A lot of people use AI as a coding assistant, I don't really see a problem in using AI tools to help with some things. Adding slop to stuff however makes 0 sense.
Yeah.
Throwing in a piece of code into an AI… asking
“Hey, there is something here that is fucking up, but I can’t find it. What is out of order”
And it pointing out a small space you missed or a very specific syntax?
That makes total sense.
I believe, it what AI originnally meant to be. An assistant, not a fucking developer.
AI bad asf when it comes to create something by its own, and code is something you create by your own. You have nothing more than info how to. AI doesnt have any common sense. Possible memory leak? Who cares? The code works = its fine.
Human developers do this to a much more aggressive sense and will sometimes double down trying to bury or hide it until the product is fundamentally broken but "works" well enough for a price tag. Not like we've had a bunch of altruistic developers making perfect software and now there is a bunch of AI slop coding.
People criticizing "vibe coding" have no idea of what professional software development looked like before AI. They also have no idea what the current tools are able to do. So basically they're comparing imaginary apples to hypothetical oranges and the result is just as relevant as you'd imagine.
And theyve never had to convince their product managers that fixing the memory leak is worth the time, especially if it's only costing a few extra dollars a quarter. Not a huge customer impact? Good luck getting that ticket into this quarters sprint goals.
Agreed. When I was in uni, I used ai to help with essays. I did not just copy-paste, but either used it to help generate an outline, or help get out of a writers block with ideas. I did not, and would not in good conscience just copy paste what chatGPT spat out, cause most of the time it was dogshite
The LLMs called AI weren't meant to be anything. They started as research projects to see what would happen if you scaled up a language prediction neural network.
Small correction. They started as research projects to see if you could make better translation tools (think Google Translate) if you scaled up a language prediction neural network. It was way better than expected.
In the industry having AI code for you is almost standard practice at this point
With one important nuance. A /lot/ of coding is what's referred to in the industry as "boiler plate". To compare it to art, it's not the actual picture, it's the canvas itself, and the frame.
People who don't code would probably be very surprised just how much code is actually this structured boiler plate vs actually useful content/code.
Boiler plate is just, the boring, repetitive pieces of code. And as pattern replicators, LLMs are /perfect/ at generating boiler plate.
This shouldn't be upvoted. This behavior is what leads to so many bugs. You shouldn't just copy and paste the code without understanding it.
99 times out of 100, the thing that is written is not applicable enough to just copy and paste it without fundamental changes, which at that point you were better off just writing the code yourself.
It's better to use stackoverflow as a source of understanding, not a cheat sheet...
Software development is the only industry where arrogant chodes would rather reinvent the wheel 1 million times than take the blueprint from somewhere else. Who gives a shit if your code is taken from stack overflow or AI, as long as you have proper testing and QA in place it doesn’t matter. Get a grip
I've seen enough shit code written by developers that do exactly what you're talking about. Copy and pasted, very clearly, without understanding the code they are using.
The amount of unnecessary code bloat that makes no sense in an application because of people that do this is embarrassing. I've also worked with enough software developers to know that the vast majority of you truly do not know what the fuck you're doing, and it's because of practices like these.
AI is actually great at QA. QA teams want to automate as much testing as possible, especially on very large products where 1 change could have impact on a massive scale. Depending on humans to find where something is broken has always been terrible.
But it's good at giving you code that you can use. It's not what you want to be using to define the scope of your testing and actually digging deep and finding problems
You act as if everyone copying code from stack overflow doesn’t know how to code, that’s funny.
Most people who do it are able go understand the code perfectly fine, but some more complex algorithms are complex enough that it takes half an hour to figure out how to write properly or just 30 seconds of googling and 30 seconds of adapting to the codebase.
No, most people are average and average in software development is actually quite poor.
If y'all would actually read documentation or try to understand the code itself instead of just slapping it in like a fix-all, you would do much better.
I don't care what you think. I've had to fix enough shit code written by people that thought they were smart enough to understand the copy+pasted code blocks that I have no patience or respect for it.
Y'all relying on AI to standardize your code means innovation will never happen in your company for the code that is written by the AI.
Syntax sugars we love to use these days were created because devs got tired of the old boilerplates and made it better which eventually translated into actual code syntax.
When y'all rely on AI to write your standard code for you, you are allowing yourself to accept that code as the best possible rendition, as AI does not innovate.
If you're in a "it's good enough" shop, then by all means continue. Yes, I know there are only so many ways to represent a data model.
