Learn · Practical workflows
A world full of agents needs oversight
Agents can write code, operate browsers, call tools, and act across systems faster than a person can watch each step. Phigon gives teams a practical surveillance and monitoring layer for those AI agents—without turning that oversight into hidden monitoring of people.
Engineering operations
Understand agent activity across development machines
Platform and engineering teams can share one view of supported coding-agent activity instead of collecting manual status updates from every machine.
Use Phigon to:
- Spot stale or disconnected machines.
- Review current and earlier activity windows.
- Separate supported activity from limited coverage.
- Understand when a machine needs attention.
Security operations
Investigate unusual behavior with evidence context
When something unexpected happens, the most important question is not only “what appears to have happened?” It is also “what evidence supports that view?”
Phigon helps reviewers compare agent-native, OS-native, and approved gateway claims while keeping disagreements visible.
Incident review
Reconstruct what the system could actually observe
Move from current machine health into relevant history and keep the evidence state attached to each activity record.
This helps incident reviewers avoid two common mistakes:
- Treating missing telemetry as proof that nothing happened.
- Joining unrelated activity because an operating system reused a PID.
Governance and responsible AI
Make supervision boundaries reviewable
Privacy, risk, and platform owners need to know whether an AI-agent deployment is operating within its approved boundary.
Phigon makes it easier to review:
- The collection scope approved by the machine owner.
- Whether consent is still current.
- Which evidence sources are available.
- Where attribution is limited or conflicting.
- Whether revocation and deletion workflows are available.
Long-running and high-volume agent fleets
Monitor agents when direct observation no longer scales
As agent fleets grow, supervision cannot depend on a person staring at every session. Phigon creates a shared operational layer for fleet health, agent presence, history, and uncertainty.
That makes it useful for teams introducing longer-running agents, parallel agent workflows, or agent infrastructure spread across many authorized machines.
What Phigon is not for
Not covert surveillance. Phigon requires authorization and informed machine-owner consent. It is not designed to hide collection, bypass local privacy controls, or turn weak evidence into claims about a person.