I am likely wrong here, but I thought the term “prompt engineering” was also related to the act of building a system around generating a prompt dynamically base

I am likely wrong here, but I thought the term “prompt engineering” was also related to the act of building a system around generating a prompt dynamically based on limited input? Eg not just trial and error over single prompts but using broader techniques like in-context learning, chain of thought reasoning, other AI models (BERT), vector DB etc to build prompts to send to the LLM? I’m likely wrong cause I can’t remember where I read this definition, but IMO it makes more sense that it relates to building systems around promoting, rather than how a single model reacts to very limited circumstances. Models etc are going to change pretty regularly, tiny adjustments in wording will change along with it, so seem to have limited ROI. Broader techniques will become wide spread pretty quickly, how you use them all together in a system I think will be more important over time, but I don’t know, everything is moving so quickly shrugs.