I work for an adtech company and im pretty much the only developer for the javascript library that runs on client sites and shows our ads. I dont use AI at all because it keeps generating crap
this post was submitted on 11 Jul 2025
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Explain this too me AI. Reads back exactly what's on the screen including comments somehow with more words but less information Ok....
Ok, this is tricky. AI, can you do this refactoring so I don't have to keep track of everything. No... Thats all wrong... Yeah I know it's complicated, that's why I wanted it refactored. No you can't do that... fuck now I can either toss all your changes and do it myself or spend the next 3 hours rewriting it.
Yeah I struggle to find how anyone finds this garbage useful.
If you give it the right task, it’s super helpful. But you can’t ask it to write anything with any real complexity.
Where it thrives is being given pseudo code for something simple and asking for the specific language code for it. Or translate between two languages.
That’s… about it. And even that it fucks up.
I bet it slows down the idiot software developers more than anything.
Everything can be broken into smaller easily defined chunks and for that AI is amazing.
Give me a function in Python that if I provide it a string of XYZ it will provide me an array of ABC.
The trick is knowing how it fits in your larger codebase. That's where your developer skill is. It's no different now than it was when coding was offshored to India. We replaced Ravinder with ChatGPT.
Edit - what I hate about AI is the blatant lying. I asked it for some ServiceNow code Friday and it told me to use the sys_audit_report table which doesn't exist. I told it so and then it gave me the sys_audit table.
The future will be those who are smart enough to know when AI is lying and know how to fix it when it is. Ideally you are using AI for code you can do, you just don't want to. At least that's my experience. In that, it's invaluable.
You shouldn't think of "AI" as intelligent and ask it to do something tricky. The boring stuff that's mostly just typing, that's what you get the LLMs to do. "Make a DTO for this table " "Interface for this JSON "
I just have a bunch of conversations going where I can paste stuff into and it will generate basic code. Then it's just connecting things up, but that's the fun part anyway.
Most ides do the boring stuff with templates and code generation for like a decade so that's not so helpful to me either but if it works for you.
I have asked questions, had conversations for company and generated images for role playing with AI.
I've been happy with it, so far.
That's kind of outside the software development discussion but glad you're enjoying it.
As a developer
- I can jot down a bunch of notes and have ai turn it into a reasonable presentation or documentation or proposal
- zoom has an ai agent which is pretty good about summarizing a meeting. It usually just needs minor corrections and you can send it out much faster than taking notes
- for coding I mostly use ai like autocomplete. Sometimes it’s able to autocomplete entire code blocks
- for something new I might have ai generate a class or something, and use it as a first draft where I then make it work
I’ve had success with:
- dumping email threads into it to generate user stories,
- generating requirements documentation templates so that everyone has to fill out the exact details needed to make the project a success
- generating quick one-off scripts
- suggesting a consistent way to refactor a block of code (I’m not crazy enough to let it actually do all the refactoring)
- summarize the work done for a slide deck and generate appropriate infographics
Essentially, all the stuff that I’d need to review anyway, but use of AI means that actually generating the content can be done in a consistent manner that I don’t have to think about. I don’t let it create anything, just transform things in blocks that I can quickly review for correctness and appropriateness. Kind of like getting a junior programmer to do something for me.
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Experienced software developer, here. "AI" is useful to me in some contexts. Specifically when I want to scaffold out a completely new application (so I'm not worried about clobbering existing code) and I don't want to do it by hand, it saves me time.
And... that's about it. It sucks at code review, and will break shit in your repo if you let it.
Same. I also like it for basic research and helping with syntax for obscure SQL queries, but coding hasn't worked very well. One of my less technical coworkers tried to vibe code something and it didn't work well. Maybe it would do okay on something routine, but generally speaking it would probably be better to use a library for that anyway.
Important thing they left out here being a broad news source reporting tech stuff is that this was specifically bug fixing tasks. If you’re familiar with using it for coding you’ll know it’s horrendous at that sort of thing. It can typically only provide the broadest of advice and it’s largely incapable of tackling things holistically.