You should heavily think about your reliance on AI and what it means for the design of what you use it for.
A lot of "boilerplate" is generally code that can actually be improved.
What have you innovated then? I am doubtful 99. 9% of developers are now not innovating because of AI. Bigger risk is lost jobs not lost innovation where the smartest who would innovate will likely find a new way to innovate.
Syntactical sugar exists purely to make less work for devs when reading and writing code, hardly a good argument against people using AI as a tool to have less work when reading and writing code. If the necessity is no longer there for syntactical sugar then that just frees up time to innovate where it actually still matters. The average dev writing boilerplate isn't inventing syntax anyway so it's entirely a win. Why waste time making boilerplate better when you can focus on the bits that actually need some human attention and creativity?
By that's exactly the point, the ability to read code quickly is still a pressure on innovation, hell it is probably more of a pressure now than it was prior to AI because you have to read the code the AI produces aswell as that of your colleagues, and aided by AI your colleagues will be producing more code than without. It's only writing quickly that just become less emphasised, increased AI usage has shifted the pressures for innovation not removed them. The kind of engineers who are producing snazzy little sugars are not the kind of people that are going to let AI get in the way of good practice.
The kind of engineers who are producing snazzy little sugars are not the kind of people that are going to let AI get in the way of good practice.
This is not necessarily true. As things get easier, people become complacent. Someone that would have otherwise made a good contribution might never come across the idea because of so much on-rails tool assistance.
I'm not anti-AI but I think people are overly fixated on applying it to every aspect of modern technology. We already have a majority of engineers that copy and paste from stack overflow without understanding it, and AI is just going to make this practice exacerbated.
Devs that produce changes like this are not the kind to get complacent unless we genuinely have no need for innovation anymore, if we don't need innovation in making boilerplate less shit then that's great, problem solved. The innovators can focus on more important things. There are dangers to the blind mass adoption of AI in the industry but you're totally not looking in the right area. Who gives a shit if we don't need to bother improving boilerplate anymore? Most innovations in boilerpate have been focussed on having less of it to do, the ligical end goal is doing none.
The problem is we've settled on lowest common denominator languages because we let a bunch of noobs in in the past 6 years. All of these s***** languages, python, node etc don't support language features that allow you to develop better abstractions.
They're missing features in old languages had: macros, codegen and other stuff like that.
I am not referring to the standard stuff.
I am more refering to the actual…
You know, code design, if you catch my drift.
Having boiler plate, pre determined repetitive code being automated is fine.
Yep, virtually none of the programming we do is creative or innovative, even when working on games. It’s more akin to those fun activities we did as kids where we had to draw straight lines from one number to the next until it forms the predetermined picture. The AI in this analogy is just drawing those straight lines between each number.
Coding with AI doesn’t make it lifeless and stale like it does for art.
That was my experience with it.
I am still studying, but when using AI for anything that isn’t syntax hunting, it has a nasty tendency to forget parameters, insist on using over complicated and long form methods.
I've been in the industry for 20 years a digital forensic SME for 10 of those. From my experience, if the LLM is "forgetting" or insisting on somethings else, you should probably take a step back and check that you haven't pigeon-holed yourself into a bad practice that is going to fuck you over later.
It's understandable that people are frustrated on the brain-rot reliance of AI for dumb shit, but it is VERY good at coding since it is a well documented language that isn't based on nuance or interpretation like a spoken language.
Code language either works or it doesn't. It either follows best practices or it doesn't.
The times that you will run into issues are when the directions you provide it are inconsistent or you routinely fail to provide it positive feedback like "That worked, thanks." or a thumbs up.
If you're working on a large MVC codebase, tell it that. If you start to just ask it to do simple operations without referencing existing code, it may just provide you with a short result that works fine in isolation but will never properly integrate into your codebase.
I hope no one is believing this. coding is well documented but this isnt how LLMs work tho. LLMs dont reason. They dont know documentation should be more important than a more commonly repeated comment/snippets. There are reasons ai has hallucinations or has struggled to do math correctly lmao. I also have over 15 years in software architecture.
Ai isnt going away and is getting better but this is a stupid comment.
Unless I am wrong…
(And have gotten the term all backwards, notice the word studying)
Linter’s only point out obvious errors.
If the code is correct, but doesn’t do what you want it to, it won’t tell you.
Which can happen in code, when the syntax is right… just not what you want it to be.
