Dev iconDevSep 26, 2026 ~1 min source read

Why an AI Agent Can Execute the Same Action Twice

They send messages, create tickets, issue refunds, make bookings, update customer records, trigger deployments, provision resources, and call tools that change external state. That creates a failure mode distributed-systems engineers already know well — but agent loops make it unusually easy to trigger: a tool call can succeed and still look like a failure to the agent.

Why an AI Agent Can Execute the Same Action Twice

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They send messages, create tickets, issue refunds, make bookings, update customer records, trigger deployments, provision resources, and call tools that change external state.

That creates a failure mode distributed-systems engineers already know well — but agent loops make it unusually easy to trigger: a tool call can succeed and still look like a failure to the agent.

A timeout is not proof of failure A timeout describes what the caller observed.

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The useful part

They send messages, create tickets, issue refunds, make bookings, update customer records, trigger deployments, provision resources, and call tools that change external state. That creates a failure mode distributed-systems engineers already know well — but agent loops make it unusually easy to trigger: a tool call can succeed and still look like a failure to the agent. A timeout is not proof of failure A timeout describes what the caller observed.

What to take from it

At step 6, the important question is no longer:

Details worth keeping

That distinction is where ordinary retry logic can become dangerous. It does not prove what the external provider did.

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