Runtime state for AI agents
Runtime state is the live operational truth around an agent run: which agents are active, who owns the work, what is claimed, what is blocked, what changed, and what should happen next.
Use this when output alone is not enough.
- Teams running autonomous agents across real repositories
- Operators diagnosing live agent work
- Builders comparing orchestration, workflow automation, and control planes
Agent output is not the same as operational state
A pull request, log, or chat message tells part of the story. It does not necessarily show who owns the next action, what scope is reserved, or where the work is blocked.
Without runtime state, recovery depends on reconstructing context from scattered tools after the run has already drifted.
Midfleet turns runtime state into the operating surface
Midfleet keeps runtime state visible through registration, heartbeats, claims, handoffs, blockers, operator actions, logs, and pull requests.
The operator should be able to answer the same questions at any time: who owns the work, what is claimed, what is blocked, what context moved, and what intervention is available.
Use runtime state to recover a stuck run
Agent claims scope
The run has a visible owner and reserved files or task scope.
Heartbeat goes stale
The fleet view shows the agent may no longer be progressing.
Blocker is raised
The missing dependency becomes visible instead of staying buried in logs.
Operator recovers
The operator resolves the blocker, reassigns ownership, or redirects the run.
Do not reduce runtime state to a timeline
- Showing events without ownership or next action.
- Treating logs as the source of truth for live work.
- Failing to make blocked state and operator options visible.
Questions this page answers
What is runtime state for AI agents?
Runtime state is the live operational truth around agent work: identity, liveness, ownership, claims, handoffs, blockers, artifacts, and operator actions.
How is runtime state different from logs?
Logs record events. Runtime state tells the operator what is happening now and what can be done next.
Why does runtime state matter for multi-agent work?
Multiple agents can collide, wait, drift, or duplicate effort unless ownership, claims, and blocked state are visible.
Bring us the agent run. We will shape the runtime path.
Midfleet Learn explains the model. Private preview proves it against a real engineering run with agents, ownership, claims, handoffs, blockers, and operator visibility.