Not a developer per se (mostly virtualization, architecture, and hardware) but AI can get me to 80-90% of a script in no time. The last 10% takes a while but that was going to take a while regardless. So the time savings on that first 90% is awesome. Although it does send me down a really bad path at times. Being experienced enough to know that is very helpful in that I just start over.
In my opinion AI shouldn’t replace coders but it can definitely enhance them if used properly. It’s a tool like everything. I can put a screw in with a hammer but I probably shouldn’t.
Like I said, I do find it useful at times. But not only shouldn't it replace coders, it fundamentally can't. At least, not without a fundamental rearchitecturing of how they work.
The reason it goes down a "really bad path" is that it's basically glorified autocomplete. It doesn't know anything.
On top of that, spoken and written language are very imprecise, and there's no way for an LLM to derive what you really wanted from context clues such as your tone of voice.
Take the phrase "fruit flies like a banana." Am I saying that a piece of fruit might fly in a manner akin to how another piece of fruit, a banana, flies if thrown? Or am I saying that the insect called the fruit fly might like to consume a banana?
It's a humorous line, but my point is serious: We unintentionally speak in ambiguous ways like that all the time. And while we've got brains that can interpret unspoken signals to parse intended meaning from a word or phrase, LLMs don't.
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I have limited AI experience, but so far that's what it means to me as well: helpful in very limited circumstances.
Mostly, I find it useful for "speaking new languages" - if I try to use AI to "help" with the stuff I have been doing daily for the past 20 years? Yeah, it's just slowing me down.
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Everyone on Lemmy is a software developer.
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no shit. ai will hallucinate shit I’ll hit tab by accident and spend time undoing that or it’ll hijack tab on new lines inconsistently
Fun how the article concludes that AI tools are still good anyway, actually.
This AI hype is a sickness
Upper management said a while back we need to use copilot. So far just used Deepseek to fill out the stupid forms that management keep getting us to fill out
"Using something that you're not experienced with and haven't yet worked out how to best integrate into your workflow slows some people down"
Wow, what an insight! More at 8!
As I said on this article when it was posted to another instance:
AI is a tool to use. Like with all tools, there are right ways and wrong ways and inefficient ways and all other ways to use them. You can’t say that they slow people down as a whole just because some people get slowed down.
I use github copilot as it does speed things up. but you have to keep tight reins on it, but it does work because it sees my code, sees what i'm trying to do, etc. So a good chunk of the time it helps.
Now something like Claude AI? yeah...no. Claude doesn't know how to say "I don't know." it simply doesn't. it NEEDS to provide you a solution even if the vast majority of time it's one it just creates off the top of it's head. it simply cannot say it doesn't know. and it'll get desperate. it'll provided you with libraries or repos that have been orphaned for years. It'll make stuff up saying that something can magically do what you're really looking for when in truth it can't do that thing at all and was never intended to. As long as it sounds good to Claude, then it must be true. It's a shit AI and absolutely worthless. I don't even trust it to simply build out a framework for something.
Chatgpt? it's good for providing me with place holder content or bouncing ideas off of. that's it. like you said they're simply tools not anything that should be replacements for...well...anything.
Could they slow people down? I think so but that person has to be an absolute moron or have absolutely zero experience with whatever their trying to get the AI to do.
Writing code is the easiest part of my job. Why are you taking that away?
For some of us that’s more useful. I’m currently playing a DevSecOps role and one of the defining characteristics is I need to know all the tools. On Friday, I was writing some Java modules, then some groovy glue, then spent the after writing a Python utility. While im reasonably good about jumping among languages and tools, those context switches are expensive. I definitely want ai help with that.
