I work in a field related to operations research (OR), and ChatGPT 4o has ingested enough of the OR literature that it's able to spit out very useful Mixed Integer Programming (MIP) formulations for many "problem shapes". For instance, I can give it a logic problem like "i need to put i items in n buckets based on a score, but I want to fill each bucket sequentially" and it actually spits out a very usable math formulation. I usually just need to tweak it a bit. It also warns against weak formulations where the logic might fail, which is tremendously useful for avoiding pitfalls. Compare this to the old way, which is to rack my brain over a weekend to figure out a water-tight formulation of MIP optimization problem (which is often not straightforward for non-intuitive problems). GPT has saved me so much time in this corner of my world.
Yes, you probably wouldn't be able to use ChatGPT well for this purpose unless you understood MIP optimization in the first place -- and you do need to break down the problem into smaller chunks so GPT can reason in steps -- but for someone who can and does, the $20/month I pay for ChatGPT more than pays for itself.
side: a lot of people who complain on HN that (paid/good - only Sonnet 3.5 and GPT4o are in this category) LLMs are useless to them probably (1) do not know how to use LLMs in way that maximizes their strengths; (2) have expectations that are too high based on the hype, expecting one-shot magic bullets. (3) LLMs are really not good for their domain. But many of the low-effort comments seem to mostly fall into (1) and (2) -- cynicism rather than cautious optimism.
Many of us who have discovered how to exploit LLMs in their areas of strength -- and know how to check for their mistakes -- often find them providing significant leverage in our work.