I mostly agree with you. But I think we should be weary of statements like this:

> It's very easy to teach someone non-ML or even nontechnical how to do it given a few examples

Because a C programmer could have said the same thing about a Python job posting in 2004. Or an Assembly programmer could have said it about a job posting for a C programmer in 1975.

It's possible that prompt engineering will become the next higher level of abstraction above scripting languages, which means it will have its own ecosystem develop around it while introducing a new audience to the technical domain. That doesn't make it any less of a programming language, even if it appears that way now. Prompt engineering will have its own quirks and what makes a "good" prompt engineer may end up being somewhat distinct from what makes a "good" programmer. Maybe it will turn out that the best prompt engineers are the people most skilled with communicating precisely, which - to be fair - definitely includes programmers, but also opens the field to expert communicators from non-technical domains, like lawyers or editors.

All that said - paying anyone, non-technical or otherwise, $350k for talking to ChatGPT is obviously outrageous.

Most people are already used to prompt engineering thanks to years of using Google. They just aren't fully conscious of that connection yet, as "prompt engineering" sounds far more complex than it actually is.

Also worth noting, prompt engineering is only "difficult" now because the UI is effectively non existent, it's just a text box. This too will improve, and prompt engineering will get easier. It's imperative it becomes easier from the perspective of AI providers.

>That doesn't make it any less of a programming language

I don't see how you can believe that. Prompt engineering will never require learning an entirely new method of communication because the entire point is to communicate in languages you already know to create generations. Just because someone writes "image barn sunny trees" doesn't mean it's incomprehensible to those who know English, definitely not in the same way that "public static void main()" is incomprehensible to those who do understand English but not Java (or it's similar). You might think "well, prompt engineering can turn out the same way that Java example does", but that negates the entire functionality of AI and you're now just programming!

> Prompt engineering will never require learning an entirely new method of communication

No, but it's not like every person in the world is a super competent communicator even in their own language. But I agree the number of competent natural language communicators is an order of magnitude larger than the number of competent programmers. So I do agree with minimaxir that supply will rapidly outstrip demand, and it's unlikely that "prompt engineering" (which is a ridiculously stupid title, btw, can we still change that?) will ever be more highly paid than "real" programming (or whatever is left of real programming, at least).

Still, my point is mostly that we should be weary of making proclamations like this because it's not easy to predict how this field will develop, especially when you consider aspects like domain-specific expertise (e.g. lawyers will be in a better position than programmers to "prompt engineer" a legal contract), and the simultaneous replacement of existing jobs with AI. These factors will blend together to create a mix of incentives that makes it difficult to predict the end result.

I don't think the Assembly/C/Python analogy is perfect, but it's not far off from the truth - we see a new technology ushering in a new wave of people proficient in it, and the temptation is to wave it away as unlikely to affect the status quo, but reality never ends up being so simple.

On the contrary, I was not suggesting it is unlikely to affect the status quo, I think prompt engineering will become so default it's as expected as "can work on a team". Status quo will change, but not in the "direct replacement" theory people are so scared of.

I also don't believe that domain-specific expertise is the big exception here you believe it to be, as domain specific expertise is not gatekept in any efficient form. This will result in people being able to utilize such expertise just through AI - after all, you don't need to be an expert chef to know what a julienne technique is, just ask AI.

This is the new 'social media expert'.

Bracing for Robert Scoble to announce his new AI Whisperer company in his next sexual harassment victim blaming non-apology-apology.

https://web.archive.org/web/20171111033215/https://scobleize...

https://onemanandhisblog.com/2017/10/scoble-utterly-tone-dea...

https://www.theverge.com/2017/10/25/16547332/robert-scoble-s...

>The Verge‘s Adi Robertson sums it us thus: "But his latest defense puts forward an absurd definition of sexual harassment and effectively accuses women of reporting it to fit in with the cool crowd, while claiming he’s writing in “a spirit of healing.” There’s even a tasteless plug for his latest business venture. It’s one of the most disappointing responses we’ve seen to a sexual harassment complaint, which, after the past few weeks, is a fairly remarkable achievement."

I'm no fan of Scoble, but among AI hypemen on Twitter, he's far from influential.

Excellent description, just another gimmick

Except the fact that a vast number of people actually do this for a living and make good money. A good fraction (no comment on whether that’s larger than 0.5 or less) do something real and tangible and produce value to their clients too.

Importantly, the good ones, what they do, is not necessarily something everyone (especially people with the mind of an engineer) can do well even though in paper it’s a stupid job. I can see prompt engineering be the same.

The vast majority of people I’ve seen, the only original things they can think of asking chatGPT is to come up with workout plans or ask unoriginal questions about common societal issues. There’s nuance and imagination involved in figuring out how to effectively interact with this human like system to get it to do exactly what you want.

> it's very easy to teach someone non-ML or even nontechnical how to do it given a few examples

Sounds like we could train an AI to do it.

Just like any position, it's not hard to find X, but hard to find good X'ers. Same is true for developers, there are way more developers than demanded, but what's hard is finding good developers, not just any developer. Same is true for most professions that doesn't rely on certificates and alike (think "real" engineering, like engineering for construction and such).

Quoting myself from the post I linked above: as a machine learning engineer, I can attest that the only reasons machine learning engineers are good at prompt engineering are a) years of practice and b) a tendency to be pedantic assholes. But there are other professions who are even better at being pedantic assholes such as writers and lawyers, so there’s no need for someone with a specialized skillset to do it.

There is some granularity in terms of prompt engineering with ReACT/LangChain, which does require a machine learning background to make any sense out of it because it's very arcane. But that's not what these job openings are looking for, yet.

Requiring pedantry is also a system flaw. One would hope that AI assistants and delegates would understand more about what the human requesters want, and when to ask clarifying questions.

I’ve done dynamic prompt engineering with string concatenation

I’ve used this to create procedurally generated games, and noticed LLMs are able to dynamically generate NPCs and maintain state about those NPCs and their dialogue too

There is no way this is going to be a valuable skillset that humans do for salary. If the humans manage to become significant shareholders of the output or revenue stream, they’ll be fine, but for salary this is not valuable and computers will take prompt engineering too.