Agent Interface is an open-source layer that gives AI agents a more efficient way to interact with computers by running local action-and-feedback loops.

This represents a crucial shift from simply building larger models to improving the tooling and interfaces models use to operate environments.

• –By caching or reusing learned interactions locally, the system mitigates the high latency and token costs typically associated with vision-based GUI agent frameworks.
• –Exploring "control in a world that doesn't pause" is an excellent forcing function for building robust, real-time agentic capabilities.
• –The project is well-positioned to capitalize on the growing demand for capable, autonomous desktop agents by providing a better abstraction layer.