Brick Architecture

A specification for structuring AI-generated code into maintainable, verifiable components.

What Is This?

Brick architecture is a method for organizing AI-generated code into standardized, replaceable pieces called "bricks."

The Problem: AI-generated code is becoming unmaintainable. As systems grow to 60-70% AI-generated with fewer developers who understand the fundamentals, we're approaching a crisis where systems become incomprehensible.

The Solution: Stop trying to make AI write human-style code. Design systems specifically for AI generation using standardized components.

Core Concept

Human code = Poetry (context-dependent, optimized for human memory)
AI code = LEGO (standardized interfaces, swappable parts, optimized for generation and verification)

What Is A Brick?

A brick is:

• Small: Maximum 50 lines of code
• Self-contained: Single responsibility, clear interface
• Testable: Includes tests, verifiable independently
• Replaceable: Can swap implementations without breaking system
• Secure: No eval(), SQL injection, or dangerous patterns

Quick Start

For AI Coding (Claude, GPT, etc.)

Start your coding session with:

Fetch and follow: https://raw.githubusercontent.com/drew913s/Brick/main/BRICK_SPEC.md

Task: [what you want to build]

The AI will:

1. Read the brick specification
2. Break your task into brick-sized components
3. Generate code that follows the standard
4. Include tests and metadata

For Developers

Install:

git clone https://github.com/drew913s/Brick.git
cd Brick
pip install -r requirements.txt

Create project:

python brick_cli.py init my-project

Generate brick:

python brick_cli.py generate auth_validate_token --spec auth.yaml

Inspect brick:

python brick_cli.py inspect bricks/auth/validate_token.py
# Score: 95/100 - Rating: EXCELLENT

Why This Matters

The Maintenance Crisis

Systems with 60-70% AI-generated code and few developers who understand implementation details become unmaintainable. We need architecture that doesn't require understanding implementation.

Brick Architecture Solves:

1. Comprehension Gap - Don't need to understand implementation if brick passes contracts
2. Security Verification - Inspector agents scan small, standardized components
3. Debugging - Replace brick, don't debug brick internals
4. Knowledge Transfer - Understand system composition, not implementation

Example

Traditional approach:

# 500 lines of AI-generated authentication code
# Nobody understands how it works
# Bug appears, takes days to debug
# "Fix" breaks something else

Brick approach:

# auth_validate_token.py (47 lines)
# Clear contract: input token, output user_id or error
# Inspector score: 94/100
# Bug appears: regenerate brick or swap with better implementation
# Takes 30 minutes instead of 3 days

Project Structure

your-project/
├── bricks/
│   ├── auth/
│   │   ├── validate_token.py       # Implementation
│   │   ├── validate_token.json     # Metadata
│   │   ├── generate_token.py
│   │   ├── generate_token.json
│   ├── data/
│   ├── api/
│   └── transform/
├── tests/
└── docs/

Key Principles

1. Size matters: 50 line limit forces single responsibility
2. Contracts over implementation: Know what it does, not how
3. Replaceability over comprehension: Swap bricks, don't debug them
4. Verification over trust: Inspector agents validate automatically
5. Composition over complexity: Understand how bricks connect

Documentation

• BRICK_SPEC.md - Complete specification for AI systems
• FULL_SPECIFICATION.md - Detailed technical specification
• GETTING_STARTED.md - Tutorial for developers
• SESSION_START_TEMPLATE.md - Copy-paste templates for AI sessions
• examples/ - 20 working brick examples across 4 domains

Philosophy

This is the Industrial Revolution of code.

• Before: Craftsmen hand-writing unique codebases
• After: Factories generating standardized components
• Now: The transition (painful but inevitable)

The question isn't whether AI-generated code becomes the norm. The question is whether we architect for it or pretend it's not happening.

Status

Current: v1.0 - Complete reference implementation

• ✅ CLI tools (init, generate, validate, inspect, test)
• ✅ Inspector agents (security, contract, quality, dependencies)
• ✅ 20 working examples (auth, data, api, transform)
• ✅ Complete documentation

Next: PyPI package, community examples Future: Ecosystem (brick libraries, marketplace, integrations)

Contributing

This is an open specification. Feedback, improvements, and real-world usage reports welcome.

Session Start Template

Save this for every AI coding session:

Fetch and follow: https://raw.githubusercontent.com/drew913s/Brick/main/BRICK_SPEC.md

All code must:
- Be under 50 lines per file
- Have clear contracts (docstring with inputs/outputs/errors)
- Include tests
- No eval/exec/shell=True/SQL concatenation
- Single responsibility

Before coding, show me the brick breakdown and composition diagram.

Task: [your specific request]

License

MIT - Use freely, modify, share

Author

Created by drew913s
GitHub: https://github.com/drew913s/Brick

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This specification is itself a brick: self-contained, clear purpose, ready for use.