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
1003 B
Markdown
18 lines
1003 B
Markdown
# Finding 7: Emerging role assignments (pattern, not conclusion)
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**Date:** 2026-04-26 (one day of intensive work — treat as hypothesis)
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- Opus (via Claude Code): complex generation needing deep project context.
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Rich context: CLAUDE.md, full codebase access, design docs. Broad mandate.
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- Sonnet: parallel volume work (5 subagents drafting simultaneously).
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Rich context per section, constrained output scope.
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- GPT-5: independent analytical review. Rich context (diff + files + issue).
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Best when task is bounded and explicit.
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- GPT-4.1 Mini: focused narrow analysis (bias detection). Minimal context,
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precise question. Cheap and fast.
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- **Takeaway:** The role assignment matters, but so does the context shape.
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Opus gets broad context + broad mandate. Sonnet gets broad context +
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narrow scope. GPT-5 gets rich context + explicit task. GPT-4.1 Mini gets
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minimal context + laser question. We haven't tested swapping these
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combinations — that's where the real learning will come from.
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