Almost as if it was made to simulate human output but without the ability to scrutinize itself.
this post was submitted on 23 Dec 2025
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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
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(Fuck AI though. Planet burning trash)
It's humans burning the planet, not the spicy Linear Algebra.
Blaming AI for burning the planet is like blaming crack for robbing your house.
Blaming AI is in general criticising everything encompassing it, which includes how bad data centers are for the environment. It's like also recognizing that the crack the crackhead smoked before robbing your house is also bad.
How about I blame the humans that use and promote AI. The humans that defend it in arguments using stupid analogies to soften the damage it causes?
Would that make more sense?
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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.
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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.
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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.
It can't even copy and paste a Hello World example properly. If someone says it's working well for them, I'm going to now assume they are too ignorant to understand what's broken.
It works well for recalling something you already know, whether it be computer or human language. What's a word for... what's a command/function that does...
For words, it's pretty good. For code, it often invents a reasonable-sounding function or model name that doesn't exist.
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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.
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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.
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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.
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And even worse, it doesn't realise it and can't fix the errors.
I'd never ask a friggin machine to do coding for me, that's MY blast.
That said, I've had good luck asking GPT specific questions about multiple obscure features of Javascript, and of various browsers. It'll often feed me a sample script using a feature it explains ... a lot more helpful than many of the wordy websites like MDN ... saving me shit-tons of time that I'd spend bouncing around a half-dozen 'help' pages.
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I'm not a programmer, but I've dabbled with Blender for 3D modeling, and it uses Node trees for a lot of different things, which is pretty much a programming GUI. I googled how to make a shader, and the AI gave me instructions. About half of it was complete nonsense, but I did make my shader.
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.
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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.
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I find if I ask it about procedures that have any vague steps AI will stumble on it and sometimes put me into loops where it tells me to do A, A fails, so do B, B fails, so it tells me to do A...
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You need to babysit and double check everything it does. You can’t just let it loose and trust everything it does.
Although I don't doubt the results… can we have a source for all the numbers presented in this article?
It feels AI generated itself, there's just a mishmash of data with no link to where that data comes from.
There has to be a source, since the author mentions:
So although the study does highlight some of AI's flaws [...] new data from CodeRabbit has claimed
CodeRabbit is an AI code reviewing business. I have zero trust in anything they say on this topic.
Then we get to see who the author is:
Craig’s specific interests lie in technology that is designed to better our lives, including AI and ML, productivity aids, and smart fitness. He is also passionate about cars
Has anyone actually bothered clicking the link and reading past the headline?
Can you please not share / upvote / get ragebaited by dogshit content like this?
I'll go ahead and file this under "duh".
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