Software Engineering is kinda fake, especially in industry, but at least that's an actual discipline.
"AI monkey" is a better description
Using LLMs to solve real problems is not easy. Making sure that you don't introduce regressions while making improvements is difficult, and requires building and evaluating a dataset, and the necessary pipelines. It may also include diversification of LLM providers, and creating the necessary abstractions. A fundamental understanding of how LLMs work, ability to compare different architectural approaches, along with typical data engineering and software development skills would be required.
What if you want to use the LLM for Question/Answer systems that requires working with embeddings? What if you want to find a way to process data locally without sending sensitive data to the LLM provider?
This requires real engineering skills.
Yes it is.
That is exactly why products like ChatGPT have been taking off as quick as they have.
What you're talking about is not using LLMs as a product but using them as a component within a broader system. And so of course that requires engineering skills.
It's highly unlikely that anyone taking this effort seriously is copying and pasting from ChatGPT, rather than using the API and building pipelines as part of a broader system.
Instruction-fine-tuned LLMs like ChatGPT require creating, validating, and maintaining prompts. Finding ways to use them safely is also not easy - prompt injection and hallucination are just 2 potential pitfalls - there are many more.
Denigrating this effort as "AI monkey" is myopic at best, but really just comes across as a signal that someone is terrified of being replaced by this new tech. With that attitude, they will be.
>What if you want to [do software engineering]?
Then you're a software engineer. Writing prompts isn't engineering. Building systems is engineering. Just because I use keyboards to program doesn't mean I'm a keyboard engineer, does it?
Otherwise, the job title would be "prompt writer".
Your point is what, that existing engineering titles cover this effort? Sure, you can just call all of it software engineering, but sometimes it's useful to be more specific. The LLMs are so powerful now that this new, more specific title makes sense to me, and clearly those using this new title. We'll see how it pans out over the next few years.
A more charitable description might be "You're employing the scientific method to extract value from GPT-like systems." Just like in science, with time you're developing intuition for how the underlying system works, but you still have to run the experiments.
"Google for Dummies"