I Taught an AI Agent How to Undo Its Mistakes

I used to think the hardest part of building an autonomous AI agent was getting the model to reason correctly.

I was wrong.

The harder problem begins after the model has made a decision.

An LLM can decide that a customer order should be processed, inventory should be reserved, a payment should be charged, a CRM record should be updated, and a shipping notification should be sent.

That sounds straightforward.

Until the third API call times out.

Then things get interesting.

Imagine an AI agent processing a $12,000 enterprise order.

It reserves the inventory.

The payment succeeds.

Then it calls the CRM.

The CRM returns a 504 Gateway Timeout.

Did the CRM actually reject the request?

Or did the CRM update the record successfully, but the response disappear somewhere between the server and the agent?

The model doesn't know.

The orchestration layer doesn't know.

And meanwhile, the customer's credit...

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