What actually broke when we put agents on back-office work

Reddit r/AI_Agents News

Summary

A practitioner shares real-world failure modes of running AI agents on back-office workflows, covering ambiguous timeouts, poorly contextualized human review queues, and shared credential management, along with fixes for each.

I've been running agents on real back-office work, not demos. Invoices, chasing missing docs, the boring ops that sit between systems. A few things broke in ways the tutorials never mention. Unknown outcomes. A timeout is not a failure. If the agent might have already written to the ERP or sent the email, treating "no response" as "retry" creates duplicates. We now force every outward action into done / not done / unknown, and unknowns go to a person. Review queues without context. Early on we just dumped failures into a human queue. Reviewers had no idea what the agent saw or why it stopped. Now every handoff carries the fields, the reason it abstained, and what to check. The corrections become the eval set. Credentials. One shared API token for "the bot" was a mess. When something went wrong we could not revoke one agent without killing the rest. Each agent gets its own scoped token, a named owner, and an expiry. Curious what broke for you once agents left the happy path. Was it state, ownership of side effects, or something else?
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