But there's a cost induced with this superior productivity, and it's not only about speed. Maintaining and updating these (dynamically typed) programs in the future feels way less productive because things start to break everywhere, unless they've an extensive test base and use modern features like type annotations -- but then, you start losing the productivity advantage you had in the first place.

There's something to be said about path dependency and honing your skills any way you can. I discovered nice features of Ada2012 (and things that have been neglected in the standard) while writing some scraping-and-generating-svg tools, or replacing some ugly bash scripts.

The more you use one tech (especially out of the usual zone) the more you learn. And maybe you learn to avoid that language.

Also I like being able to come back and pick up small tools in my 'main' languages without rewriting them. So for me it's java for GUIs or highly dynamic runtime-y stuff (introspection, code gen, AOP) or 'throwable' stuff, and Ada for 'serious real-time must run 2 years without crash' stuff.

Too many times I end up maintaining python scripts that have overgrown the 'script' phase and are full fledged business-critical tools and... It's then often too late to back off.

Very subjective. I find Python much less productive than Rust. Easy to learn != productive in the long run.

Languages like Python being more productive is a myth. A story people keep repeating, with absolutely no way to back it by facts, not to mention that productivity is not a scalar.

All there is just bunch of subjective experiences in specific circumstances.