I am building a terminal UI for self-hosted AI agents on Jetsons and other edge devices with unified memory.

The reason I started it was that most local agent harnesses seems aimed at machines with plenty of RAM and a stable internet-connected developer environment. On Jetson-class hardware, the annoying problems are different: context growth eats memory, sessions break, models may fit but leave very little headroom, and a lot of tools assumes cloud access.

Recent additions include:

- air-gapped mode - automatic context condensing under memory pressure - persistent memory files and /memory controls - harness modes for chat/code/review/debug workflows - replayable traces for evals/debugging - multimodal local image input - OpenTelemetry support

I’d love for you to try it out. The code is up on GitHub, and contributions/roasts of my memory management are very welcome. On a 8GB, I got the latest Qwen3.5-9B running (it just about fits in the memory).

Contributions are welcome ofc. Github: https://github.com/L-Forster/open-jet