I work on CloudGPU. A failed AI video shot is only useful if the next trial can tell you something new. Changing the reference, prompt and motion settings together makes that harder. Start with one question: what exactly should this retry establish?
Write an experiment card containing the observed defect, the variable to change, the acceptance rule and the output name. If the character is correct but the movement is wrong, preserve the accepted image and compare the movement stage. Keep failed outputs so a later reviewer can see why an option was rejected.
Record the workflow revision and environment alongside the seed. A seed is a comparison aid, not a promise that different software and hardware produce identical files. Check decode integrity independently from visual acceptance.
Before expanding a remote run, approve the new batch scope and its spending and time ceilings. A successful small experiment should answer a question before it becomes a larger batch.
