minion-orchestrator

You can coordinate durable background AI workloads by submitting tasks through a unified queue interface that manages shell automation and subagent workflows with persistent state tracking. This allows reliable execution of long-running processes.

Yes, long-running background jobs support full lifecycle control including pause, resume, cancel, and replay functions. Restart durability ensures workloads recover seamlessly after interruptions while maintaining structured status tracking.

Job orchestration for parallel research agents is the process of submitting and monitoring concurrent tasks through a persistent queue. It is needed when coordinating multiple subagents requires progress visibility, steering controls, and recovery from interruptions.

You can track progress and send steering instructions by utilizing the observable job state management interface. This provides structured status updates and allows real-time steering controls to guide running subagent workflows during execution.

Yes, background task queue management operates without external dependencies. It handles job orchestration and protected execution pathways internally, requiring only the core system environment to manage and monitor durable workflows.

You should use a dedicated job orchestration queue when tasks require observable state management, restart durability, or parallel work coordination. Basic shell automation lacks the lifecycle controls and recovery mechanisms needed for complex subagent workflows.