Managed AI agents that don't get stuck
The dirty secret of autonomous agents is that they fail quietly — they loop, they stall on a hung tool call, or they declare victory without finishing. PAI's Supervisor watches every run from the outside: a definition of done, honest heartbeats, and an intervention ladder from a gentle nudge to a hard cancel — with a Monitor and kill switch in your pocket.
Six controls that keep agents honest
- Independent SupervisorWatches every run from the outside — it never asks the agent how it's doing.
- Live MonitorSee what's running from your phone — the Pocket Companion, closer than the incident.
- Pocket kill switchOne tap pauses every Pie on the instance instantly, recorded in the audit chain.
- Parks for approvalDestructive interventions default-deny — the safety net can't overreach without your yes.
- Driver RecordOne accountable human; every action signed into a tamper-evident chain.
- Autonomy per PieEach Pie runs inside limits you set — autonomy and budget, per agent.
The real failure mode: agents that get stuck
Search “AI agents get stuck” and you'll find the same story: an agent twenty minutes into a loop, sitting idle on a tool call that never returned, or reporting “done” without finishing.
The problem isn't the model — most agent stacks don't watch the run itself. They trust the agent to report its own progress, the one thing a stuck agent can't do. Reliable AI agents need a supervisor independent of the agent.
Run contracts: a definition of done
Before a Pie's run begins, the Supervisor derives a run contract: a checkable definition of done, a timebox, and a heartbeat cadence. A run with no definition of done can't be judged finished — so every run gets one.
During the run it tracks honest wall-clock beacons — started, waiting, finished — never a fake progress bar, and classifies each run as running, stalled, diverged, finished, failed, or cancelled. Afterward it scores adherence: every part of the definition of done is marked met or unmet, so nothing is silently dropped.
The intervention ladder: nudge, then cancel
Detection without action is just a nicer dashboard. When a run stalls or drifts, the Supervisor escalates an ordered ladder, harmless to destructive: a nudge (a resume prompt) → cancel the run → release the issue → pause the agent.
The safety net is itself on a leash: an intervention you trigger runs immediately, but a destructive one the Supervisor wants to take automatically parks behind a default-deny approval first. The thing that cancels your agents can't overreach without your yes.
Keep reading
Supervision is the safety net. These are the rest of the controls.
AI CEO Autopilot
The delegation loop the Supervisor watches over — goal in, staffed workforce out, every step gated.
Hard-stop AI agent budgets
Stall detection plus a budget wall — runaway loops caught two ways before they cost you.
Run multiple businesses with one AI workforce
Supervised, isolated workforces across every company you run — one phone, one Monitor.
Managed AI agents — FAQ
Autonomous agents fail quietly. A task has no clear definition of done, so the agent loops; a tool call hangs, so the run waits forever; or the agent declares success without finishing. Raw agent frameworks rarely watch the run itself — so a stuck agent just sits there burning time and tokens until you happen to check. The fix is supervision: something independent that knows what 'done' looks like and steps in when a run drifts.
The Supervisor is the layer that watches every run from the outside. Before a run starts it derives a run contract — a short definition of done plus a timebox and a heartbeat cadence. During the run it tracks honest wall-clock beacons (started / waiting / finished, never a fake progress bar). After the run it scores adherence: did the work actually meet the definition of done? It classifies each run as running, stalled, diverged, finished, failed, or cancelled.
It intervenes, from gentlest to firmest: a nudge (a resume prompt), then cancel the run, then release the issue back to the queue, then pause the agent. An owner-initiated intervention from your phone executes immediately. An automatic destructive intervention the Supervisor wants to take parks behind a default-deny approval first — so the safety net itself can't overreach without your say-so.
Raw agent runtimes give you reach — channels, tools, browsers — but they trust the run to report on itself. PAI adds the run contract, the honest beacons, the adherence check, and the intervention ladder on top, all signed into a tamper-evident chain. You don't just run agents; you run agents you can watch, correct, and prove. That supervision layer is the strongest differentiator over a bare agent stack.
Yes. The Pocket Companion gives you a live Monitor of what's running and a one-tap kill switch that pauses every Pie on the instance instantly, with the stop recorded in the audit chain. The off switch is always closer than the incident — and it's in your pocket.
Run agents you can actually trust
See the Supervisor alongside every other capability — and the honest status of each — then choose your plan.