Hello everyone! For many years, I have been coding every once in a while and actually learned a lot. I especially liked C and C-Like languages and building useless stuff just for fun and for the sake of the intellectual challenge that came with it, but since when AI became decent enough, it just kinda ruined the passion for programming and computers as a whole. Thing is, I am in university now and need to go back to using C and program regularly, but now that AI does everything 20000 times better than I ever will I always either cede to temptation to use it (thus nullifying learning) or just get bored so quickly I just turn off the computer to do something different.
is there a way to revive the interest for programming and building projects? I am doing my best to stop using AI but heck I really am self-indulging. please help!
Don’t use LLMs to learn, if you insist on using them use them to automate things you already can do yourself. Treat university like a 40 hour a week job, you need to put that time in to build knowledge & retain it through practice if you want to develop your knowledge and intuitions. If you’re going to dedicate that time to it you’ll be less inclined to take shortcuts since saving time won’t matter because you’ll spend the same time working at it either way.
Al does everything 20000 times better than I ever will
This is where you’re wrong. Models you can afford are not that good, and you can actually learn to do a lot of stuff better than affordable LLMs ever will
Earlier I replied to someone who made a similar comment to yours: I’m sure AI must have a limit since AGI is still not there and apparently won’t be realized any time soon. I know I can become even better than AI but that is gonna take years and this is the kind of thing that requires for pleasure to be found in the pathway to the objective and not to the objective by itself
now that AI does everything 20000 times better than I ever will
Now I’m no cognitive behavioral therapist, but, uh… this is what I think is catching you.
I use AI plenty. I write most of my code with it. The garbage it spews out if you don’t hand-edit or get ultra-specific with design instructions is just atrocious, even if it looks sleek in the gestalt. You can give it small tasks and one-shots that it handles perfectly, sure, but it will rot a large codebase to the core if you start letting it make any real structural decisions.
There’s simply no replacing architecture and focused thought, and writing code by hand isn’t going anywhere, even if the majority of the industry works with AI. I mentor junior engineers, I’ve seen the worst spaghetti they can make, and I can nonetheless confidently assure you that you’re better than “frontier” AI across multiple domains.
Thank you bro, I just lack willpower to focus on studying the “old way” without AI. Do you think getting a good manual would be better?
Yeah, O’Reilly books or any other printed stuff that strikes your fancy are great options. DDIA and Learning the Bash Shell are personal faves.
I will check it out. I have got a manual of C that really sucks and puts nothing useful on the table. Do you think I should get the official manual?
I’m not a C guy, but afaik the closest thing to a useful manual in print is the K&R book (written by Kernighan & Ritchie, authors of the language).
I have a copy on my shelf and it’s… alright. It’s much more focused on basic language constructs than pragmatic usage and opinionated style. Good for what it is, but you should pick up something more recent and opinionated to go alongside it IMO, based on whatever C dialect you want to focus on (C89/C23).
Thank you for your advice
Np!
If you can’t drop the use of AI for your own learning, use it for learning. Tell it specifically that you want guidance on how to do something, not to do it for you, perhaps have it create a html guide you can follow without it giving you all the answers.
If it does something in a way you didn’t expect, ask why. Ask if the way it has done something is the best way of doing it, and then do a bit of research and challenge it when it’s wrong, and it will definitely be at times.
Don’t use it.
I know it seems like everyone is doing it, and it’s really good and cool, but that’s not reality, and you can certainly just write code the old fashioned way by thinking about what you want to do, and then typing some words on into an IDE or text editor.
AI does t do everything 20000 times better than you ever will.
Don’t tell yourself that.
It’s better than you right now, but every mid-level tech worker will tell you it sucks. You have significantly higher capacity than it, you just have to learn to get there and that isn’t easy or quick.
Thank you for your encouragement :3
I’m not sure it’s even faster. Damn thing ties itself in knots trying to do basic tasks.
Yeah the problem is will he learn faster than AI improves? I wouldn’t want to be in his shoes.
Oh no, they have bettered themselves for nothing!
You should watch TNG When the Bough Breaks, that’s the future we’re heading for if everyone decides to not learn hard things because the computer can do it
And once AI can no longer sustain itself once people become reliant on it, you get the modern version of “The Machine Stops” by E. M. Forster from 1909: https://web.cs.ucdavis.edu/~rogaway/classes/188/materials/the machine stops.pdf
You said
It’s better than you right now, but every mid-level tech worker will tell you it sucks. You have significantly higher capacity than it, you just have to learn to get there and that isn’t easy or quick.
