Mitchell Hashimoto recently described a shift he calls the building block economy: the most effective path to software is no longer a polished monolith, but small, well-documented components that others (increasingly agents) can assemble. His key observation: AI is okay at building everything from scratch, but it is really good at gluing together proven pieces.

That thesis has mostly been told with code libraries. But the same forces are hitting multimedia AI. The hard part of using a state-of-the-art image model, a video model, a TTS model, or a 3D reconstruction model was never the model. It was the integration: SDKs, weights, GPUs, input formats, polling. If each model were instead a documented, callable block, an agent could glue them together the same way it globs together npm packages.

The Hub hosts thousands of state-of-the-art models (a huge share of them open-weights), and most are deployed as interactive Spaces. As of now, every Gradio Space also exposes a plain-text agents.md that tells an agent exactly how to call it:

returns everything needed in one shot: the schema URL, the call and poll templates, how to upload files, and the auth hint: