- cross-posted to:
- technology@midwest.social
- cross-posted to:
- technology@midwest.social
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AI-generated code contains more bugs and errors than human output
Yeah. No shit. I used an LLM’s “help” to make fin.
It got me reading and debugging more than 10 times the [bad] code, per day, than I had in the entire prior 10 years of using fish. [And reading the documentation way more too, learning a lot.]
… more bugs and errors than human output
However, it’s not necessarily a bad thing, with AI improving efficiency across the initial stages of code generation.
Oh but it’s so effortless. HA! Debugging takes a lot more effort. And then still have to just re-write it all yourself any way.
Still, it’s a good learning experience.
Dear AI,
Thanks for being so shit.
Taught me a lot.
Microsoft: Let’s have it rebuild our most well known product from the ground up!
Almost as if it was made to simulate human output but without the ability to scrutinize itself.
To be fair most humans don’t scrutinize themselves either.
(Fuck AI though. Planet burning trash)
The number of times I have received an un-proofread two sentence email is too damn high.
And then the follow up email because they didn’t actually finish a complete thought
I do this with texts/DMs, but I’d never do that with an email. I double or triple check everything, make sure my formatting is good, and that the email itself is complete. I’ll DM someone 4 or 5 times in 30 seconds though, it feels like a completely different medium ¯\_(ツ)_/¯
It’s like having a lightning-fast junior developer at your disposal. If you’re vague, he’ll go on shitty side-quests. If you overspecify he’ll get overwhelmed. You need to break down tasks into manageable chunks. You’ll need to ask follow-up questions about every corner case.
A real junior developer will have improved a lot in a year. Your AI agent won’t have improved.
This is the real thing. You can absolutely get good code out of AI, but it requires a lot of hand holding. It helps me speed some tasks, especially boring ones, but I don’t see it ever replacing me. It makes far too many errors, and requires me to point them out, and to point in the direction of the solution.
They are great at churning out massive amounts of code. They’re also great at completely missing the point. And the massive amount of code needs to be checked and reviewed. Personally I’d rather write the code and have the AI review it. That’s a much more pleasant way to work, and that way it actually enhances quality.
They are improving, and probably faster then junior devs. The models we had had 2 years ago would struggle with a simple black jack app. I don’t think the ceiling has been hit.
Just a few trillion more dollars, bro. We’re almost there. Bro, if you give up a few showers, the AI datacenter will be able to work perfectly.
Bro.
The cost of the improvement doesn’t change the fact that it’s happening. I guess we could all play pretend instead if it makes you feel better about it. Don’t worry bro, the models are getting dumber!
Don’t worry bro, the models are getting dumber!
That would be pretty impressive when they already lack any intelligence at all.
They might. The amount of money they’re pumping into this is absolutely staggering. I don’t see how they’re going to make all of that money back, unless they manage to replace nearly all employees.
Either way it’s going to be a disaster: mass unemployment or the largest companies in the world collapsing.
I dunno, the death of mega corporations would do the world a great deal of good. Healthier capitalism requires competition, and a handful of corporations of any given sector isn’t going to seriously compete nor pay good wages.
It’s certainly the option I’m rooting for, but it would still be a massive drama and disrupt a lot of lives. Which is why they’ll probably get bailed out with taxpayer money.
Maybe but they also know the fiat currency will collapse sooner rather than later, too. That money is pointless and they are playing the game knowing that as a fact at this point.
And I ask you - if those same trillions of dollars were instead spent on materially improving the lives of average people, how much more progress would we make as a society? This is an absolutely absurd sum of money were talking about here.
It’s beside the point. I’m simply saying that AI will improve in the next year. The cost to do so or all the others things that money could be spent on doesn’t matter when it’s clearly going to be spent on AI. I’m not in charge of monetary policies anywhere, I have no say in the matter. I’m just pushing back on the fantasies. I’m hoping the open source scene survives so we don’t end up in some ugly dystopia where all AI is controlled by a handful of companies.
I have the impression that anti-AI people don’t understand that they are giving up agency for the sake of temporary feels. If they truly cared about ethical usage of AI, they would be wanting to have mastery that is at least equal to that of corporations and the 1%.
Making AI into a public good is key to a better future.
They are having an emotional reaction to this situation so it’s all irrational.
I guess we need to force them to think about what they actually want, because the utopic ideal of putting the AI back in the bag is NOT happening and they best not attempt to take it away from the poor and working class while leaving power free reign of it.
That is the most stupid position you can take on this. Absolutely the most short sighted thought. People need to stop and think logically about this.
None, because none of it would go to attempting to slow climate change. It would be dumped into consumption as always instead of attempting to right this ship.
The suffering is happening regardless.
Yout desire to delay it only leads to more suffering.
Y’all are mourning a what if that was never in the cards for us.
It’s happening regardless. The rich and powerful will have this tech whether you like it or not. Y’all are thinking emotionally about this and not logically. You want to take away this tool from regular people for what reason?
My jr developer will eventually be familiar with the entire codebase and can make decisions with that in mind without me reminding them about details at every turn.
LLMs would need massive context windows and/or custom training to compete with that. I’m sure we’ll get there eventually, but for now it seems far off. I think this bubble will have to burst and let hardware catch up with our ambitions. It’ll take a couple of decades.
Technically the AI is improving, too. Just not as fast as a human would… yet.
A computer is a machine that makes human errors at the speed of electricity.
I think one of the big issues is it often makes nonhuman errors. Sometimes I forget a semicolon or there’s a typo, but I’m well equipped to handle that. In fact, most programs can actually catch that kind of issue already. AI is more likely to generate code that’s hard to follow and therefore harder to check. It makes debugging more difficult.
AI is more likely to generate code that’s hard to follow and therefore harder to check.
Sure. It’s making the errors faster and at a far higher volume than any team of humans could do in twice the time. The technology behind inference is literally an iterative process of turning gibberish into something that resembles human text. So its sort of a speed run from baby babble into college level software design by trial, evaluation, and correction over and over and over again.
But because the baseline comparison code is, itself, full of errors, the estimation you get at the end of the process is going to be scattering errant semicolons (and far more esoteric coding errors) through the body of the program at a frequency equivalent to humans making similar errors over a much longer timeline.
Also seems like it’d be a lot harder to modify or extend later
No shit.
I actually believed somebody when they told me it was great at writing code, and asked it to write me the code for a very simple lua mod. It’s made several errors and ended up wasting my time because I had to rewrite it.
In a postgraduate class, everyone was praising ai, calling it nicknames and even their friend (yes, friend), and one day, the professor and a colleague were discussing some code when I approached, and they started their routine bullying on me for being dumb and not using ai. Then I looked at his code and asked to test his core algorithm that he converted from a fortran code and “enhanced” it. I ran it with some test data and compared to the original code and the result was different! They blindly trusted some ai code that deviated from their theoretical methodology, and are publishing papers with those results!
Even after showing the different result, they didn’t convince themselves of anything and still bully me for not using ai. Seriously, this shit became some sort of cult at this point. People are becoming irrational. If people in other universities are behaving the same and publishing like this, I’m seriously concerned for the future of science and humanity itself. Maybe we should archive everything published up to 2022, to leave as a base for the survivors from our downfall.
The way it was described to me by some academics is that it’s useful…but only as a “research assistant” to bounce ideas off of and bring in arcane or tertiary concepts you might not have considered (after you vet them thoroughly, of course).
The danger, as described by the same academics, is that it can act as a “buddy” who confirms you biases. It can generate truly plausible bullshit to support deeply flawed hypotheses, for example. Their main concern is it “learning” to stroke the egos of the people using it so it creates a feedback loop and it’s own bubbles of bullshit.
So, linkedin? What if the real artificial intelligence was the linkedin lunatics we met along the way?
That’s not a bad idea. I’m already downloading lots of human knowledge and media that I want backed up because I can’t trust humanity anymore to have it available anymore
I’ve been coding for a while. I did an honest eager attempt at making a real functioning thing with all code written by AI. A breakout clone using SDL2 with music.
The game should look good, play good, have cool effects, and be balanced. It should have an attractor screen, scoring, a win state and a lose state.
I also required the code to be maintainable. Meaning I should be able to look at every single line and understand it enough to defend its existence.
I did make it work. And honestly Claude did better than expected. The game ran well and was fun.
But: The process was shit.
I spent 2 days and several hundred dollars to babysit the AI, to get something I could have done in 1 day including learning SDL2.
Everything that turned out well, turned out well because I brought years of skill to the table, and could see when Claude was coding itself into a corner and tell it to break up code in modules, collate globals, remove duplication, pull out abstractions, etc. I had to detect all that and instruct on how to fix it. Until I did it was adding and re-adding bugs because it had made so much shittily structured code it was confusing itself.
TLDR; LLM can write maintainable code if given full constant attention by a skilled coder, at 40% of the coder’s speed.
It depends on the subject area and your workflow. I am not an AI fanboy by any stretch of the imagination, but I have found the chatbot interface to be a better substitute for the “search for how to do X with library/language Y” loop. Even though it’s wrong a lot, it gives me a better starting place faster than reading through years-old SO posts. Being able to talk to your search interface is great.
The agentic stuff is also really good when the subject is something that has been done a million times over. Most web UI areas are so well trodden that JS devs have already invented a thousand frameworks to do it. I’m not a UI dev, so being able to give the agent a prompt like, “make a configuration UI with a sidebar that uses the graphql API specified here” is quite nice.
AI is trash at anything it hasn’t been trained on in my experience though. Do anything niche or domain-specific, and it feels like flipping a coin with a bash script. It just throws shit at the wall and runs tests until the tests pass (or it sneakily changes the tests because the error stacktrace repeatedly indicates the same test line as the problem).
Yeah what you say makes sense to me. Having it make a “wrong start” in something new is useful, as it gives you a lot of the typical structure, introduces the terminology, maybe something sorta moving that you can see working before messing with it, etc.
It’s basically just for if you’re lazy and don’t want to write a bunch of boilerplate or hit your keyboard a bunch of times to move the cursor(s) around
It is great for boilerplate code. It can also explain code for you, or help with an unfamiliar library. It’s even helped me be productive when my brain wasn’t ready to really engage with the code.
But here’s the real danger: because I’ve got AI to do it for me, my brain doesn’t have to engage fully with the code anymore. I don’t really get into the flow where code just flows out of your hands like I used to. It’s becoming a barrier between me and the real magic of coding. And that sucks, because that’s what I love about this work. Instead, I’m becoming the AI’s manager. I never asked for that.
I generally agree with what you’ve said for sure. I think I’ve honestly started to use it for helping me to go pinpoint where to go look for issues in the spaghetti code of new code bases. I’ve also mostly tried to avoid using it in my personal coding time but I feel like it’s gotten harder and harder to get legitimately good search results nowadays which I realize is also because of ai. Given the choice I’d happily just erase it from existence I think. Spending hours sifting through reddit and stack overflow was way more fulfilling + I feel like people used to be slightly less prickly about answering stuff because that was how you had to get answers. It seems like lemmy could replace that space at least, I’ve genuinely gotten helpful comments and I’ve always felt downvotes on here have been productive versus what Reddit is now.
I’ve found the same thing. I’ve turned off the auto suggestions while tying because by the time I’m typing i already know what I’m going I’m to type and having mostly incorrect suggestions popping up every 2 seconds was distracting and counterproductive.
This was a very directed experiment at purely LLM written maintainable code.
Writing experiments and proof of concepts, even without skill, will give a different calculation and can make more sense.
Having it write a “starting point” and then take over, also is a different thing that can make more sense. This requires a coder with skill, you can’t skip that.
It would be really interesting to watch a video of this process. Though I’m certain it would be pretty difficult to pull off the editing.
You want to see someone using say, VS Code to write something using say, Claude Code?
There’s probably a thousand videos of that.
More interesting: I watched someone who was super cheap trying to use multiple AIs to code a project because he kept running out of free credits. Every now and again he’d switch accounts and use up those free credits.
That was an amazing dance, let me tell ya! Glorious!
I asked him which one he’d pay for if he had unlimited money and he said Claude Code. He has the $20/month plan but only uses it in special situations because he’ll run out of credits too fast. $20 really doesn’t get you much with Anthropic 🤷
That inspired me to try out all the code assist AIs and their respective plugins/CLI tools. He’s right: Claude Code was the best by a HUGE margin.
Gemini 3.0 is supposed to be nearly as good but I haven’t tried it yet so I dunno.
Now that I’ve said all that: I am severely disappointed in this article because it doesn’t say which AI models were used. In fact, the study authors don’t even know what AI models were used. So it’s 430 pull requests of random origin, made at some point in 2025.
For all we know, half of those could’ve been made with the Copilot gpt5-mini that everyone gets for free when they install the Copilot extension in VS Code.
It’s more I want to see the process of experienced coders explaining the coding mistakes that typical AI coding makes. I have very little experience and see it as a good learning experience. You’re probably right about there being tons of videos like that.
