My students (18-21) are excited to learn Rust in my class I teach about programming languages. Younger students are learning Luau via Roblox -- spoke with a middle schooler on Sunday who was making games with his friends. They get introduced to Scratch in school and learn that until they move on to Java at middle and high school. I teach freshman Lua in their intro to engineering class, and they also go on to learn things like R, Matlab/Simulink, Python. Java, C, and C++ if they're a CS major.
Combine that most CS students learn many languages with LLMs and coding agents and the size of the ecosystem isn't quite as important as it used to be. New hires can be productive from day 1. Missing libraries are relatively easy to add. Moreover the language characteristics can be more useful than ever: fast running, fast compiling, typed, easy to read, etc.
Coding agents strengthen the value of low code platforms, and reduce even further the role of specific programming languages.
Examples, workato, boomi, opal,....
Many automations that used to be written in programming languages, deployed via serverless or containers, are now agents driven by prompts.
Yeah I think LLMs really help with the chicken-egg situation in language adoption. Contrary to many opinions that predict programming homogenizing around the big 3 languages that exist today (because that's what the LLMs currently write) I think in the future more nice languages will gain adoption as they are written by LLMs, who as you note don't care about a lack of community surrounding those langs -- if they need a missing library the AI can just write it. Maybe they even add it to the language ecosystem for other AI or humans.
I think Python is actually kind of the worst language of the top langs to be the lingua franca of AI, where more niche statically typed languages like Nim are better suited.
As a Pythonista I tend to agree. I had high hopes for Mojo but it's taking its due time to become usable outside the narrow focus of GPU programming, whereas Nim fits multiple niches surprisingly well.
Python is a way, is Lisp's revenge after its AI winter dismissal.
Finally, due to AI market share pressure, JITs in Python are a real thing, after all those years of PyPy being largely ignored.
Python at least has type annotations these days, even if they aren't enforced.
One of my concern is LLMs are going to generate a lot of low quality code for languages that do not have sufficient discussions on forums like Stackoverflow.
That's why these niche languages need state-of-the-art compilers that enforce invariants more strongly. This way, they can catch most of the subtle bugs the LLM produces, sort of like antibodies.
> New hires can be productive from day 1.
...or counterproductive, lmao