The symptom is specific: an AI automation publishes unfinished content. Start with the affected item and identify the decision or input that could produce this behavior.
Find the likely cause
Draft generation and publication share an unrestricted path.
Treat this as an explanation to verify against the actual work. Look at the input, the relevant decision, and the final result together. If the evidence does not support this diagnosis, investigate the mismatch before applying a convenient but unrelated fix.
Make the targeted correction
Insert an explicit approval state before the publishing action.
Automation is valuable when the trigger, transformation, review, and destination are reliable enough to reduce real work.
Check that the repair worked
Test that rejected or incomplete drafts cannot reach the live destination.
Repeat the check on the final version that the reader or customer will encounter. An approved draft, a preview, and a published result can differ; the acceptance decision should concern the version people actually use.
Prevent the next related failure
A separate issue to watch for is this: the workflow runs twice for one request. Use a stable request identifier and check completion before repeating work.
Monitor the useful outcome
Measure successful completed runs, exception rate, and total human time including corrections.
Keep a short record of the original symptom, the evidence behind the diagnosis, and the result of the acceptance check. That record makes the solution reusable when the same condition appears again, without assuming that every superficially similar problem has the same cause.