Throw up a search result that just uses cosine similarity on the vector search with questionable metrics and no explanations on how things are calculated.
Charge yearly because you know people will churn after a month or two.
Profit
- Every "AI startup" in the last 2 months
Comparing to google search, there definitely is skill involved in knowing how to google things well. We're all accustomed to googling things many times per day so I think a lot of people forget that being able to google things and get the results you want is a skill that has to be learned.
But I would never refer to being "good at writing google search queries" as any kind of engineering. But is becoming good at searching google any less difficult than getting good at writing LLM prompts?
I'd love to hear the other side of the argument. How difficult is it to become good at "prompt engineering"? Why do we even call it "prompt engineering" instead of just "writing effective prompts"?
Edit: I think the main gripe I have with the term "prompt engineering" is it makes the skill of writing prompts sound a lot harder than it actually is. Maybe I'm underestimating how difficult it is to learn how to write good prompts?
I've seen some of the more serious people switch to the term "Applied AI" which I think encompasses the role a lot better. Also I've seen a decent number of grifter types saying they're "prompt engineers" when what they mean is they're writing prompts into ChatGPT's UI, which I think is part of what drives the cringing feeling when you hear the phrase "prompt engineer" and probably drives some of the movement away from the term for engineers.
It is easy to be cynical about the gold rush, but don’t throw the babies out with the bathwater.