AI Pulse · Under the Radar

Alibaba has released AgentSight as part of its open-source Anolis OS project. It monitors AI agent processes from the operating system level using eBPF, rather than requiring developers to add tracking code inside each agent.

That matters because unattended agents create a basic operational problem. They can make LLM calls, consume tokens, fail halfway through a task, or behave in ways nobody sees until a customer or employee reports an issue. AgentSight is designed to give teams visibility into token use, LLM call activity, and crashes without changing the agent’s own code. For businesses running agents built by different teams, vendors, or frameworks, that could remove a lot of the manual work involved in setting up oversight.

It’s very early, and the initial response is limited, so this is not proof that the tool is ready for broad production use. Still, the technical approach is worth watching. Monitoring at the kernel level could give operators an independent audit trail, rather than relying only on what the agent application chooses to record. This is the kind of thing we build into an AI command centre, where cost, activity, failures, and control need to be visible in one place.