50% of Your Users Don't Have Eyes

Dual-native design is a paradigm for building systems that serve both human and AI agent users simultaneously. It involves designing interfaces and abstractions to optimize experiences for both parties without treating one as an afterthought. Key aspects include schema-driven capability discovery, tiered autonomy for operations based on risk levels, and shifting the human role towards oversight rather than direct control. This approach ensures information parity between human and machine interfaces, making systems more efficient and adaptable in a world where AI agents are increasingly prevalent.

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