How many times would you need to parse to get an energy saving on using an lm to parse vs using an llm to write a parser, then using the parser to parse.
This is the kind of thinking that leads to modern software being slower than software from 30 years ago, even though it is running on hardware that's hundreds of times faster.
LLM's are not the solutions, they are the source of big troubles.
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 ;)
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.)
For small problems it’s not worthwhile, for large problems it is.
It’s similar to choosing to manually do something vs automate it.