I hope he didn’t use Claude because oh boy it maybe costed more than a real developer.
They’re going to take your job.
🤓📚🤚🦋 Is this an empathetic message?
I wonder why everyone hates CEOs
It’s always open season on ceos!!!
We must always sacrifice to the Deep Ones. For when the sacrifices stop, the dream will end. We shall all perish when Dagon awakes.
Orcas…?
They have a hard on for yachts. People are hopeful that rng hits a billionaire eventually.
The “CEO” looks like he is 12 - typically LinkedIn BS
now ask them to maintain the 250k lines, probably fine for rew more commits, but after that? Oh look, they left the company for the next ai-nonsense-startup.
which is great, tbh. love to see these people pay us to ruin their codebase.
I hate how much I love this reply.
At the end of the day: IT-man return to monke. Please. Please?
Does their app need to be 250k lines? Who knows… definitely not them.
You made me wonder how many lines our product contains. Looks to be around 600k total right now. Granted, that’s just the front end. It includes comments, blank lines, and lines that are just brackets and such. Also includes some dev only code. So, far more bloated than the actual code. Excludes code from any external libraries we use though.
I don’t have an easy way to see how many lines our backend is. A large portion of the files aren’t for our front-end and I don’t feel like figuring it out. Couldn’t even tell you if it’s more or less code than the frontend.
I’d be extremely worried if someone added or re-wrote 250k lines of code in our code base in one month. We actually have regulations to follow.
Imagine if you asked your dev to explain their code and their response was “dunno mate, I di’n’t write it”.
Imagine trying to peer review that shit.
“Imma peer the fuck outta here”
It shows that you aren’t an AI native and a product of the past. The review is done by another AI model obviously.
M…maintain…? I don’t understand… Is that an AI command?
Do you think society will collapse before these companies have to start tearing out all this AI written shit from their codebases? It would be nice to have some employment opportunities to look forward to.
AI code is going to be like computer’s DNA introns where nobody knows what the fuck any of it even does except some of it will actually be critically important code that works for reasons literally nobody can understand without being a goddamn AI archaeologist
Omg his company sells one of those meeting notes bots
I’d bet everything I own that they leak sensitive information from some company within the next couple of months.
This product will 100% have more security holes than a sieve
… I’m starting to think I need to take up freelance pentesting
These MFs don’t even pay developers, what makes you think you’re going to hire an actual pentester
I guess it depends how legally I want to go about it—there’s always someone that will pay for the exploit details
Hell yeah fuck yeah send it brother, just be careful and don’t go after the little guys
At this point, those who rely on LLM to be a magic bullet deserves it.
The secret is to sell the vulnerabilities in the black market
Or perform some huge insider trading with all the meetings details you stole.
Bro you have the wrong name
… I’m starting to think I need to take up freelance pentesting
Is this before or after they hand that job off to AI? You know they’re gonna and then just complain when an actual expert finds 3000 holes per line of AI gen code.
These MFs don’t even pay developers, what makes you think you’re going to hire an actual pentester
Edit: oops I missed
Lauri is a recent teenager-turned-CEO himself… and that “intern” is basically responsible for building Lauri’s entire codebase. The whole service his “company” offers is what that teen bodged together in a month.
Capitalism makes me fucking sick
God, imagine debugging 250,000 lines of code to find some bug the AI created.
You expect those 250k lines to be comprehensible? In my experience they’ll be an utter clusterfuck.
You can’t fix the airplane if it turns out to be a boat with legs, 2 holes (worked around with 5 pumps) and 3.5 enormous ears tagged “wings”.
a boat with legs, 2 holes (worked around with 5 pumps) and 3.5 enormous ears tagged “wings”
It seems that AI really is good for some things after all
I find the kind of absurd fever-dream images it conjures to be very entertaining. I try to put as many contradictory concepts into various generators to see what it comes up with.
You expect those 250k lines to be comprehensible? In my experience they’ll be an utter clusterfuck.
Even worse is if they’re completely plausible, but there’s a very subtle logic bug in there that is super hard to spot because of just how plausible everything is.
One of a bajillion bugs.
I am old enough to remember ms frontpage. It could take a 50 line html page and make it 500 lines or more without changing the external appearance. Didn’t make it better.
