When it comes to the challenging problems of causal inference (all the issues we encounter that create the gaps between textbook and applied econometrics) I think the best advice I have seen as an applied researcher comes from Marc Bellemare:
Which seems to be a big takeaway from Angrist and Pischke's Mostly Harmless Econometrics:
"So what's an applied guy to do? One answer, as always, is to check the robustness of your findings using alternative identifying assumptions. That means that you would like to find broadly similar results using plausible alternative models"
That's applied econometrics in one lesson. That's the credibility revolution in practice.