I was just pointing out that this view completely depends on AI improving slower than he does. I would not put money on that.
It does not.
AI can get better but this is learned helplessness.
Of course it does. You said he has a higher capacity than AI and he just needs to learn to get there. Well that’s no help if by the time he does AI has advanced even further.
learned helplessness
No, I just accept reality. You can bury your head in the sand if you like.
It is known that, with effort, a person can improve from the level they are in university
It is not known how much AI can be improved
It is not known how much AI can be improved
I didn’t say it was. But at this point it would be a pretty wild prediction to think it’s not going to continue to rapidly improve.
Is it a wild thing to predict that AI improvement will slow down faster than humans?
Yes.
Why?
A few reasons:
- The evidence so far seems to be that AI capability scales with compute, and compute continues to advance. Including with crazy AI hardware like Cerebras and Taalas. There are still a ton of AI hardware startups that have yet to tape out.
- There’s an enormous amount of research into algorithmic and infrastructure improvements, which also show no signs of slowing down.
- Empirically, it has been getting better continuously for several years now. There appears to be no reason to suspect any blockers.
In other words: why not?
To steel man, the main reasons I would counter with are:
- Moore’s law is pretty much dead… Except that we still have a ton of headroom with custom AI-focused chips. E.g. I know of at least two startups working on DRAM stacked on the compute chip instead of next to it, which gives dramatically higher memory bandwidth.
- There are still a couple of architectural issues, e.g. context length is limited, AI can’t really remember/learn things on-line, hallucination is not solved. But… in practice those problems seem to not matter too much and also hallucinations seem less common the more capable the model is, so maybe it doesn’t need an architectural solution at all.
Yeah, it’s a mental thing. Why draw something when there’s proper artists out there? Why learn to play the guitar when Mark Knopfler is out there? Why assemble a Jacuzzi in your backyard, when there’s a waterpark in the country? Why do your own barbecue when restaurants exist?
These models can create apps that are great for a single person with no skill but they all miss something. its a great tool for analyzing. but it misses in style and domain.
here is my best analogy. i love mesding around with suno the ai music creator. it offers similar fun as mad libs does for me. i plug dhit in snd see what i get. well i am 50 and miss 90s alternative rick/grunge music. i try to see what suno can come up with. recently i tried to have it mimic the wallflowers. it created a song thay seemed technically the same but didnt have the same feel.
a non dev can plug shit in and have an app but it takes skill to use that tool to make a solid piece of software.
AI does everything 20000 times better than I ever will
I find it hard to believe that AI throwing pointers and references at random counts as “20000 times better” than anything.
Besides, saying that means that you fell for the worst trap, of believing that everything it does is flawless. It’s not. You’re in uni, so you don’t really have experience in ordering people around, which is what fucking around with AI is - you give an order and wait for a result. If you trust 100% of the end result, the problem is you.
AI is great at stuff you don’t know about, because when you do know about it, you’ll notice errors and mistakes, making you realize you cannot trust it.
Thank you
The satisfaction you’re looking for comes from the process of learning and doing, not having the final product explained/handed to you. You have to remind yourself that the joy is in the making, not the final product.
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@[email protected], don’t fall for the (insanely voluminous) hype around LLM capabilities.
LLMs aren’t better than you even today. They will extrude mediocre code, far too verbosely, and inevitably lose track of what they are supposed to be doing. When asked to make a change, they will frequently change far too much. They will make a mess that no one understands, least of all the LLM.
You can do better than them, today and in the future, by being curious, reading to understand, intending what you write, and improving from mistakes. LLMs can do none of this, their design does not allow them to.
I honestly feel like I’m going crazy. Everybody is constantly telling me that LLMs are so good and capable, and a lot of people even consider them superior and talk about that like it’s a known fact. But I just don’t see it.
I tried to use them lot of times, but the results were simply not good and I always end up just wasting my time. And everybody is always like “well you have to write the right prompts, they have to be like this and this” or “well it might be that you’re not using the right model, try this and this model” or whatever.