The mistakes it makes depends on the model and the language. GPT5 models can make horrific mistakes though where it randomly removes huge swaths of code for no reason. Every time it happens I’m like, “what the actual fuck?” Undoing the last change and trying usually fixes it though 🤷
They all make horrific security mistakes quite often. Though, that’s probably because they’re trained on human code that is *also" chock full of security mistakes (former security consultant, so I’m super biased on that front haha).
Oh, gpt def does that’s lol.
Even replaces large bits with just a …
But I don’t use it to rewrite code. I use projects to load everything into it and just ask for pieces that I’ll edit and insert. There’s something about it that works with my adhd in keeping track. It works well for me.
Gemini coughs up more garbage than chatgpt for me by a long shot. For python, anyways.
Which is funny because you should be able to just copy and paste And combine from maybe two maybe three GitHub pages pretty easily and you learn just as much
Water makes things wetter than fire does.
Yeah no shit
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That’s what a bot would say…
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Anyone blindly having AI write their code is an absolute moron.
Anyone with decent experience (5-10 years, maybe 10+?) can absolutely fucking skyrocket their output if they properly set up their environments and treat their agents as junior devs instead of competent programmers. You shouldn’t trust generated code any more than you trust someone fresh out of college, but they produce code in seconds instead of weeks.
I have tripled my output while producing more secure code (based on my security audits), safer code (based on code coverage and security audits), and less error-prone code (based on production logs and our unchanged QA process).
Now, the ethical issues and environmental issues, I 100% can get behind. And I have no idea what companies are going to do in 10 years when they have to replace people like me and haven’t been hiring or training replacements. But the productivity and quality debates are absolutely ridiculous, as long as a strong dev is behind the wheel and has been trained to use the tools.
Consider: the facts
People are very bad at judging their own productivity, and AI consistently makes devs feel like they are working faster, while in fact slowing them down.
I’ve experienced it myself - it feels fucking great to prompt a skeleton and have something brand new up and running in under an hour. The good chemicals come flooding in because I’m doing something new and interesting.
Then I need to take a scalpel to a hundred scattered lines to get CI to pass. Then I need to write tests that actually test functionality. Then I start extending things and realize the implementation is too rigid and I need to change the architecture.
It is as this point that I admit to myself that going in intentionally with a plan and building it myself the slow way would have saved all that pain and probably got the final product shipped sooner, even if the prototype was shipped later.
What about my comment made you believe I was using gut feelings to judge anything? My ticket completion rate, number of tickets, story points, and number of projects completed all point to massive productivity gains.
The end of your comment was
But the productivity and quality debates are absolutely ridiculous
Which is a general statement and not dealing with your specific circumstance. If a tool works for you, by all means keep using it.
However, broadly across software that is not the case. So the “productivity and quality debates” are not ridiculous … the data supports the sceptics.
Which is a general statement and not dealing with your specific circumstance. If a tool works for you, by all means keep using it.
Absolute nonsense. Do people talk shit about hammers because some people keep hitting their hands with them? Do people complain about how useless ladders are, as one of the single most dangerous items in any household?
I don’t think we should be putting these tools in the hands of junior devs - as the studies show, it hinders their productivity and learning. But to generally claim that they are bad tools with no upsides is just as ridiculous as the strawman you set up.
It depends on the task. As an extreme example, I can get AI to create a complete application in a language I don’t know. There’s no way that’s not more productive than me first learning the language to a point where I can make apps in it. Just have to pick something simple enough for the AI.
Of course the opposite extreme also exists. I’ve found that when I demand something impossible, AI will often just try to implement it anyway. It can easily get into an endless cycle where it keeps optimistically declaring that it identified the issue and fixed it with a small change, over and over again. This includes cases where there’s a bug in the underlying OS or similar. You can waste a huge amount of time going down an entirely wrong path if you don’t realize that an idea doesn’t work.
In my real work neither of these really happen. So the actual impact is much less. A lot of my work is not coding in the first place. And I’ve been writing code since I was a little kid, for almost 40 years now. So even the fast scaffolding I can do with AI is not that exciting. I can do that pretty quickly without AI too. When AI coding tools appeared my bosses started asking if I was fast because I was using one. No, I’m fast because some people ask for a new demo every week. Causes the same problems later too.