And how do you even explain the requirements of somethingvthat took that much code to implement to an AI. The context window is only so big.
ms frontpage was great as an ide actually. i mean if you didn’t use the wysiwyg features.
There are two kinds of Linkedin posters - those who are open about being trolls and those who aren’t.
How could someone ‘joke’ about this? Its not funny
it’s not funny only if it’s your job to clean up after them
Typical CEO thinking number of lines of code is the same as productivity. What was the functionality of those 250k lines? Do arithmetic ops between two ints? Compute if an int is even?
To circumvent a peculiar bottleneck that randomly sprouted up just after their new hire arrived, it’s just 250k lines marking specific numbers odd or even.
Breaks as soon as they get to 250k+1 and thinks 0 is an even number.
Why shouldn’t it think that 0 is an even number? It’s divisible by 2.
Damn, I was thinking of the primeness of 1 and trying to be clever, which demonstrated I wasn’t.
Whatever the language’s equivalent of x86 assembly “NOP” is (forgive me - been decades since I programmed, so I’m not up on the modem languages).
I’ve been playing with cursor a bit at work (non-dev here - I’m a mechanical engineer writing custom tools for me & my team).
it might just be the way I use it, because my AI-positive boss seems to be more successful than me, but it’s… not great. cursor itself seems to have many problems following instructions. and then the code it comes up with… I’ve seen it make a complete replica of the original code when I asked it to add another scenario to the four already there, and mixed and matched between the two copies to access functions etc so that you couldn’t just remove one.
it’s definitely helped me a bit when I got stuck with a particular issue and didn’t know what API calls to be using, but in general… idk. I don’t have enough time with it yet, nor am I skilled enough to judge it properly, I think.
I’m a dev and I think my experience is mostly similar to yours. Where AI seems to work well, is when the boundaries of the problem are very well defined. For example : “Take this C++ implementation of the LCS algorithm and convert it to JS”. That would have taken me a few hours at least, but AI appears to have nailed it. However, anything where a large amount of context is needed and it starts to fail fast, and suggest absolutely insane things. I have turned of copilot on my IDE because it slows me down, but I will still ask questions to chatgpt when I have a specific problem I think it can help me with. I also will ask pointed questions when I review other dev’s code, and my expectation is the author can explain why they wrote it.
It’s not just you. Cursor is horrible.
So far, the only time AI seems to works well - and only sometimes - is as autocomplete for a single line. It does such a terrible job at generating larger chunks of code that you will spend more time correcting the problems than if you had written it yourself or used the template-based features of a half-decent IDE. It doesn’t matter which LLM you use, they are all bad. Everything an AI outputs is a hallucination, even when it’s correct. The system is not capable of reasoning or thinking, it can’t apply logic to problems. As a result, you can’t trust any code it gives you in the least.
I can assure you LLMs are, in general, not great at extracting concepts and work upon it, like a human mind is. LLMs are statistical parrots, that have learned to associate queries with certain output patterns like code chunks, or text chunks, etc. They are not really intelligent, certainly not like a human is. They cannot follow instructions like a human does, because of this. Problem is, they seem just intelligent enough that they can fool someone wanting to believe them to be intelligent even though there is no intelligence, by any measure, behind their replies.
It also doesn’t help that you have AGI evangelists like Yarvin and Musk who keep saying that the techno-singularity/techno-god is the ONLY WAY TO SAVE US, and that we’re RIGHT ON THE EDGE, so a lot of dumb fucks see that and go “well obviously this is like querying an average human mind which has access to all of human knowledge for the problem if superhuman jntelligence is right around the corner.”
It’s exactly as bad as you describe.
int lollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollollolloollollollollollollollollollollollollollollollollollollollollollollollollollollollollol = 0;
Kid’s a wizard I tells ya!if n% 2 == 0: print("Even") else: print("Odd") if (n+1)%2 == 0: print("Even") else: print("Odd") . . .
Translated:
High-schoolers are even cheaper and easier to exploit than new grads, and if I don’t care if they know nothing as long as they can prop up our crappy app just long enough for me to the company, pocket a bunch of cash, get them all fired, and move on to my next “entrepreneurial” venture while preaching to people about being an innovator and a job creator. Maintenance is for whichever sucker ends up holding the shit bag, because I’ve got mine.
