- cross-posted to:
- programming@programming.dev
- cross-posted to:
- programming@programming.dev
“No Duh,” say senior developers everywhere.
The article explains that vibe code often is close, but not quite, functional, requiring developers to go in and find where the problems are - resulting in a net slowdown of development rather than productivity gains.
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Even though this shit was apparent from day fucking 1, at least the Tech Billionaires were able to cause mass layoffs, destroy an entire generation of new programmers’ careers, introduce an endless amount of tech debt and security vulnerabilities, all while grifting investors/businesses and making billions off of all of it.
Sad excuses for sacks of shit, all of them.
Look on the bright side, in a couple of years they will come crawling back to us, desperate for new things to be built so their profit machines keep profiting.
Current ML techniques literally cannot replace developers for anything but the most rudimentary of tasks.
I wish we had true apprenticeships out there for development and other tech roles.
You mean relying blindly on a statistical prediction engine to attempt to produce sophisticated software without any understanding of the underlying principles or concepts doesn’t magically replace years of actual study and real-world experience?
But trust me, bro, the singularity is imminent, LLMs are the future of human evolution, true AGI is nigh!
I can’t wait for this idiotic “AI” bubble to burst.
AI coding is the stupidest thing I’ve seen since someone decided it was a good idea to measure the code by the amount of lines written.
More code is better, obviously! Why else would a website to see a restaurant menu be 80Mb? It’s all that good, excellent code.
It did solve my impostor syndrome though. Turns out a bunch of people I saw to be my betters were faking it all along.
Might be there someday, but right now it’s basically a substitute for me googling some shit.
If I let it go ham, and code everything, it mutates into insanity in a very short period of time.
Almost like its a desperate bid to blow another stock/asset bubble to keep ‘the economy’ going, from C suite, who all knew the housing bubble was going to pop when this all started, and now is.
Funniest thing in the world to me is high and mid level execs and managers who believe their own internal and external marketing.
The smarter people in the room realize their propoganda is in fact propogands, and are rolling their eyes internally that their henchmen are so stupid as to be true believers.
Imagine if we did “vibe city infrastructure”. Just throw up a fucking suspension bridge and we’ll hire some temps to come in later to find the bad welds and missing cables.
Glad someone paid a bunch of worthless McKinsey consultants what I could’ve told you myself
It is not worthless. My understanding is that management only trusts sources that are expensive.
Yep, going through that at work, they hired several consultant companies and near as I can tell, they just asked employees how the company was screwing up, we largely said the same things we always say to executives, they repeated them verbatim, and executives are now praising the insight on how to fix our business…
I code with LLMs every day as a senior developer but agents are mostly a big lie. LLMs are great for information index and rubber duck chats which already is incredible feaute of the century but agents are fundamentally bad. Even for Python they are intern-level bad. I was just trying the new Claude and instead of using Python’s pathlib.Path it reinvented its own file system path utils and pathlib is not even some new Python feature - it has been de facto way to manage paths for at least 3 years now.
That being said when prompted in great detail with exact instructions agents can be useful but thats not what being sold here.
After so many iterations it seems like agents need a fundamental breakthrough in AI tech is still needed as diminishing returns is going hard now.
If it wasn’t for all the AI hype that it’s going to do everyone’s job, LLMs would be widely considered an amazing advancement in computer-human interaction and human assistance. They are so much better than using a search engine to parse web forums and stack overflow, but that’s not going to pay for investing hundreds of billions into building them out. My experience is like yours - I use AI chat as a huge information index mainly, and helpful sounding board occasionally, but it isn’t much good beyond that.
They are so much better than using a search engine to parse web forums and stack overflow,
The hallucinations (more accurately bullshitting) and the fact they have to get new training data but are discouraging people from engaging in the structures that do so make this highly debatable
I agree that it is certainly debatable. However, my experience has been that information extracted about, say what may cause a strange error message from some R output, has been at least as reliable as random stack overflow posts - however, I get that answer instantly rather than after significant effort with a search engine. It can often find actual links better than a search engine for esoteric problems as well. This, however is merely a relative improvement, and not some world-changing event like AI boosters will claim, and it’s one of the only use-cases where AI provides a clear advantage. Generating broken code isn’t useful to me.
