I am pretty surprised to see no discussion of statistical power in the article and very little mention in the comments here. To me, having more statistical power solves many of the issues mentioned in the article. Many of the rest can be handled with use of Bayesian priors, context-specific p-values thresholds (.01, .1, etc.), and replication.

There's decent working guidelines for statistical power, but a lot of the issues (especially around replication) I see are mainly due to sample sizes being too small to adequately detect effects, especially if those effects are small.