Should you use random state or random seed in machine learning models?
Your intuition is correct. You can set the random_state or seed for a few reasons.:

For repeatability, if you want to publish your results, share with
other colleagues
if you are tuning the model, in an experiment you usually want to
keep all variables constant except the one(s) you are tuning.

I usually set the random_state variable, not the random seed while tuning or developing, as this is a more direct approach. When you go to production, you should remove the random_state and or random_seed settings, or set to None, then do some cross validation. This will give you more realistic results from your model.