You're making another assumption: that the power calculations are actually rigorous and the effect size (not "having an effect", but "having an effect of at least the size used to calculate power at a given alpha") is sufficient. If you've ever designed a clinical trial or written up the statistics for a grant, you know damned well that these numbers are cooked 6 ways from Sunday.
Colquhoun is a sharp guy (I have debated various fine points with him on several occasions and he has convinced me with reproducible examples that I was wrong in my beliefs). It would be nice if the name of the article was "It's time for science to abandon the term statistically significant", as in the URL, because that's the real point here.
"Signficance" can only be judged in context. Post all your data and then we'll see whether you can be believed. But that notion of transparency is absolutely terrifying to the sorts of senior scientists who control most funding and peer review at the moment. It's OK, though; the rest of us put up preprints knocking down the most egregious lies and those who care about the truth can have it (for free, no paywall).
I've got plenty of Cell, Nature, and NEJM papers on my CV; direct support on grants where I am PI, Co-I, or KP is over $5M; and I still think the situation is fucked up. I'm not bitter because I feel left out; I'm bitter because I fear that the bad money is driving out the good, as it always does.
Take away the monetary incentive, the Journal Impact Factor BS, the "prestige" of hoodwinking 3-5 referees with a pile of STAP or single-sample comparisons (had to warn a student about this when he pulled some data from a Nature paper that a respectable MSKCC scientist gooned for...) and let's see what's left...