For about two years, "prompt engineer" was a job you could put on a resume and watch people's eyebrows go up. Six-figure listings, breathless threads about the magic phrase that cracked GPT open, whole courses selling the secret incantations. I want to be careful here, because the backlash overcorrected. Writing good prompts is a genuine skill and it will stay one. It is just not a career, and pretending otherwise did nobody any favors.
Here is the distinction that got flattened. A skill is something you use inside a job. A career is the job. Spreadsheet formulas are a skill. "Excel engineer" was never a role, even in the years when knowing Excel cold made you far more valuable than the person next to you. Prompting is heading down the same road, and quickly.
The tricks are decaying on purpose
Think about what the famous prompt hacks actually were. "Let us think step by step." "You are a world-class expert." "I will tip you 200 dollars." "Take a deep breath." These worked because early models needed a nudge to behave, and people found the nudges by trial and error. They were patches for the model's weaknesses.
But every one of those weaknesses is a bug the labs are actively fixing. Reasoning models now think step by step without being asked, because that behavior was trained in. Newer models shrug off the fake tip and the flattery because they were tuned to ignore that kind of manipulation. The clever phrase that earned you a screenshot last year does nothing this year, and that is not an accident. The whole direction of model development is to understand what you meant, so you have to say less. A skill built entirely on the model failing to understand you has a short shelf life by design.
I have watched people memorize prompt templates the way you would memorize keyboard shortcuts, and then act surprised when a model update makes half of them pointless. The templates were never the skill.
What actually survives
Strip away the incantations and look at what makes one person consistently get better results than another. It is not secret words. It is that they can state what they want. They know what a good answer looks like before they ask. They give the relevant context and leave out the noise. They notice when an output is subtly wrong and can say why. They break a fuzzy goal into parts a machine can actually chew on.
Notice that none of that is about the model. That is editing, specification, and clear thinking, the same muscles a good manager uses to brief a new hire or a good writer uses to structure an argument. Those skills were valuable before language models and they will be valuable after, because they are about knowing your own mind well enough to hand the intent to someone, or something, else.
The parts of prompting that do stay technical are drifting toward normal engineering anyway. Structuring context, wiring up tools, chaining calls, evaluating outputs at scale, managing what goes in the window. That work is real and growing, but it looks like software work, and the people doing it call themselves engineers, not prompters.
So what should you do with this
Learn to prompt well. Seriously. Anyone who uses these tools daily should get fluent, the same way anyone in an office should be able to write a clear email. Fluency compounds and it is cheap to acquire. Just do not build an identity on it, and do not pay a lot for a certificate in it.
If you want the durable version of this skill, practice saying exactly what you mean to a smart colleague who takes you completely literally and has no idea what is in your head. That is most of prompting, and it happens to be most of thinking clearly, which was always the thing worth getting good at. The models will keep meeting you halfway. Your job is to have something worth meeting them with.