But I also do think that we all still need to learn how to use AI properly. This applies to all tools, but I think it’s more difficult than with other tools. If I try to use a hammer on something other than a nail, it will not enthusiastically tell me it can do it with just one more small change. AI tools absolutely will though, and it’s easy to just let them try because it’s just a few seconds to see what they come up with. But that’s a trap that leads to those productivity wasting spirals. Especially if the result actually somehow still works at first, so we have to fix it half a year later instead of right away.
At my work there are some other things that I feel limit the productivity potential of AI tools. First of all we’re only allowed to use a very limited number of tools, some of them made in-house. Then we’re not really allowed to integrate them into our workflows other than the part where we write code. E.g. I could trivially write an mcp server that interacts with our (custom in-house) ci system and actually increases my productivity because I could save a small number of seconds very often if I could tell an AI to find builds for me for integration or QA work. But it’s not allowed. We’re all being pushed to use AI but the company makes it really difficult at the same time.
So when I play around with AI on my spare time I do actually feel like I’m getting a huge boost. Not just because I can use a claude model instead of the ones I can use at work, but also just basic things like e.g. being able to turn on AI in Xcode at all when working on software for Apple platforms. On my work Macbook I can’t turn on any Apple AI features at all so even tab completion is worse. Or in other words, those realities of working on serious projects at a serious company with serious security policies can also kill any potential productivity boost from AI. They basically expect us to be productive with only those features the non-developer CEO likes, who also doesn’t have to follow any of our development processes…
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Jeez, you aint joking about that brain injury :( I whish you good luck with your life. I am not trying to be an AH, i truly do whish you the best.
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AI has made being OE insanely easy.
Did they compare it to the code of that outsourced company that provided the lowest bid? My company hasn’t used AI to write code yet. They outcourse/offshore. The code is held together with hopes and dreams. They remove features that exist, only to have to release a hot fix to add it back. I wish I was making that up.
And how do you know if the other company with the cheapest bid actually does not just vibe code it? With all that said it could be plain incompetence and ignorance as well.
Because it has been like this before vibe coding existed…
That’s a valid question, especially with AI coding being so prevalent.
Cool, the best AI has to offer is worse than the worst human code. Definitely worth burning the planet to a crisp for it.
Oh, so my sceptical, uneducated guesses about AI are mostly spot on.
As a computer science experiment, making a program that can beat the Turing test is a monumental step in progress.
However as a productive tool it is useless in practically everything it is implemented on. It is incapable of performing the very basic “Sanity check” that is important in programming.
The Turing test says more about the side administering the test than the side trying to pass it
Just because something can mimic text sufficiently enough to trick someone else doesn’t mean it is capable of anything more than that
We can argue about it’s nuances. same with the Chinese room thought experiment.
However, we can’t deny that it the Turing test, is no longer a thought exercise but a real test that can be passed under parameters most people would consider fair.
I thought a computer passing the Turing test would have more fanfare, about the morality if that problem, because the usual conclusion of that thought experiment was “if you cant tell the difference, is there one?”, but now it has become “Shove it everywhere!!!”.
Oh, I just realized that the whole ai bubble is just the whole “everything is a dildo if you are brave enough.”
yhea, and “everything is a nail if all you got is a hammer”.
there are some uses for that kind of AI, but very limiting. less robotic voice assisants, content moderation, data analysis, quantification of text. the closest thing to Generative use should be to improve auto complete and spell checking (maybe, I’m still not sure on those ones)
I was wondering how they could make autocomplete worse, and now I know.
In theory, I can imagine an LLM fine tuned on whatever you type. which might be slightly better then the current ones.
emphasis on the might.
The Turing Test has shown its weakness.
Time for a Turing 2.0?
If you spend a lifetime with a bot wife and were unable to tell that she was AI, is there a difference?
The Turing test becomes absolutely useless when the product is developed with the goal of beating the Turing test.
it was also meant as a philosophical test, but also, a practical one, because now. I have absolutely no way to know if you are a human or not.
But it did pass it, and it raised the bar. but they are still useless at any generative task
…is this supposed to be news?
Kinda. It’s a novel technology and one that hasn’t been well analyzed or exhaustively tested.
It’s been tested a lot and the results are that it can’t be trusted at all unless you are already an expert in the thing you’re asking it to “help” you with so you can correct the many mistakes it will make, but it’s slower and, again, is **guaranteed **to make mistakes (hallucinations are built into what techbros are insisting on labeling as “AI”, no matter how many resources you throw at it).
All of this at great environmental and human cost too.
I think his point is that this is less “news”, and more “well, duh”.