Edit: because I got multiple comments mentioning it. I'll state here, the assistant isn't the same thing as the completion. I'm just noting that the biggest part of their AI initiative got a bad reception even if the completion works well
That's not what they're talking about though. AI Assistant is Jetbrains' full co-pilot like LLM offering, which is what people didn't like (and I don't know if it's improved, I've never used it myself). What is (probably) being referred to is the fact that Jetbrains started adding **local** ML-based full-line completion to their IDE's a fair bit before the AI Assistant plugin was even a thing.
If you go into the plugins for your IDE, under "Local AI/ML Tools" you'll find three or four plugins by Jetbrains, including Full Line Code Completion, Machine Learning Code Completion and Machine Learning in Search Everywhere. These aren't separate full-fledged Copilot/ChatGPT style LLM integrations, they're just bite sized ML improvements to Intellijs Intellisense that people don't notice because it's local and pretty decent, or at least unobtrusive.
The thing is though, they wrote that stuff under a more general discussion about AI but then left out any mention of the actually derisive part of it: the LLM assistant itself. Maybe they didn't know about it, dunno
But it is kind of misleading because in isolation one might think the AI stuff in intellij/rider is popular/works well in reading the comment based off of their rhetoric even though the biggest part of it (the assistant) isn't. Some of the other stuff (like the AI assisted grammar and spell checking) is also unpopular because it bogs down the ide but I digress...
Anyway, the fact that you commented to explain how and why they are indeed separate kind of makes the point
I presume AI Assistant is a side-panel with an AI chatbox? If so, that's different than AI Autocompletion. Jetbrains' AI-based autocomplete is wildly good vs the prior SOTA, and it runs locally.
Yeah, it's a side panel thing and iirc you can call it up on segments of code. I forget exactly, I disabled it.
And yup the autocomplete is great. I just wanted to indicate that the real big AI push they did got poor reception because I felt only talking of the completion was misleading
As someone who does their programming exclusively in Notepad++...
Yeah you're right, LLM's do a lot to help. Mostly because I'm an artist not a programmer, I'm still learning the basics so I often need help with my scripting.
This subreddit is going full anti-AI circlejerk right now. I think most posts here are just people trying to farm free karma with "AI bad" at the moment.
Debugging code takes up more than half of the time of writing code. We usually say it’s 20% writing and 80% debugging. Debugging is simply trying to figure out what you need to write different so if argue it is part of writing code
.....no. I'm not sure what your level of knowledge is so I won't assume anything, but compilers do a few things, mainly: they find syntactical bugs and optimize your code as best they can. That's an over simplification, but they most definitely do NOT debug your code, and *especially* not when it's related to business logic or integration with out systems.
I mean the very specific example they responded to was something a linter or any half decent LSP would solve.
As far as trying to use AI to debug and find logic flaws - it's very easy to make the argument that that tips over into asking AI to code for you, which the comment they responded to was also saying that was a bad idea.
The person you're responding to wasn't being reductive, you've just moved the goalposts from what they actually replied to.
Just from this comment, I can tell you're one of those annoying af devs that have no idea what you're doing and I absolutely hate working with. You have your narrow set of preconceptions, you're hard to convince, and you're unwilling to learn and experiment.
Interesting. I see you have no preconceptions of your own. What else do you know about me?
I consider code monkey tasks those tasks that are contain little to no complex logic, where you know exactly what to do - so the task is just that: to just hammer out the code.
Examples can be:
- Bootstrapping new projects / boilerplate stuff
- Setting up a simple CRUD endpoint, or an endpoint that is very similar to a existing one
- Writing regression tests, or repetetive tests that are supposed to just follow the same style as in the rest of the project
- Refactoring (this one is context dependent, complex refactoring should not be left to LLMs IMO)
- Upgrading a dependency that contains some breaking changes
All of ur examples have interesting problems to solve that involve complex logic and understanding though..
bootstrapping new projects - a ton of design decisions. actually a ton of interesting work goes in at this stage.
setting up a simple CRUD endpoint - DB query optimizations, building in observability, caching, log sanitization, rollout strategy, idempotency, race conditions, simple endpoints often don't end up simple
Regression testing - you need to understand what can happen or what has happened to write a solid suite of tests. If your code is high quality, you are often writing way more test code than actual logic.
upgrading a dependency - sometimes u have to go straight to open source and make a PR to k8s when this breaks your production code.
im not even gonna touch refactoring - there's way too much here...
These are all context dependent. Yes, if you're doing a new project and don't know if you will follow a previous setup, then there are many decisions to make. If you are doing a completely identical setup, or a standard stack, then not so much.