That being said, ai is just a step up from search or autocomplete, it’s not magical. I’ve had the most luck with it generating unit tests since they tend to be simple and repetitive (also a major place for the juniors to screw up: ai doesn’t know whether the slop it’s pumping out is useful. You do need to guide it and understand it, and you really need to cull the dreck)
I study AI, and have developed plenty of software. LLMs are great for using unfamiliar libraries (with the docs open to validate), getting outlines of projects, and bouncing ideas for strategies. They aren't detail oriented enough to write full applications or complicated scripts. In general, I like to think of an LLM as a junior developer to my senior developer. I will give it small, atomized tasks, and I'll give its output a once over to check it with an eye to the details of implementation. It's nice to get the boilerplate out of the way quickly.
Don't get me wrong, LLMs are a huge advancement and unbelievably awesome for what they are. I think that they are one of the most important AI breakthroughs in the past five to ten years. But the AI hype train is misusing them, not understanding their capabilities and limitations, and casting their own wishes and desires onto a pile of linear algebra. Too often a tool (which is one of many) is being conflated with the one and only solution--a silver bullet--and it's not.
This leads to my biggest fear for the AI field of Computer Science: reality won't live up to the hype. When this inevitably happens, companies, CEOs, and normal people will sour on the entire field (which is already happening to some extent among workers). Even good uses of LLMs and other AI/ML use cases will be stopped and real academic research drying up.
My fear for the software industry is that we'll end up replacing junior devs with AI assistance, and then in a decade or two, we'll see a lack of mid-level and senior devs, because they never had a chance to enter the industry.
That's happening right now. I have a few friends who are looking for entry-level jobs and they find none.
It really sucks.
That said, the future lack of developers is a corporate problem, not a problem for developers. For us it just means that we'll earn a lot more in a few years.
Only if you are able to get that experience though.
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Code reviews take up a lot of time, and if I know a lot of code in a review is AI generated I feel like I'm obliged to go through it with greater rigour, making it take up more time. LLM code is unaware of fundamental things such as quirks due to tech debt and existing conventions. It's not great.
Code reviews seem like a good opportunity for an LLM. It seems like they would be good at it. I’ve actually spent the last half hour googling for tools.
I’ve spent literally a month in reviews for this junior guy on one stupid feature, and so much of it has been so basic. It’s a combination of him committing ai slop without understanding or vetting it, and being too junior to consider maintainability or usability. It would have saved so much of my time if ai could have done some of those review cycles without me
This has been solved for over a decade. Include a linter and static analysis stage in the build pipeline. No code review until the checkbox goes green (or the developer has a specific argument for why a particular finding is a false positive)
Not really.
Linter in the build pipeline is generally not useful because most people won’t give results time or priority. You usually can’t fail the build for lint issues so all it does is fill logs. I usually configure a linter and prettifier in a precommit hook, to shift that left. People are more willing to fix their code in small pieces as they try to commit.
But this is also why SonarQube is a key tool. The scanners are lint-like, and you can even import some lint output. But the important part is it tries to prioritize them, score them, and enforce a quality gate based on them. I usually can’t fail a build for lint errors but SonarQube can if there are too many or too priority, or if they are security related.
But this is not the same as a code review. If an ai can use the code base as context, it should be able to add checks for consistency and maintainability similar to the rest of the code. For example I had a junior developer blindly follow the AI to use a different mocking framework than the rest of the code, for no reason other than it may have been more common in the training data. A code review ai should be able to notice that. Maybe this is too advanced for current ai, but the same guy blindly followed ai to add classes that already existed. They were just different enough that SonarQube didn’t flag is as duplicate code but ai ought to be able to summarize functionality and realize they were the same. Or I wonder if ai could do code organization? Junior guys spew classes and methods everywhere without any effort in organizing like with like, so someone can maintain it all. Or how about style? I hope yo never revisit style wars but when you’re modifying code you really need to follow style and naming of what’s already there. Maybe ai code review can pick up on that
Yeah, I’ve added AI to my review process. Sure, things take a bit longer, but the end result has been reviewed by me AND compared against a large body of code in the training data.
It regularly catches stuff I miss or ignore on a first review based on ignoring context that shouldn’t matter (eg, how reliable the person is who wrote the code).
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