Submitted 1 year ago by Dot@feddit.org to technology@lemmy.world
https://slopwatch.com/posts/bad-programmer/
I asked ChatGPT to give me a script to parse my history file and output the dates in something human readable. Later I learned you can use something like history -i. It was basically instantaneous while the script was slow.
Though, I’m questioning my memory of this because I don’t see that flag on man pages online.
I’ve been writing code professionally for nearly two decades, and I love having copilot available in my IDE. When there is some boilerplate or a SQL query I just don’t want to write, it’ll oftentimes get me started with something reasonable that is wrong in a couple of subtle ways. I then fix it, laugh at how wrong it was, or use part of the proposed answer in my project.
If you’re a non-corder, sure it is pure danger, but if you know what you’re doing it can give you a little boost. Only time will tell if it makes me rusty on some basics, but it is another tool in the toolbox now.
Same here (15 years). I work in all sorts of frameworks and languages. I normally would have just googled a given question to see the code i need, paste it in with everything that’s wrong, and fix it to my liking. I know what I’m doing I was just missing the specific words i havent used in a couple years, i still understand them. Copilot just avoid me opening google, clicking through some bad SEO, passing the bad answers, and doing that a couple more times to bring in everything I need. It’s a google formatter.
I also exactly like searching google. If you ask “is this cancer” you’ll find cases where it’s cancer, if you ask “is this not cancer” youll find cases where it’s cancer. You can’t trust it in that way, but you can still quickly parse the internet
For me personally, there is only two applications of LLMs in programming:
Essentially, one-off things that you know how to check for correctness.
I don’t have an encyclopedic knowledge of every random library or built-in function of every language on earth so what’s the difference between googling for an example on stack overflow or asking an LLM?
If you are asking ChatGPT for every single piece of code it will be terrible because it just hallucinates libraries or misunderstands the prompt. But saying any kind of use makes you a bad programmer seems more like fud than actual concern
I can be a bad programmer without using AI generated code. 😤
Not using AI Generated Code won’t make you programmer at all. It’s just another way to start a journey to alcoholism and loneliness in front of computer screen. The only difference is that this time you travel with junior developer for poor people.
I don’t love AI, but programming is engineering. The goal is to solve a problem, not to be the best at solving a problem.
Also I can write shitty code without help anyway
The issue with engineering is that if you don’t solve it efficiently and correctly enough, it’ll blow up later.
That’s a problem for HR if they have shitty retention.
What’s really ugly is it makes really good code with fucking terrible bugs. My last job for all of six weeks was trying to fix and integrations wrapper of an integrations wrapper on a 3rd party library of integrations.
It looked like really good code, but the architecture was fucked beyond repair. I was supposed to support it for a fortune 50. I quit before they could put me in the on call rotation.
Preface: If all you want is to get a simple script/program going that will more or less work for your purposes, then I understand using AI to make it. But doing much more than this with it will not help you.
If you want to actually learn to code, then using AI to write code for you is a crutch. It’s like trying to learn how to write an essay by having ChatGPT write the essays for you. If you want to use an API in your code, then you’re setting yourself up for greater failure the more you depend on AI.
Case in point: if you want to make a module or script for Foundry VTT, then they explicitly tell you not to use AI, partly because the models available online have outdated information. In fact, training AI on their documentation is explicitly against the terms of service.
Even if you do this and avoid losing your license, you run a significant risk of getting unusable code because the AI hallucinated a function or method that doesn’t actually exist. You will likely wind up spending more time scouting the documents for what you actually want to do than if you’d just done it yourself to begin with.
And if the code works perfectly now, there’s no guarantee that it will work forever, or even in the medium term. The software and API receive updates regularly. If you don’t know how to read the docs and write the code you need, you’re screwed when something inevitably gets deprecated and removed. The more you depend on AI to write it for you, the less capable you’ll be of debugging it down the line.
This begs the question: why would you do any of this if you wanted to make something using an API?
AI and the discussion around it doesn’t live in a vacuum.
Occasionally you’ll get shit opinions like this. Easy slutty greek frat bro strawmen that’ll sleep with anything that moves and then dodge child support payments.
We all have to remember the true Chad argument against AI is that it’s built on degenerate theft and corporate soulless shills. AI is the Shikrelli of creativity.
