>> Excalidraw AI Proxy
Excalidraw is already good at one thing: turning a sketch into a structured visual language. The interesting part begins when that sketch is no longer just an image, but an interface. A diagram can become a prompt surface, a workflow map, or a command graph.
An AI proxy for Excalidraw would sit between the drawing and the model. It would interpret the diagram, classify the nodes, infer the intended action, and translate that structure into a tool call or a narrow instruction. The drawing remains the front-end. The proxy becomes the translation layer.
That feels useful because diagrams often carry intent that text does not. A box labeled review, a line pointing to gate, and a second line to approve are not just shapes. They are an executable workflow. The same goes for architecture sketches, agent plans, release flows, and command surfaces.
The strength of this idea is that it keeps the model out of the center. The diagram provides structure. The proxy provides meaning. The model provides interpretation. That is a much better fit for local tools than letting the model invent an entire workflow from thin air.
The real design challenge is not whether the model can read the canvas. It is whether the system can turn the canvas into something deterministic enough to trust. If the proxy can emit a clear schema — nodes, edges, intent, action, and confidence — then the rest of the stack becomes much easier to automate.