Agreed, and I think it makes sense once you have a certain scale of assets. Right now, we have a small number assets across a variety of systems -- I would basically be writing 7 different IO managers right now, to support 4 instances of each. I think something like

pandas.DataFrame -> snowflake_table

is pretty easy to grok, but it's a little less clear for some other types of assets. dbt cloud job, Sagemaker training job, Rockset query lambda, etc. A good comparison here is dbt -- they essentially offer a single IO Manager per project, and you get a ton of mileage out of it