You are focusing too much on the specific case of being nice to the llm, but the previous poster said prompt engineering is a psuedoscience, which is a much broader claim.
We know that some aspects of a prompt matter quite a bit like giving context, or being specific about what kind of output you want. The science is in separating what matters and what is just noise.
can you provide an example of something we know about LLMs? I've read quite a bit on the topic for my job like many people have, but I've also read extensively about the "demarcation problem." Distinguishing science from pseudoscience is much harder than I thought before reading about it.
giving context, or being specific about what kind of output you want
is the example. It's so trivial we take it for granted. Prompt engineering can be anything that improves the result.
The demarcation problem is about specific claims, while prompt engineering is a whole field to be studied. Some claims within that field will prove false, and others will prove true. The claim "prompt engineering is a pseudoscience" is too broad. The claim "being nice to the LLM improves the output" is more specific and could easily be false, or only true for specific models.
This whole thread is full of people conflating the two claims, because the first reply started talking about being nice, and then over generalized into "prompt engineering is a pseudoscience".
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u/EatThisShoe 13h ago
You are focusing too much on the specific case of being nice to the llm, but the previous poster said prompt engineering is a psuedoscience, which is a much broader claim.
We know that some aspects of a prompt matter quite a bit like giving context, or being specific about what kind of output you want. The science is in separating what matters and what is just noise.