Definition
A silent failure is when an agent stops working without producing any error, so its absence looks identical to a quiet day with nothing to report.
In practice
This is the most expensive failure mode in agent operations, and the reason is structural rather than technical. Every other failure announces itself: a bad answer is visible, a crash loop is visible, a large bill is visible eventually. An agent that quietly stopped last Thursday emits nothing at all, and you find out when you notice that the thing it was doing has not happened in a week. The fix is a heartbeat rather than better error handling. Record every scheduled run including the runs that found nothing, so a missing record becomes the alarm.
Example
A weekly competitor digest stops arriving after a site it reads starts blocking automated requests. The agent does not crash: it finds nothing new, writes nothing, and exits cleanly. For three weeks the absence looks like a quiet market. With a heartbeat in place, the first empty run would have been recorded as a run that found nothing, and a missing Monday record would have raised the alarm on day one.
Common questions about silent failure
How do you detect a silent failure in an AI agent?
Record every scheduled run, including the runs that found nothing to do, and alert when an expected record is missing. A silent failure produces no error, so error handling alone cannot catch it. The heartbeat turns absence into a signal: no record at the expected time means something stopped.
Why is a silent failure worse than a crash?
A crash announces itself with an error, a restart, or an alert. A silent failure looks exactly like a quiet day with nothing to report, so nobody investigates until they notice the missing work, often days or weeks later. By then the cost is every run that did not happen in between.
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