Chad argument against AI
Generative AI*
Good. There’s a lot of non-programmers who are now shitty ones and are using AI to make their ideas real. It’s made programming way more accessible to people who would never learn before.
I got back into programming because I can ask an Ai my stupid questions I’m too dumb to google correctly. I haven’t otherwise wrote code since college and kinda revived a long dead hobby. It removes a barrier to entry that I otherwise gave up on. Been working on a project to teach myself python the last few months, with Ai replacing the roll of google for the most part.
Copy-pasting Ai code still blows up in your face just as much as code you stole from stack overflow…
The issue isn’t you doing your hobby projects however you want, it’s people being paid and produce LLM generated code.
And the biggest issue is managers/c-suites thinking that LLMs can replace senior devs.
And the biggest biggest issue is that the LLMs in their current mainstream form are terribly bad for the environment.
I wouldn’t say you’re dumb when it comes to Google. Their search is just a broken mess of dog shit now.
No…stack I can usually figure out from the context of questions what went wrong. AI will very confidently and eloquently give you a very subtle bullshit answer.
Can confirm. Using AI for coding for a couple of months now. There sure is a lot of copy and paste, trail and error, but without the assistance I would not have been able to enhance and customize code like that. Now I am some steps further and was even able to question the AI output, correct it, made it better. I am getting there: learning, optimizing, creating new stuff. It is fun. And when I compile the code, it runs. If not, I debug. Unthinkable for me a year ago.
If you treat an AI like anything other than the rubber duck in Rubber Duck Programming you’re using it wrong.
I use it to generate repetitive patterns that’s easy to guess what’s next, but PITA to write, eg. asserts in Unit tests
I’ll confess I only skimmed the article, but I don’t buy it and it seems like just a bunch of unsubstantiated opinions.
Using AI generated code is like pair programming with a junior programmer. You tell the junior what to do and then you correct their mistakes by telling them how to do better. In my experience, explaining things to someone else makes you better at your craft. Typically this cycle includes me changing the code at the end, and then possibly feeding it back to ChatGPT for another cycle of changes.
Apart from letting me realize and test my ideas quicker, this allows me to raise the abstraction level of my thinking. I can spend more time on architecture, and less time on the nitty gritty details. I would say it makes me both a faster and a better programmer.
I’ve seen the comparison to pair programming with a junior programmer before, and it’s wild to me that such a comparison would be a point in favor of using AI for improving productivity.
I have never experienced a productivity boost by pairing with a junior. Which isn’t to say it’s not worth doing, but the productivity gains go entirely to the junior. The benefits I receive are mainly improving my communication and mentoring skills in the short term, and improving the team’s productivity in the long term by boosting the junior’s knowledge.
And it’s not like the AI works on the mundane stuff in parallel while I work on the more interesting, higher level stuff. I have to hold its hand through the process.
I feel like the efficiency gains of AI programming is almost entirely in improving your speed at wrestling a chatbot into producing something useful. Which may not be entirely useless going forward - knowing how to search well is an important skill, this may become something similar, but it just doesn’t seem worth the hassle to me.
I have done pair programming with a junior partner, and I found it extremely beneficial. Taking the time to talk out my ideas and logic invariably helped make them clearer in my mind and realize pitfalls much sooner than I otherwise would have.
I had to explain things clearly and logically, and he was bright enough to ask good questions and point out typos as I was coding.
Bugs never occur in the high-level/big picture land, it usually come up in the low-level/implementation land. Should you entrust these to AI ?
Only because bugs are defined as errors in implementation details. You can still have errors in your design (sometimes referred to as design bugs).
And it’s not about “entrusting” to AI any more than I would be entrusting important code to a junior developer to just go off and commit on his own. We still have code review, pair programming etc. As I said, I read the output, point out issues with it, and in the end make manual adjustments to fit what I want. It’s just a way of building up the bulk of the code more quickly and then you refine it.
I've never had AI create working code anyway.
But it will generally point me in the right direction. It's useful for:
You need to be skilled to spot the mistakes it will definitely make.
The same logic can explain why Teslas crash so often.
I haven’t seen any statistics suggesting Teslas crash more often than other vehicles.
