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About this paper
Jia Huang, Joey Tianyi Zhou
A two-dimensional framework is introduced for classifying AI agent design patterns, utilizing orthogonal axes of "Cognitive Function" and "Execution Topology" to provide a unified vocabulary. The framework defines 28 patterns, 15 of which are new, and establishes five empirical laws guiding pattern selection based on environmental constraints.
Key insights
- Cognitive Function and Execution Topology are orthogonal axes, confirming that architectural structure and functional capability can vary independently.
- Environmental constraints (e.g., time pressure, action authority, failure cost asymmetry, task volume) are critical determinants for selecting appropriate AI agent design patterns.
- The framework provides a durable, framework-neutral, and model-agnostic vocabulary for agent architecture, aiming to bridge functional and structural descriptions.
Summary by alphaXiv.
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