What a research result needs before production
Give the next operator enough information to reproduce, observe, and reverse the change.
Make the result reproducible
When I review a promising experiment, I ask for the inputs, evaluation window, configuration, and known exclusions. Those details should travel with the result. A colleague should be able to rerun it after the original notebook and source extracts have changed.
Decide how the system can fail
A stale feed, an empty batch and a plausible but wrong value look different in the pipeline. Write down how each condition is detected and what the workflow does next. Some signals can safely pause. Others need a fallback rule and an explicit warning to the reviewer.
Observe before routing work
I prefer a shadow run when the change will alter someone’s queue. Compare the candidate’s dispositions with current outcomes, inspect disagreements, and measure the workload it would create. Agree in advance on the conditions for switching over and for rolling back.
Hand off ownership
The handover should name the owner and link to one runbook with the health checks, recovery steps and rollback procedure. Have the receiving operator walk through a failure with the person who built the system before the first production shift.