Not that I've had to deal with this specifically, but I have noticed how the input phrasing in my prompts pushes the LLM in different directions. I've just tried a quick test with `duck.ai` on gpt 4o-mini with:
A: Why is drinking coffee every day so good for you?
B: Why is drinking coffee every day so bad for you?
Question A responds that it has "several health benefits", antioxidants, liver health, reduced risk of diabetes and Parkinson's.
Question B responds that it may lead to sleep disruption, digestive issues, risk of osteoporosis.
Same question. One word difference. Two different directions.
This makes me take everything with a pinch of salt when I ask "Would Library A be a good fit for Problem X" - which is obviously a bit leading; I don't even trust what I hope are more neutral inputs like "How does Library A apply to Problem Space X", for example.
A: Why is drinking coffee every day so good for you?
B: Why is drinking coffee every day so bad for you?
Question A responds that it has "several health benefits", antioxidants, liver health, reduced risk of diabetes and Parkinson's.
Question B responds that it may lead to sleep disruption, digestive issues, risk of osteoporosis.
Same question. One word difference. Two different directions.
This makes me take everything with a pinch of salt when I ask "Would Library A be a good fit for Problem X" - which is obviously a bit leading; I don't even trust what I hope are more neutral inputs like "How does Library A apply to Problem Space X", for example.