It's interesting, people have been trying to solve the "two language problem" since before I …

There's a very interesting video about the "1.5 language problem" in Julia [0]. The point being that when you write high-performance Julia it ends up looking nothing like "standard" Julia. It seems like it's just extremely difficult to give fine-grained control over the metal while having an easy, ergonomic language that lets you just get on with your tasks. [0] https://www.youtube.com/watch?v=RUJFd-rEa0k

From what I can tell, gaming has mostly just embraced two language solutions. The big engines Unity, Unreal, and Godot have tight cores written in C/C++ and then scripting languages that are written on top. Hobby engines like Love2D often also have a tight, small core and are extensible with languages like Lua or Fennel. Modern Common Lisp also seems to have given up its "one language to rule them all" mindset and is pretty okay with just dropping into CFFI to call into C libraries as needed. Over the years I've come to see that mindset as mostly a dead-end. Python, web browsers, game engines, emacs, these are all prominent living examples of two-language solutions that have come to dominate in their problem spaces. One aspect of the "two language problem" that I find troubling though is that modern environments often ossify around the exact solution. For example, it's very difficult to …

You say this is some ideal outcome, but I want to get as far away from python and C++ as possible. Also, no. I can't use Python for inference, because it is too slow, so I have to export to tensorflow lite and run the model in C++, which essentially required me to rewrite half the code in C++ again.