I think it's a simple abstraction situation and the move for programming environments that include everything.
Geordi Laforge doesn't code much on the Enterprise. He simply asks the computer to build him a model of the anomaly so he can test out ideas. In a way, modern languages like Python (even before LLMs) let you get a lot closer to that reality. Sure you had to know some language basics, but this was pretty minimal and you'd use those basic building blocks to glue together libraries to make an application. Python has a good library for practically anything I do and since this is standard, it's expected that a task doesn't take too long. I can't tell my boss I'll need 3 years to code my own solution that uses my own libraries for numpy and scipy. You're expected to glue libraries together. This is why MIT moved SICP from scheme to Python. It's a different world.
With Forth, every program is a work of art that encapsulates an entire solution to a problem from scratch. It's creator chuck moore takes this to such a level that he also fabs his own chips to work with his forth software optimally. These languages had libraries, but they weren't easy to share and didn't have any kind of repository before Perl's CPAN. Perl really took off for awhile, but Python won out by having a simpler language with builtin OO (Perl's approach was a really hacky builtin OO or you download a library...).
To be honest though, I spent a decade trying many languages (dozens including common lisp, Prolog, APL, C, Ada, Smalltalk, Perl, C#, C++, Tcl, Lua, Rust...etc) looking for the best and although I never became experts in those languages, I kept coming to the conclusion that for my particular set of needs, Python was the best I could find. I wasted a lot of time reading common lisp books and just found it much easier to get the same thing done in Python. Your mileage will vary if you're doing something like building a game engine. A lot of people are just doing process automation and stuff like that and languages like Python are just better than common lisp due to the environment and tooling benefits. Also, although Python isn't as conceptually beautiful as lisp, I found it much easier to learn. The syntax just really clicked for me and some people do prefer it.
Geordi Laforge doesn't code much on the Enterprise. He simply asks the computer to build him a model of the anomaly so he can test out ideas. In a way, modern languages like Python (even before LLMs) let you get a lot closer to that reality. Sure you had to know some language basics, but this was pretty minimal and you'd use those basic building blocks to glue together libraries to make an application. Python has a good library for practically anything I do and since this is standard, it's expected that a task doesn't take too long. I can't tell my boss I'll need 3 years to code my own solution that uses my own libraries for numpy and scipy. You're expected to glue libraries together. This is why MIT moved SICP from scheme to Python. It's a different world.
With Forth, every program is a work of art that encapsulates an entire solution to a problem from scratch. It's creator chuck moore takes this to such a level that he also fabs his own chips to work with his forth software optimally. These languages had libraries, but they weren't easy to share and didn't have any kind of repository before Perl's CPAN. Perl really took off for awhile, but Python won out by having a simpler language with builtin OO (Perl's approach was a really hacky builtin OO or you download a library...).
To be honest though, I spent a decade trying many languages (dozens including common lisp, Prolog, APL, C, Ada, Smalltalk, Perl, C#, C++, Tcl, Lua, Rust...etc) looking for the best and although I never became experts in those languages, I kept coming to the conclusion that for my particular set of needs, Python was the best I could find. I wasted a lot of time reading common lisp books and just found it much easier to get the same thing done in Python. Your mileage will vary if you're doing something like building a game engine. A lot of people are just doing process automation and stuff like that and languages like Python are just better than common lisp due to the environment and tooling benefits. Also, although Python isn't as conceptually beautiful as lisp, I found it much easier to learn. The syntax just really clicked for me and some people do prefer it.