Workflow Durable Execution
Use Workflow for long-running, resumable, and approval-oriented AI tasks.
Key takeaways
- AI tasks that outgrow request lifetimes need durable execution rather than fragile background promises.
- Workflow fits human approval pauses, long research across timeouts, multi-step automation with safe retries, scheduled reports, and external-event continuation.
- Design steps to be idempotent, store task state in durable records, and separate analysis steps from side-effect steps.
- Add approval gates before irreversible actions, and define retry, timeout, compensation, and escalation behavior before production.
AI tasks often outgrow request lifetimes. Research, approvals, retries, external events, and multi-step actions need durable execution rather than fragile background promises.
Workflow Fits
| Use case | Why durable execution helps |
|---|---|
| Human approval | Pause and resume around decision points |
| Long research | Preserve progress across timeouts |
| Multi-step automation | Track each stage and retry safely |
| Scheduled reports | Run repeatable tasks with history |
| External events | Continue when a webhook or user action arrives |
Step Design
- Make steps idempotent when possible.
- Store task state in durable records.
- Separate analysis steps from side-effect steps.
- Add approval gates before irreversible actions.
- Emit progress and final artifacts for review.
Failure Rule
Every workflow should define retry, timeout, compensation, and escalation behavior before production.