First, LLMs should be happy to use made up languages described in a couple thousand tokens without issues (you just have to have a good llm-friendly description, some examples). That and having a compiler it can iterate with / get feedback from.
Second, LLMs heavily reduce ecosystem advantage. Before LLMs, presence of libraries for common use cases to save myself time was one of the main deciding factors for language choice.
Now? The LLM will be happy to implement any utility / api client library I want given the API I want. May even be more thoroughly tested than the average open-source library.
To be clear, I mean specifically using Claude Code, with preloaded sample context and giving it the ability to call the compiler and iterate on it.
I’m sure one-shot results (like asking Claude via the web UI and verifying after one iteration) will go much worse. But if it has the compiler available and writes tests, shouldn’t be an issue. It’s possible it causes 2-3 more back and forths with the compiler, but that’s an extra couple minutes, tops.
In general, even if working with Go (what I usually do), I will start each Claude Code session with tens of thousands of tokens of context from the code base, so it follows the (somewhat peculiar) existing code style / patterns, and understands what’s where.
And this is for generic backend stuff, like a CRUD server with a Rest API, the same thing with an Express/Node backend works no trouble.
> even those languages haven't taken over much of the professional world.
Non sequitur goalpost moving ... this has nothing to do with whether language development is a dead-end "in the real world", which is a circular argument when we're talking about language development. The claim is simply false.