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.
18 lines
979 B
Markdown
18 lines
979 B
Markdown
# Finding 5: Sonnet is fast and catches structural issues; GPT-5 is slow and catches semantic issues
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**Date:** 2026-04-26
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**Task:** Dual review across PRs #372, #375, #378, #380, #382
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**How we used them:** Same pr-review skill, same context (diff + files +
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issue + AC), same sub-agent pattern. Only variable: model. Both got rich
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context. Both ran the full 7-phase review skill.
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- Sonnet consistently finishes first, catches formatting, broken links,
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structural problems (missing sections, dangling refs)
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- GPT-5 takes longer, catches meaning-level problems (verdict mismatches,
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classification inconsistencies, logical gaps)
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- **Takeaway:** With identical rich context and identical instructions, the
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models naturally gravitate to different things. Sonnet is the structural
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reviewer; GPT-5 is the semantic reviewer. Both roles matter. Question:
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would Sonnet catch semantic issues if given a narrower "check for logical
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consistency" framing instead of broad review?
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