Most automation fails because it optimizes for the happy path.
Production is exceptions.
Start here:
Why “queue” beats “dashboard”
Dashboards tell you something is wrong.
Queues tell you:
- who owns it
- what state it is in
- why it is blocked
- what evidence is missing
- what to do next
The four requirements (non-negotiable)
1) Ownership
Every item has an owner (and escalation rules).
2) Status history
Statuses are explicit and persisted. No overwrites.
3) Reason codes + evidence
Every exception includes a reason and links to the evidence needed to resolve it.
4) Safe reruns
After a fix, the operator must be able to rerun safely without duplicates.
Related:
How AI should feed a queue
AI should:
- prepare drafts and summaries
- propose next steps
- flag uncertainty explicitly
AI should not:
- silently commit money-impacting actions
- hide uncertainty
- overwrite operator decisions