[gopiandcode]

Arguably it really depends on your DSL right? If it has a semantics that already lies close to existing programming languages, then I'd agree that a few examples might be sufficient, but what if your particular domain doesn't match as closely?

Examples of domains that might be more challenging to design DSLs for: languages for knitting, non-deterministic languages to represent streaming etc. (i.e https://pldi25.sigplan.org/details/pldi-2025-papers/50/Funct... )

My main concern is that LLMs might excel at the mundane tasks, but struggle at the more exciting advances, and so now the activation energy for coming up with advances DSLs is going to increase and as a result, the field might stagnate.

[demosthanos]

Remember that LLMs aren't trained on all existing programming languages, they're trained on all text on the internet. They encode information about knitting or streaming or whatever other topic you want a DSL for.

So it's not just a question of the semantics matching existing programming languages, the question is if your semantics are intelligible given the vast array of semantic constructs that are encoded in any part of the model's weights.