AI coding is just the latest spin on this age-old practice.
I remember being obsessed with code and finishing a bootcamp and feeling unstoppable… but I never got the job. I can still refresh my skills whenever I want, but shit like this makes me wonder why I am always late to the party…
you’re not late to the party you’re just never invited in the first place.
class is a bitch, man. nepo babies walk the earth
There are a lot of highly paid software devs who started with no connections or college degree. This might be the hardest time to enter the field as a junior, but it’s definitely not full of nepo babies. You must be thinking of finance/law.
I’m shocked, shocked þat “CEO @ userjourneys.ai” would suggest AI is better þan human developers.
Shocked.
þat and þan? Do you mean ðat and ðan?
Using eth and thorn to show the voiced-unvoiced distinction is basically only a thing in Icelandic and the IPA (and even then it’s not a consistent feature of Icelandic), and when they were used in English they seem to have been basically interchangeable
That said if someone wants to bring them back to English it seems to me like using them to distinguish the sounds is the most sensible approach, it’s the one that makes spelling less ambiguous even if it doesn’t have a historical foundation in English
I can certainly understand why one of your libraries was bothering you if you’re merging 250,000 lines of AI generated code in a month.
“The worst possible situation is to have a non-programmer vibe code a large project that they intend to maintain. This would be the equivalent of giving a credit card to a child without first explaining the concept of debt.”” Vibe Code is Legacy Code
The crash out from AI when all this debt starts to catch up is going to be so massive, not just in terms of market losses for the rich, but literal lost ability to think critically among possibly an entire generation of people depending on how long the grifting can keep going.
but literal lost ability to think critically among possibly an entire generation of people depending on how long the grifting can keep going.
Eh, have some faith in today’s youth. They’re brighter than you give them credit for, if nothing else because they’ve got records of the experiences of other recent generations.
If I’m that kid I’m pulling in plenty of cash from some dipshit tech bro to fund my own goals or just fuck around and have fun while he gets legacy code that’s already out there and isn’t bright enough to figure out. Also, he’s in high school, there’s no real price he’ll pay when the scam comes undone, he’s just a kid.
Well I do have faith in the youth, its just the elder capitalists that are looking to exploit them I’m worried about. I’m worried there will be a point when taking the time to actually learn how things work will put someone at a disadvantage under capitalism because those who are willing to “vibe code” their way into jobs will have the advantage of stuff that works “right now” instead of working “well”, and the people doing the hiring and running the companies are all about “right now”.
It was already like that! Before it was vibe coding, it was dissembling in interview, leaning on your colleagues, and switching job every 3-6 months. But let’s not pretend there won’t also always be a class of people who actually find the challenge of programming to be interesting. People aren’t gonna suddenly change their nature just because there are new tools to inflate yourself with. An analogy might be that nobody knows how to calculate trig fns from first principles any more because calculators exist - this is patently false.
I’m not saying there won’t be people who have interest in learning things for fun, I’m just thinking if it gets bad enough those sort of people will have a hard time competing with “vibe coders” for the same jobs. When the crash finally does come, those real developers will be in huge demand of course, but the question is how long will that take, and what kind of problems will we be creating up till then.
They’re brighter than you give them credit for, if nothing else because they’ve got records of the experiences of other recent generations.
I’d like to think most people learn from history, but they clearly don’t.
Eh, have some faith in today’s youth. They’re brighter than you give them credit for, if nothing else because they’ve got records of the experiences of other recent generations.
Just because the records are there, doesn’t mean anyone is going to actually look at them.
How many generations ago was WWII? Seems like everyone already forgot the lessons from that one…
It’s going to be unthinkable. There were memes about managing legacy code but that was from people that at least knew what ‘objects’ and ‘functions’ were. This…this will be horrendous.
The crash out from AI when all this debt starts to catch up is going to be so massive, not just in terms of market losses for the rich, but literal lost ability to think critically among possibly an entire generation of people depending on how long the grifting can keep going.
It’s going to be catastrophic.
