claw
8338ae3019
Tests GPT-5 → Opus critique+extend pipeline on dtbp-margin-call.md. Key results: - Ensemble produces 56 unique findings vs 43 (GPT-5) or 28 (Opus) alone - Zero full disagreements — GPT-5's coverage is reliable signal - Critique phase (severity calibration) more valuable than extension phase - 28% more tokens for 30% more coverage + structured prioritization - Answers open question about adversarial ensemble value
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.