Author here. Delighted to see this near the top of HN this afternoon, and to see the healthy discussion it's provoked. Happy to answer any questions as best I can if you've got 'em.
My problem with your post is that it seems to be based on a faulty understanding of the actual way things work (compared to some theory on it), and furthermore is a case of 'I'm a software engineer, I can solve anything' without actually understanding the issues. Much like engineer's armchair lawyering, which is always so far off the mark that it's impossible to even intelligently debate, because it's based on so much misinformation.
[0] Or sciencemetrics, informetrics and other assorted subfields
For me one of the most salient things in that space -- albeit a different point than the one raised in the essay -- is the debate about what sorts of metrics are most appropriate (if any) for informing decisions about hiring, tenure, and the like. In some ways it's quite like the be-careful-what-you-wish-for problems any business has in choosing which metrics to care about. For instance, the h-index might shape a researcher's choice of whether to publish something as one larger paper or two smaller ones.
As Sam Altman put it, "It really is true that the company will build whatever the CEO decides to measure." I think a similar principle holds for research and scholarship.