Is prompt engineering a snake oil? The engineering, as the word stands so far in history is about observing clear limitations and capabilities of something and then "engineering" things around it such as "engineering a compiler" is all about knowing the underlying processor, memory and other characteristics and then engineering a solution that converts a text notation to a stream of instructions that try to strike a balanced tradeoff.
But with LLMs, no one knows their workings once they are trained. The other day, Bark model[0] for text to speech, the team itself has following to say on details:
> Below is a list of some known non-speech sounds, but we are finding more every day. Please let us know if you find patterns that work particularly well on Discord! [laughter], [laughs], [sighs]....
So that's the team themselves not knowing what their model is capable of then how come prompt engineering is any engineering at all?
But with LLMs, no one knows their workings once they are trained. The other day, Bark model[0] for text to speech, the team itself has following to say on details:
> Below is a list of some known non-speech sounds, but we are finding more every day. Please let us know if you find patterns that work particularly well on Discord! [laughter], [laughs], [sighs]....
So that's the team themselves not knowing what their model is capable of then how come prompt engineering is any engineering at all?
[0] https://github.com/suno-ai/bark