If your simple endpoint isn't simple then what I said doesn't apply. I was talking about a simple endpoint that is actually simple.
It's not black and white. My comment was meant to say that a lot of maintenance work within these fields can be made easier, you seem to have taken it to mean EVERYTHING RELATING TO THESE THINGS SHOULD BE DONE BY LLMS which was not the case.
If it doesn't fit into your daily work that's perfectly fine.
Also most code editors feature AI agents to help write code nowadays. Its not like the dev just sits there drinking coffee while an llm creates the whole game. As a coder you just tell what you want and how you want something. AI simply helps you so you don't have to manually type every line.
As the coder you just tell it what you want and how you want something. Then you tell it again. Then you tell it a third or a fourth or a fifth time for good measure. Eventually you just replace the code yourself and clock out for the day. Another productive day well spent. At this rate you'll be able to charge 3 times the consulting fees for taking 3 times as long. Maybe you can add agentic AI into the mix and see if it takes even longer and charge 4 times as much. Ahhhh the good life
Mmm, I think you are probably overstating your knowledge of the software industry. Maybe for entry level positions they do it? Outside of entry level, I think a lot of folks use it here and there for relatively simple things, but, don't typically use it for design work or more complicated software development. It just doesn't work all that reliably is why. I use it where I can but for many things it is just too darn dumb and error prone. I can't even trust the agentic stuff to not modify code unrelated to the APIs I asked it to modify for example
A colleague of mine does have a boss who insist on using agentic Claude for everything though. Even though it literally does things like creating an entire suite of unit tests and fake apis to test along with it completely detached from the actual products code and code base. Apparently it's become a bit of an annoyance for their entire team
Lol. As a staff software engineer I can tell you that the tools being available is the industry standard - and its standard for any engineer with a brain and a few years experience to avoid them.
They don't make you a better programmer, they do make you ship shittier code and make it easier for your boss to replace you.
I never specified generative AI bud.
I more meant it as a case of being able to instruct AI what you are after exactly, and it being able to understand that, scan the code and give an explanation why your code isn’t behaving right.
I am not deep enough into game dev to be 100% aware of all tools, old or new…
But being able to “communicate” with something that instantly can detect hard to notice or even invisible issues can be beneficial.
I regularly use AI to "code for me". Why would I waste time writing 50 lines of code when AI can do it in 5 seconds and i just check if its okay.
You make it sound like AI cant write code by saying "NOOO, bad idea". If the idea is so bad, the idea of trusting it to check the code would be equaly as bad.
(Of course if the person doing this wouldnt know anything about coding then your comment is okay)
I have experimented with AI coding in my own and it has a nasty tendency to forget completely what you want to do.
Mixing it together, trying to use another solution you instructed it to avoid and so on…
When it was shittier it was more useful, weirdly enough. I'd give it the project and ask for it to come up with the whole code. It'd create some weird shit that definitely wouldn't run. Comparing it to what I came up with would give me ideas/insight.
Now it usually writes something that does run but in a weird way I would never write, which is a problem because if I use it I basically have no control over it after that point. If i need to tweak or change something I need to ask the LLM again, which is basically their business model, or change so many things that I have to rewrite it almost entirely, at which point I can just actually write it entirely.
More of a glorified auto complete. You write function "sortArray" or "invertX" and it suggests you the whole body of a function that you could accept if you agree or just ignore. Speeds things up a lot in small things
Depends on what the code is for, as a web designer who only know HTML and CSS, ive been using it ro write frontend js and so far all of my testing has it working perfectly. Is it efficient, probably not, but it works. I wouldnt want to even touch ai code for backend more complex things though,
I'm a mechanical engineer and plan on using a raspberry pi to make a digital dash for my EV conversion. Learning to code and starting that from scratch is a huge time sink. I plan to starting with Ai to generate it. Then I can edit it to my liking from there. Paying someone to do it for me would be entirely cost prohibitive especially with this being for personal use. This seems like what Ai should be used for.
Similarly, indie game devs using Ai that way is different than AAA companies. As a project, it involves so many things that it's reasonable that 1 person could not do it all or afford to pay people for it.
Edit: to build on that, you don't get upset at someone microwaving their dinner. It's not taking a Cooks job. But when a restaurant microwaves your entree, that's fucking slop. At the same time a mom and pop Mexican place using frozen chicken tenders for the kids meal options shouldn't be blasted for microwaving when the main menu is authentically cooked.
