Well, this is very rapidly getting us into complex territory that future decision-theory posts will hopefully explore, but a very brief answer would be that I am unwilling to define anything fundamental in terms of do() operations because our universe does not contain any do() operations, and counterfactuals are not allowed to be part of our fundamental ontology because nothing counterfactual actually exists and no counterfactual universes are ever observed. There are quarks and electrons, or rather amplitude distributions over joint quark and lepton fields; but there is no do() in physics.

Causality seems to exist, in the sense that the universe seems completely causally structured - there is causality in physics. On a microscopic level where no "experiments" ever take place and there are no uncertainties, the microfuture is still related to the micropast with a neighborhood-structure whose laws would yield a continuous analogue of D-separation if we became uncertain of any variables.

Counterfactuals are human hypothetical constructs built on top of high-level models of this actually-existing causality. Experiments do not perform actual interventions and access alternate counterfactual universes hanging alongside our own, they just connect hopefully-Markov random numbers into a particular causal arrow.

Another way of saying this is that a high-level causal model is more powerful than a high-level statistical model because it can induct and describe switches, as causal processes, which behave as though switching arrows around, and yields predictions for this new case even when the settings of the switches haven't been observed before. This is a fancypants way of saying that a causal model lets you throw a bunch of rocks at trees, and then predict what happens when you throw rocks at a window for the first time.