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Agent telemetry

Agent telemetry is the running record an AI agent emits about the work it did and the tools it called. Security tools watch network traffic and logins, so agent work looks like ordinary app traffic. Without a record from the agent itself, nobody can reconstruct what that agent actually did.

Also called: agent observability, agent logging, agent traces, agent instrumentation, agent activity logs, AI observability

Updated

An AI agent doesn't break into anything. It logs in with a credential somebody gave it and uses the same web calls every other app uses. To a security tool watching the network, that's a normal day. The only place the agent's own choices show up is in telemetry the agent emits about itself.

What useful agent telemetry contains

  • Which agent ran, and under which identity

  • Every tool it called, with the arguments it chose

  • What each tool sent back, since that's what shaped the next step

  • Which request started the run, so one session can be followed end to end

  • Where the run stopped, and whether a person cleared it

Where teams get it wrong

They assume existing tools already cover it. The SIEM is collecting and the cloud logs are on, so surely the agent is watched. Those tools record that an API call happened under a valid credential. They don't record that an agent decided to make it, or what it read on the way there.

Here's a concrete one. An agent with a read credential pulls fourteen customer records over an afternoon. Every single call is allowed and every one looks like the app doing its job. The pattern only reads as wrong if something recorded that one agent, in one session, made all fourteen calls. Without that, there are fourteen ordinary log lines and no story connecting them.

The checkpoint has to sit between the agent and the tools it calls. That's the one spot where agent behavior is still visible as agent behavior.

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