What prompt did you use to make this 🤨🤔
The irony. I bet the guy who prompted that calls himself an artist.
Was going to comment about how there is a stock photo for everything. Fingers seem too good for AI?
Nevermind, that kids right hand… 😅
Also: the middle fingers are far too long
Now look at his eyelids…
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https://knowyourmeme.com/memes/family-laughing-at-crying-child-opening-christmas-present
That includes some history, but not the prompt itself.
That’s why I’m proud to be also programming in HTML
it’s only real programming if you also use CSS
It’s only real gatekeeping if you have a physical gate
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“Engineering”
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Yeah, well, like most software engineers lol
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They’re not engineers and they’re too chicken shit to act like engineers.
Looks like an ai did that
HATERS will say it’s fake
If you look close enough, all pictures are fake.
Is that you, Samsung?
Hey, no need to accuse the guy of cutting tvs to get out of honoring the warranty.
And HATERS will be absolutely correct
That’s the joke.
“prompt engineering” in itself is such an embarrassing term for the act of saying “computer uhhh show me epic boobies!!”
like that joke about calling dishwashing “submerged porcelain technician” but unironically
Making middle management do everything is not ‘running a business’.
If middle management is doing everything aren’t they no longer middle management?
They get middle paychecks.
And vetoed on sensible decisions in favour of non-sensible ones that make the upper management larger bonuses.
It’s not engineering either. Or art. It’s only barely writing, in an overly literal sense.
People in glass houses…
Software engineering isn’t engineering.
Yes, it is. Mostly because “real engineering” isn’t the high bar it’s made out to be. From that blog:
Nobody I read in these arguments, not one single person, ever worked as a “real” engineer. At best they had some classical training in the classroom, but we all know that looks nothing like reality. Nobody in this debate had anything more than stereotypes to work with. The difference between the engineering in our heads and in reality has been noticed by others before, most visibly by Glenn Vanderburg. He read books on engineering to figure out the difference. But I wanted to go further.
Software has developed in an area where the cost of failure is relatively low. We might make million dollar mistakes, but it’s not likely anybody dies from it. In areas where somebody could die from bad software, techniques like formal verification come into play. Those tend to make everything take 10 times longer, and there’s no compelling reason for the industry at large to do that.
If anything, we should lean into this as an advantage. How fast can we make the cycle of change to deployment?
I help make Healthcare software. Mistakes can easily lead to death. Not most, but it’s something we always have to worry about.
We might make million dollar mistakes, but it’s not likely anybody dies from it.
I had a coworker who got a gig writing PDA software for a remote-controlled baseball machine. He was to this day the most incompetent programmer I’ve ever met personally; his biggest mistake on this project was firing a 120 mph knuckleball (a pitch with no spin so its flight path is incredibly erratic) a foot over a 12-year-old kid’s head. This was the only time in my 25-year career that I had to physically restrain someone (the client, in this case) to prevent a fist fight. I replaced my coworker on the project after this and you can bet I took testing a little bit more seriously than he did.
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It gives Kerbal Space Program energy.
In many cases this is accurate. Programming alone doesn’t amount to engineering. Lotta low quality lines of code being churned out these days because standards have dropped.
By how some teams operate, and some developers think, there is certainly cases where the “engineering” aspect is hard to find.
mm yes ai
But is “prompt hacking” considered actual “hacking?”
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Build an entire ecosystem, with multiple frontends, apps, databases, admin portals. It needs to work with my industry. Make it run cheap on the cloud. Also make sure it’s pretty.
The prompts are getting so large we may need to make some sort of… Structured language to pipe into… a device that would… compile it all…
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Perfect! We’ll just write out the definition of the product completely in Jira, in a specific way, so the application can understand it - tweak until it’s perfect, write unit tests around our Jira to make sure those all work - maybe we write a structured way to describe each item aaand we’ve reinvented programming.
I see where you’re going, but I’ve worked with AI models for the last year in depth, and there’s some really cool stuff they can do. However, truly learning about them means learning their hard pitfalls, and LLMs as written would not be able to build an entire application. They can help speed up parts of it, but the more context means more VRAM exponentially, and eventually larger models, and that’s just to get code spit out. Not to mention there is nuance in English that’s hard to express, that requirements are never perfect, that LLMs can iterate for very long before they run out of VRAM, that they can’t do devops or hook into running apps - the list goes on.
AI has been overhyped by business because they’re frothing at the mouth to automate everyone away - which is too bad because what it does do well it does great at - with limitations. This is my… 3rd or 4th cycle where business has assumed they can automate away engineers, and each time it just ends up generating new problems that need to be solved. Our jobs will evolve, sure, but we’re not going away.
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lol okay dude. Flippantly you ignored all of the limitations I pointed out. Sure it could happen, but not on the timeline you’re discussing. There is no way within a year that they have replaced software engineers, I call absolute BS on that. I doubt it will rise above copilot within a year. I see it being used alongside code for a long time, calling out potential issues, optimizing where it can, and helping in things like building out yaml files. It cannot handle an entire solution, the hardware doesn’t exist for it. It also can’t handle specific contexts for business use-cases. Again maybe, but it’ll be a while - and even then our jobs shift to building out models and structuring AI prompts in a stable way.
My attitude is the same because these are the same issues that it’s faced. I’m not arguing that it’s not a great tool to be used, and I see a lot of places for it. But it’s naiive to say that it can replace an engineer at it’s stage, or in the near future. Anyone who has worked with it would tell you that.
I firmly do think companies want to replace their 250k engineers. That’s why I know that most of it is hype. The same hype that existed 20 years ago when they came out with designers for UIs, the same hype when react and frontend frameworks came out. Python was built to allow anyone to code, and that was another “end of engineers”. Cloud claimed to be able to remove entire IT departments, but those jobs just shifted to DevOps engineers. The goalposts moved each time, but the demand for qualified engineers went up because now they needed to know these new technologies.
Why do you think I worked with AI so much over the last year? I see my job evolving, I’m getting ready for it. This has happened before - those who don’t learn new tech get left behind, those who learn it keep going. I may not be coding in python in 10 years, god knows I wasn’t doing what I was 10 years ago - but it’s laughable to me to think that engineers are done and over with.
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It will happen, probably in weeks to months.
in the next few years, like, very few
Now who’s moving the goalposts…?
There are no models good enough to just ask for something to be done and it gets done.
We call those “compilers”. There are many of them.
BUT I TOOK ALL THESE COURSES!
I only program with LBP2 microchips.
I also can make up words.
hörgenmal
