majiayu000 Pattern Synthesis
Purpose
When you run N instances, you get N outputs. Most will be different.
Pattern synthesis asks: What's the same across all of them?
What patterns persist even when the specific details change?
The Key Insight
Specific answer: "The answer is 42" Pattern: "The answer is always the answer when you ask the right question"
The pattern is more robust than the specific answer.
Core Pattern
Instance 1: X₁ ─┐
Instance 2: X₂ ─┼─→ Pattern Extractor
Instance 3: X₃ ─┤ (what's the same?)
Instance 4: X₄ ─┘
Result: "All outputs have property P"
"All outputs follow rule R"
"The common thread is C"
Key Features
- Invariant Detection - What doesn't change?
- Structure Extraction - What form is repeated?
- Noise Filtering - What's signal vs. noise?
- Meta-Pattern Recognition - Patterns about patterns
- Generalization - From examples to principle
Implementation
See: .claude/skills/pattern-synthesis/pattern_extractor.py
Examples
Input: 4 different solutions to a problem Output: "All solutions follow this architectural pattern"
Input: 6 different explanations of a concept Output: "Core idea is X, the explanations just dress it differently"
Input: 10 different approaches to the same goal Output: "No matter the path, you have to pass through these 3 gates"
Payment Anchor
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