistencies, logical gaps)
- Takeaway: With identical rich context and identical instructions, the models naturally gravitate to different things. Sonnet is the structural reviewer; GPT-5 is the semantic reviewer. Both roles matter. Question: would Sonnet catch semantic issues if given a narrower "check for logical consistency" framing instead of broad review?