Hey folks!
I'm looking for beta users to try out Cerone — an AI Agent governance runtime.
It helps monitor, control, and enforce policies on AI agents at runtime, would love early feedback from anyone building with agents.
Install it via PyPI: pip install ceroneFull details & docs on the PyPI page: pypi.org/project/cerone
If you try it out, drop your feedback in the comments or reach out directly — every bit helps shape the roadmap!
pypi.org
Top comments (4)
Interesting direction.
A lot of agent governance tooling right now is still focused on policy definition instead of runtime enforcement.
The harder problem usually starts once agents are operating continuously across tools, environments, retries, and autonomous execution loops.
That’s where Governance Telemetry, Decision Boundaries, escalation persistence, and Stop Authority start becoming operationally important.
Especially if organizations need replay visibility into:
what executed,
what changed,
what triggered intervention,
and whether controls remained active during runtime.
Stop Authority is an interesting framing, are you thinking about this in the context of continuous execution loops specifically? Cerone handles the rejection gate but I'm curious how you're thinking about mid-execution intervention.
Run- time enforcement is exactly the gap Cerone targets. I tend to think of governance and compliance as an always-on capability, and not an "after the fact" process..
That’s very close to how I think about it.
Most governance systems still operate like a preflight checklist:
approve the model
approve the policy
approve the deployment
But execution behavior changes over time.
That’s where execution-time governance becomes necessary.
The gap is usually not initial approval.
The gap is what happens after escalation conditions emerge during runtime.
For me, Stop Authority is less about static rejection and more about survivable intervention capability during continuous execution.
Can the system:
detect behavioral drift
escalate against operational thresholds
interrupt execution mid-stream
preserve telemetry continuity
maintain replayable accountability after intervention
Without that layer, governance can become observational instead of enforceable once systems begin operating continuously.
That’s why I keep treating governance as infrastructure rather than documentation.
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