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Fractal Architecture

> patterns_repeat_at_every_scale()

Build AI-friendly codebases through self-similar patterns. When structure repeats at every level - files, functions, modules - AI understands instantly and suggests correctly.

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Expansion Guides

// from chaos to self-similar elegance

01

Why AI Loves Consistent Patterns

Pattern recognition at architectural scale

AI models excel at pattern recognition. When your codebase follows fractal patterns - same structure from functions to modules to services - AI predicts correctly without extensive context. Learn why consistency beats cleverness.

Pattern Recognition Consistency AI-Friendly Code Predictability
02

Extractable Components: The Fractal Test

Can you copy-paste this to a new project?

The fractal test: if you can't extract a component cleanly, it's not fractal. Learn to build self-contained units that work anywhere, use dependency injection naturally, and make AI suggestions transferable across contexts.

Component Design Extraction Test Self-Containment Portability
03

Scaling Patterns Across Your Codebase

From single file to microservices

Once you establish patterns that work at one scale, replicate them everywhere. File structure mirrors module structure mirrors service structure. AI learns once, applies everywhere. Build scaffolding tools to enforce consistency.

Scaling Patterns Structure Replication Scaffolding Enforcement

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