The GPU/compute telemetry feels a little too superficial for an IDE whose whole premise is running agents in parallel. Once you have ~10–15 concurrent sessions across machines, I’d really want per-agent resource attribution rather than just aggregate CPU/RAM/GPU stats. Ideally something like GPU utilization, VRAM consumption, process-level memory, thermal throttling, and inference/compute saturation over time.
The other thing I’ve noticed is that the spatial canvas starts becoming its own resource-management problem at scale. A 2D representation is great for reducing context switching, but once you have dozens of terminals emitting high-frequency updates, the UI needs aggressive virtualization/backpressure or you end up trading terminal-tab chaos for rendering/event-loop contention.
Would also love configurable polling intervals + event-driven telemetry instead of periodic system metrics, and some kind of resource budget per agent so one runaway process doesn’t starve the rest of the workspace.
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The GPU/compute telemetry feels a little too superficial for an IDE whose whole premise is running agents in parallel. Once you have ~10–15 concurrent sessions across machines, I’d really want per-agent resource attribution rather than just aggregate CPU/RAM/GPU stats. Ideally something like GPU utilization, VRAM consumption, process-level memory, thermal throttling, and inference/compute saturation over time.
The other thing I’ve noticed is that the spatial canvas starts becoming its own resource-management problem at scale. A 2D representation is great for reducing context switching, but once you have dozens of terminals emitting high-frequency updates, the UI needs aggressive virtualization/backpressure or you end up trading terminal-tab chaos for rendering/event-loop contention.
Would also love configurable polling intervals + event-driven telemetry instead of periodic system metrics, and some kind of resource budget per agent so one runaway process doesn’t starve the rest of the workspace.