Who priority-parks background agents? An ops veteran on sharing one 16GB GPU between apps and agents
Powermadlux · reddit · 2026-10-22
A developer with 22 years in infrastructure runs production apps and local experiments on a single RX 6900 XT (16GB) via llama.cpp, and raises an overlooked agent-orchestration problem: an agent can plan five parallel tasks, but the hardware doesn't gain 5x capacity — real users compete with deferrable background work.
Policies he wants made explicit:
- Interactive requests take priority over background agent work
- Per-task limits on retries, elapsed time and model calls, including subagent calls
- Overloaded backends should trigger a deliberate wait/fallback/stop decision; timeouts shouldn't create more work
- Model switches must be visible in task records — a successful fallback doesn't guarantee the result still meets requirements
He asks whether others enforce such limits in the agent framework, a shared inference gateway, or both.
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