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Workers (Background Execution)

Workers are the engine room behind everything that happens when you're not looking. They're the background-execution layer that runs your Agents, generation pipelines, scheduled updates, and Mission ticks reliably, in parallel, with retries — so the platform's autonomous operation keeps humming whether you have one Work or a hundred.

You rarely manage Workers directly. They're the "who's actually doing the job" answer underneath the Agents and schedules you do manage.

What Workers run

Job kindWhat it does
Agent heartbeatsWake each active Agent on its cadence, run its decision loop, record the run.
Agent tasks & chat repliesExecute work assigned to an Agent; reply when an Agent is mentioned.
Generation pipelinesBuild and refresh a Work's content and code.
Scheduled updatesRe-run a Work's pipeline on its cadence.
Mission ticksGenerate fresh Ideas for scheduled Missions.
Inbound emailTurn incoming mail into Tasks or conversations.
Ingest & extractionNormalize and extract uploaded Knowledge Base sources.
Community PR processingTriage and merge community contributions.

How Workers behave

  • Parallel — many jobs run at once; a dispatcher claims due work in batches so thousands of Agents and schedules scale without stepping on each other.
  • Safe under contention — a single Agent's heartbeat can only be claimed by one Worker at a time (compare-and-set), so nothing runs twice.
  • Retried — transient failures (network blips, provider rate limits, upstream 5xx) are retried with backoff before a job is marked failed.
  • Bounded — runs have timeouts; an Agent that keeps failing auto-pauses rather than burning budget.
  • Observable — every run emits activity-log entries and surfaces on the relevant Dashboard, with cost attributed to the right Agent, Task, or Work.

Where they run

Workers are powered by the platform's background-jobs infrastructure (Trigger.dev plus internal queues). In the cloud, this is fully managed for you. When you self-host — or run the upcoming Desktop App — Workers run alongside the rest of the stack, and you can also point them at an external or self-hosted jobs backend.

See also