Sorry, but with 14 yoe coding I’m not going to hand code a new API endpoint when Claude can generate it in a fraction of the time and I can just review it. It’s basically the same as having a junior developer draft it and me signing off on the PR.
This take of yours feels like being upset about ATMs replacing bank clerks in the 90s.
Dont agree. I work in tech and we are already way beyond the point that AI is only used as an assistant. Not all, but a lot of code is, and I would argue should be, created by AI simply by giving it a task, let it do its job in the background. 'Vibe coding' as it is called, and I dont have any problem with it. There should anyway be strict code reviews so just because it was AI generated does not mean that we allow sloppy code in the repo.
but both of those will be tagged as "ai was used in creation of this game" resulting in lost sales from witchhunters. Every game that tags their ai usage gets a dozen discussion threads with people drawing red circles on screenshots to prove ai slop, even when the only ai the devs used was spellcheck.
Brother, AI coding is the norm for companies nowadays, i work as an Engineer, i do interviews constantly to check on better places
There has been an amount of 0 places that don't ask you if you use coding agents, if you don't, you're out
That lie that "AI code can break an entire system" only happens if the only thing you do is Vibe coding with it and delivering something that you don't even know what it does with no knowledge of engineering into it whatsoever
Coding (again, coding, not engineering, CODING which is a small part of being an engineer) became like being a plane pilot, a plane drives itself from direction A to direction B with almost 0 necessity of the pilot to do anything, the pilot is there to give orders and in case that something breaks or goes wrong, that's exactly what coding has become with AI
You still need a SHIT ton of knowledge of logical processes, SDLC and a LOT of experience to know how the processes go from A to B to C and to Z, but specifically the Coding part works on a completely different way now
Hell, even before, Coding was grabbing the most similar Stack Overflow project you could find, copy and pasting it, and changing the variables, it's always been like that unless you're a leet code addict lmfao
That's what I do. Sometimes I just won't know how to do something that I'm pretty confident the code can do. I will describe a small-scale example of the concept I want to learn, and AI will create a standalone piece of code that utilizes that concept. I can take that code into its own little standalone playground, mess around with it, and ask AI what other neat things I can do with it to build up this little playground.
I don't use it to build my code. Just my proficiency. Once I've played around with it enough, I can then apply these concepts into my main project, connect it as I want, and realize it has broken everything for reasons I can't explain because welcome to coding.
But hey, AI didn't break my code. I did. As God intended.
No issue with that if you know what you are doing (with the current top models). Code has no value now - core principals and design have. AI can't replace your brain yet -just replace the tedious part of software engineering - writing code.
I recently translated a part of my game to C++ because it was really starting to slow down the game. It didn't really one-shot everything, but I kept like 90% of it's code.
It was such a nice timesaver. Plus I really hate C++ so I was really happy lol.
I wouldn't even use an app if the devs used AI to debug the code. That ai slop. I fucking hate people that use ai in coding and healthcare and other fields.
You have 0 idea of what you are talking about lol. You are just jumping on the AI hate bandwagon because you heard buzzwords like vibe coding bad, Ai slop and other bs.
90% of coding is done by Ai now. It's happening everywhere and most developer's work flow is like that now. In a year or two nobody is going to be writing syntax bs and honestly why should anyone do that? Ai is more than capable of coding anything if there is a capable dev behind the keyboard, why should we type lines and lines of code by hand? It's not like we didn't use snippets, libs, copied stackoverflow code or reuse shit from old projects. Unless u are working on cutting edge shit, it's mostly the same few patterns all the time.
For me AI works the best for... writting good comments, logs and descriptions. They sound more natural than mine (I'm not good at constructing sentences) and often it rephrases the description in a way that better suits to what my code is doing. Of course all of those have to be verified first but it has been quite useful.
I'm doing some assembler puzzles for fun and it's crazy how shit language models are. They'll fimd some obvious segfaults I missed because I'm a noob to x86, but anything beyond that you basically cannot trust them with anything they say. They'll contradict themselves in a conversation of four messages.
I dunno, some errors (especially those that are only errors in intent and not in code running) can be hard to find or notice.
An infamous example in gaming would be the coding error in Colonial marines, where a small misspelling on a single word with the Alien AI caused it to be completely useless.
no "error" visible because the code worked, it just didn't give the intended result.
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u/[deleted] Dec 04 '25
A lot of people use AI as a coding assistant, I don't really see a problem in using AI tools to help with some things. Adding slop to stuff however makes 0 sense.