One guy even suggested that I might not be advanced enough to recognize it as good code, because again, LLMs are just so good and that’s a fact. Which, to be fair, I fully admit to not being advanced or very experienced, especially in C++ which I am currently using and trying to learn. So I’m not rejecting this notion outright, it might actually be true. Although, I am experienced and I’d even say advanced in Python, and there I can say for sure that the code written by LLMs is just bad, convoluted, and unmaintainable.
A lot of times that I talk to people about this and explain my experience, and manage to convince them that I tried different prompts, models and everything, they always land on the same conclusion - that the code doesn’t actually have to be readable and maintainable. LLMs are a new interface for coding, thus the code only has to be good enough for the LLM to be able to work with it.
And I honestly can’t even say that this is such a ridiculous idea. That may very well be the path we’re headed towards. And if that is the case, then my insisting on not using LLMs just puts me at a disadvantage since I’m much less productive (assuming that people who use LLMs are actually more productive - which I haven’t seen conclusive studies about). I’ve read a little about this topic on reddit and stuff, and a lot of people really do agree with this - if you don’t use LLMs, you’re just too slow and it will only get worse. And this is coming from people who are (claiming to be) experienced software devs.
My situation is a little bit different though - I’m writing research code and I definitely DO have to be able to read and debug the code. If I don’t, my results might be completely false and come from bugs or wrong functionalities. So I strongly reject using LLMs in my code, at least in the 95% of the code that actually implements my methodology.
But even still, I haven’t had success with getting good code out of LLMs for the 5% that doesn’t deal with the research, so what the hell is going on? I seriously feel like I’m going crazy since it seems to me like I’m the only one who isn’t satisfied with the “capabilities” of LLMs. I can admit that my prompting needs work and that I don’t exactly put much effort into it, but at some point, where do you draw the line? How many paragraphs do I have to write to ensure that the LLM does exactly what I want, before it becomes more work than actually doing it myself? I swear, some of the tips I get from people on prompting are crazy - writing .md files with instructions, writing out every single detail, explaining exactly how to do it and on and on and on. Its honestly easier and quicker just doing it myself.
And another thing - when did it happen that people stopped being embarrassed about heavily using LLMs to code?? Like this just flipped at some point and now people proudly talk about not having written a single line of code in a project (and I mean this literally, I’ve had multiple people tell me this). I cringe so hard every time in these conversations.
So I really have no idea what to think anymore. In any case, I won’t be using LLMs in my research because the main goal is for me to actually learn something, as well as to produce reliable code and results. I’m still early in my research, so there’s no problem with me doing that right now. But there will probably come a time where I will have learned enough about the topic to allow for “blackbox” code because I will be able to verify the functionalities and results, and I certainly expect higher pressure to use LLMs then. I have no idea what I’ll do then.
Thank you bro. Reading through all those comments made me realize that it wasn’t AI to have killed my will to learn, but the strict university deadlines, peer pressure and the fact that I have turned a hobby into something I am not doing for pleasure anymore
It can do classroom bullshit because it’s well-defined, small in scope, and generally isolated. If an entire app can be expressed in 1000 lines of code, AI can probably do it faster and better than you. But when you’re talking about a full microservice or game, it can’t.
Coding skill is about knowing what to build and levels of abstraction. Writing the code itself is more tedium than skill. If you can understand code well enough to see AI output and edit it to repair the bullshit and keep the boilerplate, you’re doing great.
The challenge is AI code looks really good while sucking hind tit. Even I go through this after thirty years of experience. AI writes code that looks great because the stupid stuff it does is largely hidden from you — it is stupid decisions it made and then wrote code consistent with that decision. You haven’t thought through the hard bits so it’s solution looks simple and right. But it did the thing wrong.
I use AI all the time, and I find it helpful, but it’s FAR from perfect. So very far.
is there a way to revive the interest for programming and building projects
Read some books on programming. Or read some programs others have written. This was good advice for finding inspiration even before AI.
You can understand things in principle, implement them once and still use AI afterwards. That’s basically how uni will work from now (at best). I don’t mourn programming on its own tbh, because in the field you rarely do exiting stuff. And the exiting stuff you will likely still have to do, because it is the hard stuff
I agree in spirit, but I disagree that implementing once is enough.
Yeah, perhaps it’s not enough… But the difference between people who had one major coding assignment in uni and people who had none is already staggering
