You can't secure an AI agent you can't see
AI agent observability means knowing what your agents did: every tool call, command, file read, and API request, as it happens, not stitched together after something breaks.
AI agent observability is seeing what autonomous agents are actually doing at runtime. An application log tells you an agent ran. Observability tells you it read three files, called two APIs, and tried to write somewhere it had no business writing.
For agents that touch real systems, this visibility is the foundation. You can't write policy, catch abuse, or pass an audit for behavior nobody captured.
What AI agent observability should capture
Useful observability records the actions an agent takes, not just the prompts and completions that led to them:
- Every tool call, its name, arguments, and result, logged as a structured event.
- Shell commands, file reads and writes, network and API requests.
- Which agent, which session, and which policy decision applied.
- Whether each action was allowed, blocked, or held for approval.
Observability without leaking secrets
The catch with capturing everything is that agent traffic is full of secrets: tokens, keys, private data. Log it naively and your observability store becomes a breach waiting to happen.
Prismor redacts secrets at the source, before events leave the machine, so you get complete visibility without opening a new place for credentials to leak.
From observability to control
Prismor captures agent activity as a structured, searchable event stream at the tool-call boundary, the same boundary where it enforces policy. What you can see, you can also govern, block, and prove later in an audit.
Frequently asked questions
What is AI agent observability?
Seeing what AI agents do at runtime: every tool call, command, file access, and API request, captured as structured, searchable events you can use to understand, secure, and audit their behavior.
How is agent observability different from LLM observability?
LLM observability watches prompts, tokens, and model outputs. Agent observability watches actions, the tool calls and system operations an agent performs, which is where the actual security risk lives.