
AetherLAM
An un-sandboxed Large Action Model built to bypass browser l
Hey hackers, I wanted to share the live launch of AetherLAM! Most AI chatbots are locked away inside browser sandboxes. They can generate text, but they can't actually do anything natively on your computer.
AetherLAM uses a decoupled cloud-to-os architecture to break the sandbox. We host a high-speed transactional brain on an always-on PythonAnywhere cloud core to process intents via over-the-air Gemini API routes. It translates unstructured human speech into structured JSON task parameters, then dispatches them down to a native async companion app agent running locally on the user's computer to handle documents or wireless network scans instantly.
Compute tokens decrease ONLY upon verified task extraction success, and free trial accounts get 3 token shards automatically right at launch.
I'd love your brutal product feedback on the decoupled wire loops: https://globalintelpro.com
About
I became entirely frustrated with traditional AI chatbots being locked inside rigid browser sandboxes. They talk endlessly, but they cannot perform raw, native operating system tasks on local machine. I built AetherLAM

3 Comments
The decoupled cloud-to-local approach is interesting because it separates intent processing from actually performing the task on the machine. The important test seems to be how reliably that handoff works in real-world conditions without making users think about the architecture underneath.
Yeah you are right!
That’s a good distinction. I’d be curious to hear what you learn once people start using that handoff in real workflows.