A smart-meter update can look much better than the previous version and still fail the release rule. In our synthetic MeterGuard example, a proposed hotfix sharply reduces predicted failures for the same generated fleet. The average predicted failure rate falls to 2.85% of meters with enough data to assess. But the upper end of the modeled range is 4.1%, above the demo's 3.0% stop boundary. It still recommends against release. For a firmware review, ask two separate questions: how much did the estimate improve, and does the remaining range meet the agreed limit? Check that the comparison uses the same fleet conditions. The estimate still depends on assumptions about the update's behavior. Code can apply a rule consistently without proving those assumptions right. No firmware is released in this demo. #SmartMeters #UtilityOperations #FirmwareTesting #ReleaseManagement