[edunteman]

I've got a blog on this from the launch of Muscle Mem, which should paint a better picture https://erikdunteman.com/blog/muscle-mem

Computer use agents (as an RPA alternative) is the easiest example to reach to: UIs change but not often, so the "trajectory" of click and key entry tool calls is mostly fixed over time and worth feeding to the agent as a canned trajectory. I discuss the flaws of computer use and RPA in the blog above.

A counterexample is coding agents: it's a deeply user-interractive workflow reading from a codebase that's evolving. So the set of things the model is inferencing on is always different, and trajectories are never repeated.

Hope this helps

[bigwheels]

Still not clear - the tool calls come from the model, so what is being cached by Muscle Memory?

Also:

  After my time building computer-use agents, I’m convinced that the hybrid approach of Muscle Memory is the only viable way to offer 100% coverage on an RPA workload.

100% coverage of what?

I guess it'd be great if you could clarify the value proposition, many folks will be even less patient than myself.

Best of luck!