Rodin
1b108ff66e
Full comparative analysis of GPT-5, Claude Opus 4.6, Claude Sonnet 4.6, GPT-4.1, and GPT-4.1 Mini on analytical tasks (not coding). Contents: - findings/ALL-FINDINGS.md — complete 3,249-line research log with all 29 findings, methodology notes, and open questions - prompts/ — 6 exact prompts used across experiments - methodology.md — experimental setup and evaluation criteria - open-questions.md — unanswered questions for future work - README.md — overview and summary table Key findings: - Cross-document consistency: Opus is 2.4x faster with more findings - Gap-finding: GPT-5 reasoning tokens find domain-specific gaps - Race conditions: Opus excels at temporal interaction reasoning - Bias detection: Signal-to-noise ratio > model capability - Adversarial analysis: GPT-5 exhaustive, Opus qualitatively different Signed-off-by: Rodin
48 lines
1.5 KiB
Markdown
48 lines
1.5 KiB
Markdown
# Prompt: Gap-Finding in Architecture Documents
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Used in Finding #9.
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## Setup
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- Single document (full text, no truncation)
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- Same focused analytical question to all models
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- No tools, no project context beyond the document
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- Temperature 0.3 for GPT-4.1/Mini, default for GPT-5
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## Prompt
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```
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You are a systems reliability engineer reviewing a failure modes document
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for a trading platform. Your task is to identify MISSING failure scenarios
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— things that COULD go wrong in this architecture but are NOT covered in
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the document.
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Focus on:
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1. Scenarios specific to THIS architecture (not generic "server could crash")
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2. Interactions between components that could produce unexpected states
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3. External dependency failures not covered
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4. Timing/ordering issues in the described sequences
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5. Recovery procedures that have gaps
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For each missing scenario:
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- **Scenario:** What goes wrong
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- **Why it's specific to this system:** Why generic monitoring wouldn't catch it
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- **Impact:** What state the system ends up in
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- **Why the document misses it:** What assumption makes this invisible
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## Document:
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[FULL TEXT OF failure-modes.md, 383 lines]
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```
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## Results
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| Model | Time | Output tokens | Reasoning tokens | Scenarios found |
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|-------|------|---------------|------------------|-----------------|
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| GPT-4.1 Mini | 16s | 2,003 | 0 | 10 |
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| GPT-4.1 | 24s | 2,575 | 0 | 15 |
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| GPT-5 | 45s | 8,565 | 6,656 | 14 |
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GPT-5 found the most domain-specific and actionable gaps despite finding
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fewer total scenarios than GPT-4.1. Quality > quantity.
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