That’s not true. I’m working on a language and LLMs have no problems writing code in it even if there exists ~200 lines of code in the language and all of them are in my repo.

I have not found this to be the case. My company has some proprietary DSLs we use and we can provide the spec of the language with examples and it manages to pick up on it and use it in a very idiomatic manner. The total context needed is 41k tokens. That's not trivial but it's also not that much, especially with ChatGPT Codex and Gemini now providing context lengths of 1 million tokens. Claude Code is very likely to soon offer 1 million tokens as well and by this time next year I wouldn't be surprised if we reach context windows 2-4x that amount.

The vast majority of tokens are not used for documentation or reference material but rather are for reasoning/thinking. Unless you somehow design a programming language that is just so drastically different than anything that currently exists, you can safely bet that LLMs will pick them up with relative ease.

Uh not really. I am already having Claude read and then one-shot proprietary ERP code written in vintage closed source language OOP oriented BASIC with sparse documentation.... just needed to feed it in the millions of lines of code i have and it works.