My point was that being Pareto-optimal is such a weak constraint that it doesn't really mater, in real life, when choosing a decision algorithm.

This does not agree with my professional experience; many real decisions are Pareto suboptimal with respect to terminal values.

But that perfect algorithm is usually not an option - we don't have infinite computing power, we don't have perfect knowledge, we don't have infinite time for the convergence towards the optimal to happen.

What? This is the opposite of what you just said; this is "Pareto optimality is too strong a constraint for us to be able to find feasible solutions in practical time."

I agree with you that Pareto optimality is insufficient, and also that Pareto optimality with respect to terminal values is not necessary. Note that choosing to end your maximization algorithm early, because you have an answer that's "good enough," is a Pareto optimal policy with respect to instrumental values!

I think that we understand VNM calculations well enough that most modern improvements in decision-making will come from superior methods of eliciting weights and utility functions. That said, VNM calculations are correct, should be implemented, and resistance to them is misguided. Treat measurement problems as measurement problems, not theoretical problems!