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