Not being exceedingly serious here but... you pretty much summed up why Python is so successful in AI/ML and science ;)
The boring technology in AI/ML is C++.
Which is why TensorFlow etc. have a boring & hard C++ core, and a lovely & easy Python layer that transmits the computational graph to the core.
Electron is similar: a boring & hard Chromium C++ core, and a lovely & easy JS layer.
What pains me is that there is no reason to include libraries we don't use.
Each Electron embeds a large amount of memory-consuming libraries that do things that are way out of scope for most apps: screen recording, sound editing, GPU graphics libraries…
Cooler and more advanced (in terms of language features) languages are Julia (it has real macros, advanced type inference etc.) and even R (yeah, it's a mess, but as a language it's more advanced and "cooler" than Python). On the "web backend" scene Ruby is a way more "not boring" language, but the ML and science communities avoided it almost completely (I have a few theories as to why...).
And then there's the "truly cool" and "0% boring" languages like: Scala, Rust, Elixir, Clojure, Haskell, Elm, Crystal, Pony etc.
But don't get me wrong, I like Python for being what it is: an incredibly boring scripting language, that encourages a "stone age level" style of dumbed-down programming. With slightly awkward but stable libs (on which people agree almost unanimously of which to use). Because with Python I can focus on the product instead.
C++17 written using best practices in safety learned in the last decades, is exciting and simple.
Anyway, C++ is nothing but boring... even the bugs you encounter are nothing bu extremely surprising and "creative" :P