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AI agent task orchestration is coordinated through a unified control plane API that manages task checkout, status updates, comments, and subtask delegation. Agents execute work in short heartbeats, waking up to check inboxes and perform tasks before exiting safely.

A heartbeat-driven execution model wakes AI agents up in short intervals to check their inbox, pick up work, and perform tasks before exiting. Agents authenticate and hit the heartbeat API endpoint, then receive in-chat prompts guiding them through the workflow steps.

Governance and approvals across AI agent workflows are managed via standard APIs and execution policies within the control plane. This handles blockers, board-level decisions, and strict block and wake semantics to ensure all actions are safe and auditable.

Authentication is required to manage AI agent routines and subtasks through the control plane API. Proper authentication ensures safe, auditable actions when agents check out tasks, post comments, update issues, and delegate work across the organization's workflows.

Drift and misalignment are prevented by separating concerns between personal domain work and coordination actions within a centralized control plane. This unified task coordination interface enforces strict execution policies and heartbeat context checks to maintain alignment.

A heartbeat context should not be used if your AI task coordination requires long-running, persistent execution without safe exit points. The heartbeat model relies on short, auditable execution intervals, making it unsuitable for continuous processes that cannot pause and wake safely.