Prompt engineering became a thing in 2023 and will stop being a thing in 2024.
We’re already seeing signs of its decline, but let me set the stage for those only vaguely familiar.
A prompt engineer is someone who knows how to get an AI (Normally a chatbot, but honestly, any of the raft of generative AI solutions out there for art, literature, code generation, etc.,) to do what is necessary. While at first, no one was really thinking about this, it quickly became clear that getting a quality result required some massaging in the same sense that getting a quality result from a search engine requires a specific ordering of keywords and limiting of possible results. So, as time went on, those who were better at it started being referred to as ‘prompt engineers.’ I am not certain of the genesis of the phrase, but it honestly doesn’t matter for this discussion. The name became a title, and it got popular; there were some crazy claims about exorbitant salaries for a wordsmith that made it attractive to many.
AI Tools
For some of my work, we use subcontractors to do technical research. Normally, we use technical people and have them turn out results we know will be topically close, even if they didn’t understand the specific technology when they started researching for us. On occasion, we have tried people with less technical backgrounds, and the results are definitively lower quality. With the advent of decent AI tools, we have done some research on using them for this work and have discovered that they allowed less technical people to generate roughly the same quality of results as the more skilled folks.
What this approach doesn’t do is raise either of these researcher types to the level of being able to do something with the results or understand the market well enough to determine results. And we see this across the board. In our development/scripting work, we use generative AI to help, but it doesn’t write finished code complete with the context of our tools/environment. We do that afterward, along with validating the code it does produce. My other business is in publishing and uses a lot of art, so we have contacts with a fair number of artists. Our art director uses generative AI for inspiration but not creation. She asked the other artists we use to follow that example at least until the courts work out IP law about generative AI, and across the board they came to the same conclusion. Some artists are using it for personal/learning purposes, but most AI-generated art is not being generated by professional artists. That has the usual implications for professional artists, but they’re used to being under-appreciated and being underpaid for their work … whether it’s an AI depressing costs versus an amateur doesn’t matter much in context.
Learn it and Use It
Prompt engineering will steadily become less necessary due to simple forces. Just like people learned the ins and outs of search engine prompts, they will learn to do so with AI in their space. As the AI gets more training/specialization, it will get easier to use, and at the same time, it will get more accurate. So, my advice is the same as with all automation tools. Learn it, see how it fits into your organization and use it to your advantage. But it’s not a career; it’s an automation tool. As time goes on, it will be able to do more and more, and maybe one day we’ll be able to say, “Hey Google, write me a CRM that works with our billing system.” But for the foreseeable future, focus on coding and use it to do some of the grunt work.
The only caveat I have also offered before. Go out of your way to hire and train good entry-level people. The weakness of AI doing a lot of the grunt work is that the “learning period” is shorter, so you do need to consciously say, “What is necessary to debug and/or manage our systems?” and make certain your entry-level people get that – because the day-to-day that they have traditionally trained in is far smaller.
And use it to create and maintain even better systems in the new year! I am stoked about the possibilities it opens up, and you should be, too. If I don’t have to write and debug that for loop, just generate, review and test, I’m thrilled. We should all be happy to use that time on more productive things than entry-level code.