I will concur with the whole ‘llm keeps suggesting to reinvent the wheel’
And poorly. Not only did it not use a pretty basic standard library to do something, it’s implementation is generally crap. For example it offered up a solution that was hard coded to IPv4, and the context was very ipv6 heavy
I have a theory that it’s partly because a bunch of older StackOverflow answers have more votes than newer ones using new features. More referring to not using relatively new features as much as it should.
it’s slowing you down. The solution to that is to use it in even more places!
Wtf was up with that conclusion?
I don’t think it’s meant to be a conclusion. The article serves as a recap of several reports and studies about the effectivity of LLMs with coding, and the final quote from Bain & Company was a counterpoint to the previous ones asserting that productivity gains are minimal at best, but also that measuring productivity is a grey area.
Senior Management in much of Corporate America is like a kind of modern Nobility in which looking and sounding the part is more important than strong competence in the field. It’s why buzzwords catch like wildfire.
Lmao calling nobility would imply we can’t vote our senior management and it often ends up being whoever “the king” wants or one of king’s children.
Wait…
I have been vibe coding a whole game in JavaScript to try it out. So far I have gotten a pretty ok game out of it. It’s just a simple match three bubble pop type of thing so nothing crazy but I made a design and I am trying to implement it using mostly vibe coding.
That being said the code is awful. So many bad choices and spaghetti code. It also took longer than if I had written it myself.
So now I have a game that’s kind of hard to modify haha. I may try to setup some unit tests and have it refactor using those.
Sounds like vibecoders will have to relearn the lessons of the past 40 years of software engineering.
As with every profession every generation… only this time on their own because every company forgot what employee training is and expects everyone to be born with 5 years of experience.
Wait, are you blaming AI for this, or yourself?
Blaming? I mean it wrote pretty much all of the code. I definitely wouldn’t tell people I wrote it that way haha.
It remains to be seen whether the advent of “agentic AIs,” designed to autonomously execute a series of tasks, will change the situation.
“Agentic AI is already reshaping the enterprise, and only those that move decisively — redesigning their architecture, teams, and ways of working — will unlock its full value,” the report reads.
“Devs are slower with and don’t trust LLM based tools. Surely, letting these tools off the leash will somehow manifest their value instead of exacerbating their problems.”
Absolute madness.
How are you interpreting it that way. Did you miss a sentence or something in the quote?
It’s not interpretation, it’s extrapolation.
There’s quotes.
Are you trying to tell me that the people wanting to sell me their universal panacea for all human endeavours were… lying…? Say it ain’t so.
I mean, originally they thought they had come upon a magic bullet. Turns out it wasn’t the case, and now they’re going to suffer for it.
You’re assuming honesty and they’ve earned the opposite posture.
I use AI as an entryway to learning or for finding the name or technique that I’m thinking of but can’t remember or know it’s name so then i can look elsewhere for proper documentation. I would never have it just blindly writing code.
Sadly search engines getting shitter has sort of made me have to use it to replace them.
Then it’s also good to quickly parse an error for anything obviously wrong.
LLMs work great to ask about tons of documentation and learn more about high-level concepts. It’s a good search engine.
The code they produce have basically always disappointed me.
I sometimes get up to five lines of viable code. Then upon occasion what should have been a one liner tries to vomit all over my codebase. The best feature about AI enabled IDE is the button to decline the mess that was just inflicted.
In the past week I had two cases I thought would be “vibe coding” fodder, blazingly obvious just tedious. One time it just totally screwed up and I had to scrap it all. The other one generated about 4 functions in one go and was salvageable, though still off in weird ways. One of those was functional, just nonsensical. It had a function to check whether a certain condition was present or not, but instead of returning a boolean, it passed a pointer to a string and set the string to “” to indicate false… So damn bizarre, hard to follow and needlessly more lines of code, which is another theme of LLM generated code.
