Comment by risyachka
9 days ago
>> Getting the best results out of these models requires skill, experience, intuition, and domain expertise.
domain expertise has nothing to do with llms. On the contrary, to have it you need to avoid llms.
>>you risk prompting Claude Fable 5 like it's GPT-4o
Thats fine because when GPT came out you had to treat it like a baby, GPT2 and around that time "Prompt engineering" was a thing.
Now its all dead.
After opus 4.8 all you have to do is say "fix it" or add /plan. All that time spend on learning previous models is time wasted.
And in a year or two with developed harness you will be out of the loop, errors are incoming - llm fixes them or adds new features based on some transcripts etc.
Even if model development stops now - there is nothing to learn really. Sure you may need to adjust prompt style a bit. You will do it naturally just like when you communicate with a new person. There is no "knowledge" to it, it is very smart.
> domain expertise has nothing to do with llms. On the contrary, to have it you need to avoid llms.
It has everything to do with LLMs.
Go ask Claude Fable to write you a two page position paper on how the European economy recovered after World War II, suitable for submission to a conference for economists.
It will do exactly that (well, probably, Fable can find all sorts of reasons to refuse) - and the value of what it wrote to you will be virtually zero, unless you yourself have deep expertise in economics and history.
But this is exactly what I meant.
You need expertise. But you can acquire it only by doing. So LLMs won't help you here. You need to put in the work.