| --- |
| license: apache-2.0 |
| language: |
| - en |
| pretty_name: AI System Patterns |
| tags: |
| - ai-systems |
| - agents |
| - orchestration |
| - ai-agents |
| - system-design |
| - world-models |
| - validation |
| - interoperability |
| size_categories: |
| - n<1K |
| --- |
| |
| # AI System Patterns |
|
|
| A compact reference dataset of reusable architectural patterns for modern AI systems. |
|
|
| The dataset focuses on practical system-design concepts across AI agents, orchestration, memory, validation, observability, interoperability, world models, Physical AI, data pipelines, and production operations. |
|
|
| Each row contains: |
|
|
| - `pattern` |
| - `category` |
| - `description` |
| - `components` |
| - `use_case` |
| - `complexity` |
|
|
| ## Example |
|
|
| ```json |
| { |
| "pattern": "Model Routing", |
| "category": "Orchestration", |
| "description": "Routes each request to the model best suited for the task based on capability, latency, cost, modality, or policy.", |
| "components": ["router", "model registry", "evaluation signals", "fallbacks"], |
| "use_case": "Multi-model AI systems", |
| "complexity": "medium" |
| } |
| ``` |
|
|
| ## Intended Uses |
|
|
| - AI system architecture references |
| - taxonomy experiments |
| - lightweight classifiers |
| - retrieval and search demos |
| - documentation examples |
| - agent architecture exploration |
| - educational tools |
|
|
| ## Limitations |
|
|
| This is a curated reference dataset, not a benchmark and not a comprehensive taxonomy of all AI system architectures. The `complexity` field is intentionally approximate. |
|
|
| ## License |
|
|
| Apache-2.0 |
|
|
| ## Maintainer |
|
|
| Published by **ai-systems** as a practical reference dataset for AI systems and agent infrastructure. |
|
|
