Rodin
9d0a94bd68
New analytical lens tested on gargoyle order-state-machine.md: - GPT-5: 15 findings (most CRITICAL issues, exhaustive field analysis) - Opus: 14 findings (state lifecycle focus, implementation mechanisms) - Sonnet: 10 findings (fast but shallow) Key insight: "unstated constraints" finds what's IMPLIED but not stated, distinct from gaps, race conditions, or ambiguities. GPT-5 is best for catching CRITICAL data integrity constraints; Opus for state machine implementation details.
Model Findings — Analytical & Research Work
Tracking what actually works (and doesn't) when using AI models for research, analysis, bias detection, and document review — not coding.
Started: 2026-04-26
Context
We use multiple models in different roles: Claude Code (Opus/Sonnet) for generation, Sonnet + GPT-5 for independent dual review, smaller models for focused analytical tasks. Most public discussion is about coding. We found almost no published methodology for using models in analytical research tasks (searched 2026-04-26). That gap is why we're tracking this.
Each experiment lives in its own file. See individual finding files below.