The fundamental problem is that 0 is a privileged value of effect size. So you can replace a p-value with confidence intervals, or credibility intervals (which are the same as confidence intervals as N increases to infinity, and the data dominate the posterior), or whatever, but it will always be appropriate (in the relevant scenario) to ask "is there an effect size at all?"

This is why these calls to eliminate significance testing always seem really naive and short-sighted to me. P-values are abused, and people confuse p-values and effect size, but there will always be a need to focus on 0 as that supremely-important number. ε can be judged on its practical significance but 0 is always less.

Anyway, I agree with you but wanted to point out that there's two sides to the coin, and both lead in the same direction.