Think about it, how much marginal influence does it really have if you say OP’s version vs a fully formed sentence? The keywords are what gets it in the area.
That is not correct. The keywords mean nothing by themselves. To a transformer model, the relationships between words is where meaning resides. The model wants to answer your prompt with something that makes sense in context, so you have to help it out by providing that context. Feeding it a sentence fragment or a disjoint series of keywords may not have the desired effect.
To mix clichés, "I'm feeling lucky" isn't compatible with "Attention is all you need."
I find that providing more context and details initially leads to far more success for my uses. Once there’s a bit of context, I can start barking terms and commands tersely.
I find more hallucination - like when you're taught as a child to reflect back the question at the start of your answer.
If I am not careful, and "asking the question" in a way that assumes X, often X is assumed by the LLM to be true. ChatGPT has gotten better at correcting this with its web searches.
I am able to get better results with Claude when I ask for answers that include links to the relevant authoritative source of information. But sometimes it still makes up stuff that is not in the source material.
Is this really the case, or is it the case with Claude etc because they've already been prompted to act as an "helpful assistant"? If you take a raw LLM and just type Google search style it might just continue it as a story or something.
To mix clichés, "I'm feeling lucky" isn't compatible with "Attention is all you need."