I was thinking more of when a sufficiently advanced device would be able to “decide” the task would be worth using its own capabilities to write some code to tackle the problem rather than brute force.
For small problems it’s not worthwhile, for large problems it is.
It’s similar to choosing to manually do something vs automate it.
I didn't use an LLM back then. But would totally do that today (copilot).
Especially since the parser(s) I wrote were rather straightforward finite state machines with stream handling in front, parallel/async tooling around it, and at the core business logic (domain).
Streaming, job/thread/mutex management, FSM are all solved and clear. And I'm convinced an LLM like copilot is very good at writing code for things that have been solved.
The LLM, however, would get very much in the way in the domain/business layer. Because it hasn't got the statistical body of examples to handle our case.
(Parsers I wrote were a.o.: IBAN, gps-trails, user-defined-calculations (simple math formulas), and a DSL to describe hierarchies. I wrote them in Ruby, PHP, rust and perl.)
You're assuming OP needs an LLM to write a parser, since they mentions writing many during their career they probably don't need it ;)