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Why AI Agents Double-Charge Customers: The Retry Logic Flaw Developers Miss

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A widely overlooked infrastructure bug in AI agent frameworks can cause duplicate financial actions, such as issuing a double refund, when a network timeout or dropped connection makes the outcome of an API call ambiguous. Unlike a simple success-or-failure model, distributed system calls have three possible outcomes: committed, failed, or ambiguous — and most retry logic incorrectly treats ambiguous as failed. The flaw is not caused by faulty AI reasoning; the model may have acted correctly, but the surrounding code blindly retries on any exception. The safe approach requires atomically reserving an action's unique key before making the external call, then marking it as ambiguous — not releasing it — if a timeout occurs. This principle, long established in databases via two-phase commit and in payments via idempotency keys, has yet to be widely adopted by agent frameworks that are already taking consequential real-world actions.

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Why AI Agents Double-Charge Customers: The Retry Logic Flaw Developers Miss · ShortSingh