zlacker

>>tymsca+(OP)
One thing im wondering with the LLM age we seem to be entering: is there value in picking up a language like this if theres not going to be a corpus of training data for an LLM to learn from? Id like to invest the time to learn Gleam, but I treat a language as a tool, or a means to an end. I feel like more and more I'm reaching for the tool to get the job done most easily, which are languages that LLMs seem to gel with.

>>marlie+f5
The Gleam language, yes all of it, fits in a context window (https://tour.gleam.run/everything/)

I have similar concerns to you - how well a language works with LLMs is indeed an issue we have to consider. But why do you assume that it's the volume of training data that drives this advantage? Another assumption, equally if not more valid IMO, is that languages which have fewer, well-defined, simpler constructs are easier for LLMs to generate.

Languages with sprawling complexity, where edge cases dominate dev time, all but require PBs of training data to be feasible.

Languages that are simple (objectively), with a solid unwavering mental model, can match LLMs strengths - and completely leap-frog the competition in accurate code gen.