[taesis]

I suppose I'm not arguing from the perspective of fairness, but moreso about incentives + experience. If we applied the author's argument against other fields and languages, e.g. machine learning and python, then the cpython maintainers would be right in including TensorFlow in the python stdlib (or whichever competitor dethrones in and sticks around for long enough).

That doesn't sit well with me, at least. I'd want the top ML developers looking at TensorFlow, and the best language implementers doing the same for cpython, not the latter trying desperately to improve code they have no expertise in. From that perspective, what matters is community: is there a knowledgable community supporting codebase 'x', where x could be the stdlib or some third party library. Some other commenters in this thread proposed better library curation/discovery tools in place of a formal commitment of long term support by the core team, which seems ideal! Using such an approach, you rely on the language for the core-language bits, and on third parties for the third-party bits, which seems on the surface to be healthier than arbitrarily choosing the only constant group (core language devs) as your supporters of everything.