Writing a prompt isn't engineering. It's typing.
You type what you want. The AI figures out the rest That's not a skill. that's having a conversat...
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Yeah "prompt engineer" is just a hype/marketing-driven BS term - we're still "software engineers" or "developers", prompting is only one aspect of a vast array of skills ...
Main takeaway - the foundations of our profession are still the same, and are still of vital importance - AI is just a tool to arrive at a result quicker ...
P.S. what's with the missing periods between sentences? :-)
prompt engineer job is dead!
They should just stop using that term, unless it's for business users who are "vibe coding" apps - fine with me to call them "prompt engineers" ;-)
We should instead call it as "Dumb Engineers" as the whole thing about the AI doesn't make sense at all. There is ZERO intelligence and nobody knows how it internally works including the so-called creators of AI 🤣
Haha, "dumb engineers", I like that ...
Interesting (and true) that nobody really knows how LLMs produce their magic, they call it "emergent behavior" ... on the other hand, nobody understands how our own brains work either - it's just too complex!
Leob agree on all counts Prompt engineer is marketing The foundations haven't changed. AI is a tool, not a replacement for judgment.
Periods fixed Thanks for the catch and the thoughtful comment. 🙌
Interesting article! I agree with your core premise, but I think it helps to draw a line between conversational usage and actual systems engineering.
You made a great point that 'Prompting isn't the skill. Judgment is.' I couldn't agree more. But isn't it very similar with traditional coding? Knowing syntax without technical judgment leads to fragile systems, but having great judgment without knowing how to properly formulate the logic limits what you can build. It’s the combination of both that makes a great developer.
To me, natural language is just a new abstraction layer, much like Python was to C. When you're integrating an LLM into a production app, you still have to manage context windows, mitigate hallucinations, enforce strict formatting, and orchestrate tools. And how do you manage all this technical complexity under the hood? Through prompting (system prompts, semantic routers, etc.). Structuring these instructions and making them reliable and testable via evals is exactly what true 'Prompt Engineering' is."
I think the frustration you're highlighting comes from the buzzword abuse. Generating a script in ChatGPT is a bit like using Wix to build a website: it's incredibly useful and fast, but it's not engineering. However, that shouldn't take away from the very real technical discipline required to build complex, AI-driven systems under the hood.
You've articulated the nuance I should have included. Thank you Natural language is a new abstraction layer, like Python was to C. yes. The abstraction doesn't make the underlying engineering less real.
Prompting isn't the skill. Judgment is. Same with traditional coding. fair point. Syntax without judgment is useless. Judgment without syntax (or prompt structure) is also useless.
The distinction you're drawing between chatting with ChatGPT (low stakes, anyone can do it) and engineering production AI systems (context windows, hallucinations, structured outputs, evals) is exactly the line I blurred My frustration is with the buzzword abuse. The person who generates a script and calls themselves a prompt engineer is like someone who drags a Wix template and calls themselves a web developer.
But the person building reliable, testable, production-grade agent systems? That's real engineering. And yes, that requires structured prompting.
Thanks for the thoughtful pushback it made the conversation better. 🙌
Thanks! I completely understand your frustration with the buzzword abuse—it drives me crazy too. That’s actually why I'm actively trying to change this perception and show people what real, production-grade LLM engineering actually looks like.
Really enjoyed the exchange, thanks for being so open to the nuance!
Trying to change the perception and show what real production-grade LLM engineering looks like that's the work that matters. Not defending a title, just building good systems and letting the work speak.
Thanks for the thoughtful conversation, Quentin. 🙌
Those who know how to talk and interact with the AI, knows what is a prompt. Well, the majority of them think of it as a magic or some kind of Alien Intelligence.
A prompt is a means to communicate your intent to the LLM. That's it. Period!
Ranjan Prompt is a means to communicate your intent That's it. Period Couldn't have said it better.
The magic isn't in the prompt The magic is in the intent knowing what you want, why you want it, and whether the answer is right. The prompt is just the messenger.
Thanks for the crisp take. 🙌
Interesting perspective. I’d frame it slightly differently: prompting is easy to learn, but consistently getting valuable outcomes from AI isn’t.
The biggest difference I see between experienced engineers and everyone else isn’t who can write the cleverest prompt it’s who can spot hidden assumptions, evaluate trade-offs, and recognize when an answer is confidently wrong.
That’s why AI has made judgment more valuable, not less. Code generation is increasingly commoditized, but architecture, debugging, scalability, security, and long-term maintainability still require human experience.
We’ve seen this repeatedly at IT Path Solutions while working on AI-assisted development projects: the speed gains come from AI, but the success of the product still depends on the people making the engineering decisions behind it.
Prompts start the conversation. Judgment determines whether the result survives production.
Mateo prompting is easy to learn, but consistently getting valuable outcomes from AI isn't That's the distinction the article missed the biggest difference isn't who can write the cleverest prompt it's who can spot hidden assumptions, evaluate trade-offs, and recognize confidently wrong answers.
This is the line The prompt is visible. The judgment is invisible. And the invisible part is what separates reliable engineers from everyone else AI has made judgment more valuable, not less.
Yes. The commodity (code generation) gets cheaper The rare skill (knowing what good looks like) gets more valuable. Same pattern as every other automation wave.
Prompts start the conversation. Judgment determines whether the result survives production.
Perfect closing line. Thank you for this it's the most balanced comment in the thread. 🙌
Great take. Would you say that ‘prompting’ is more like UI design for LLMs rather than a standalone skill? Because good UI also feels obvious in hindsight but designing it still needs expertise.
Urmia UI design for LLMs brilliant reframe Good UI looks obvious after the fact Designing it takes expertise Same with prompting Anyone can type write a function Crafting prompts that handle edge cases and produce reliable output? That's design.
The problem isn't that prompting takes no skill. It's that we call any prompt engineering.
Thanks for this. 🙌