You mean I can go from being a terrible programmer to merely a bad one?
Unironically, yes. It’ll generally generate working code, but not necessarily the most correct or efficient. And it may not do exactly what you want.
Not a coder. I can understand most python code and powershell scripts that others have done, but I don’t remember syntax, if I need to make something from scratch. Doing that involves ton of googling and reading awful documentation that still leaves some things out. I do this maybe twice a year.
For someone like me AI coding is a god sent.
doing that involves a ton of googling and reading awful documentation
Yes. That is programming.
To most of us, the syntax is the easy part to remember, and our IDEs take care of most of it. Being able to bang our heads through the documentation and experiment with libraries is pretty much what our jobs are.
AI coding is basically a shortcut to some of the stuff we have to repeat with slight changes in our software. It’s also useful for setting up more complex code that we know we’ll have to tweak.
Expecting it to produce something with the desired results is a recipe for disaster. It’s basically a cheaper outsourcing method that can’t actually compile and run it’s code before giving it to you.
If you’re someone who has no actual interest in learning to code, and instead see AI as more of a freelancer—telling it stuff like “make a kart racer game,” and “that sucks, make it better”—then none of this really applies to you.
Agree on the application side, but when it comes to the test suite, I’m definitely gonna consider letting an AI get that file started and then I’ll run through, make sure the assertions are all what I would expect and refactor anything that needs it.
I’ve written countless tests in my career and I’m still gonna write countless more, but I’m glad I can at least spend less time on laborious repetition now and more time on the part of the job I actually enjoy which is actually solving problems.
Things like unit tests I just have AI do it all now. Since running the test tells you your coverage you can verify if it got everything or not.
Here’s something that might blow your mind. Coverage is not the point of tests.
If you your passing test gets 100% coverage, you can still have a bug. You might have a bunch of conditions you’re not handling and a shit test that doesn’t notice.
Write tests first to completely define what you want the code to do, and then write the code to pass the tests.
I’d rather be a bad programmer that gets stuff done than a good programmer who’s just jerking off about proper design
t. good programmer
Proper design will save an epic shit ton of money when it inevitably needs to be changed or fixed.
It depends, if you work in a statically typed language you can just use a tool to refactor. I bet a ton of advice is from JavaScript programmers where it’s simply not safe to do this.
My first job doing JavaScript I realized the IDE’s refactor tool wasn’t aware that two variables of the same name were in fact a different variable. Due to how scoping works, it’s hard to write a reliable tool to rename variables for JS. I accidentally introduced a bug renaming a variable.
Our computer science professor in some programming course at university told us we were not supposed to take advice from the internet or answers from Stack Overflow for half a year... Until we learned the ropes. And could asses for ourselves what's right and what is wrong.
I think he was right. There is lots of misinformation out there that isn't a proper design pattern. And with copy-pasting stuff, you don't necessarily learn anything. Whereas learning with some method is efficient and works.
The real learning comes from debugging the garbage code you copied from stack overflow
Debugging only teaches logic. Not structure. No amount cut, paste, debug with teach you the factory pattern.
Debugging and being able to interpret documentation when it exists.
But good lord, the amount of programmers I work with that never use an IDE debugger is unreal. I get that you don’t have to, but Jesus Christ, if yout not getting an expected result, it’s way fucking faster to step through the code and see where the data changes then to slap logging into every line and attempt to read the output.
I mean it also contains great stuff. Niche workarounds, ways to do something more efficiently than some standard library function does.
You just need a means of telling apart the good and the bad. Because there's also people smashing their forehead on the keyboard until it happens to be something that compiles. And people repeating urban legends and outdated info. You somehow need background knowledge to tell it apart.
Well I’m already a bad programmer, at least I save time /j
came here to post this
Just because you are “bad programmer” does not mean you are a bad programmer.
we should use 0, 1 and 2 instead of binary just to represent truer statements like this one
antihumanitarian@lemmy.world 1 year ago
I recently removed in editor AI cause I noticed I was acquiring muscle memory for my brain, not thinking through the rest past the start of a snippet that would get an LLM to auto complete. I’m still using LLMs, particularly for languages and libraries I’m not familiar with, but using the artifacts editors in ChatGPT and Claude.