Overview
How might we design scheduled tasks & recurring actions so people can trust and act on AI output?
When this pattern fits
- Perfect for automation platforms, background job systems, and workflow tools where scheduled and recurring tasks enable proactive, time-based automation.
When to skip or lighten it
- One-off jobs that should stay manual.
- Tasks that need fresh human judgment every time they fire.
- Environments where unattended runs are policy-forbidden.
States
State model coming soon
Key UX elements
Key UX elements coming soon
Anti-patterns to avoid
Schedules that fire with no run history or last-result link.
No pause/cancel for a recurring job.
Timezone ambiguity (“9am” with no zone shown).
Quietly retrying forever after repeated failures.
How products use it
| Product | Implementation |
|---|---|
| Zapier | Schedule triggers for recurring zaps. |
| Make | Cron-like scenario scheduling. |
| GitHub Actions | Cron workflows with visible run history. |
| ChatGPT / agent platforms | Scheduled agent tasks and reminders. |
Implementation
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Pattern Definition:Frequently asked questions
What is a scheduled AI task?
It is an agent job that runs at a set time or interval without the user starting each run, with a place to review outcomes afterward.
What must the schedule UI show?
Cadence, timezone, next run, last status, and pause/delete. Link each run to logs or outputs.
How does this relate to time-delayed execution?
Time delay is a short cancel window before one action. Scheduling is recurring or future-dated automation.
What happens on failure?
Surface the error, cap retries, and notify the owner. Silent missed schedules destroy trust.