It's going to be interesting to see the AI generation arriving in the workplace, ie kids who grew up with ChatGPT, and have never learned to find something in a source document themselves. Not even just about coding, about any other knowledge.
I am from the generation whose only options on the table were RTFM and/or read the source code. Your blend of comment was also directed at the likes of Google and StackOverflow. Apparently SO is not a problem anymore, but chatbots are.
I welcome chatbots. They greatly simplify research tasks. We are no longer bound to stake/poorly written docs.
I think we have a lot of old timers ramping up on their version of "I walked 10 miles to school uphill both ways". Not a good look. We old timers need to do better.
No, it wasn't.
What such comments were directed at, and with good reason, where 'SO-"Coders"', aka. people when faced with any problem, just googled a vague description of it, copypasted the code from the highest scoring SO answer into their project, and called it a day.
SO is a valueable resource. AI Systems are a valueable resource. I use both every day, same as I almost always have one screen dedicated to some documentation page.
The problem is not using the tools available. The problem is relying 100% on these tools, with no skill or care of ones own.
I had the good fortune to work with a man who convinced me to go read the spec of some of the programming languages I used. I'm told this was reasonably common in the days of yore, but I've only rarely worked on a team with someone else who does it.
Reading a spec or manual helps me understand the language and aids with navigating the text later when I use it as documentation. That said, if all the other programmers can do their jobs anyway, is it really so awful for them to learn from StackOverflow and Google? Probably not.
I imagine the same is true of LLMs.
Chatbots like Copilot, Cursor, Mistral, etc serve the same purpose that StackOverflow does. They do a far better job at it, too.
> The problem is not using the tools available. The problem is relying 100% on these tools, with no skill or care of ones own.
Nonsense. The same blend of criticism was at one point directed at IDEs and autocompletion. The common thread is ladder-pullers complaining how the new generation doesn't use the ladders they've used.
I repeat: we old timers need to do better.
And it kind of was a problem. There was an underclass of people who simply could not get anything done if it wasn't already done for them in a Stackoverflow answer or a blog post or (more recently and bafflingly) a Youtube video. These people never learned to read a manual and spent their days flailing around wondering why programming seemed so hard for them.
Now with AI there will be more of these people, and they will make it farther in their careers before their lack of ability will be noticeable by hiring managers.
As a second-order effect, I think there's a decline in expected docs quality (of course depends on the area). Libraries and such don't expect people to read through them, so they are spotty and haphazard, with only some random things mentioned. No wider overviews and explanations, and somewhat rightly so, why try to write it if (nearly) no one will read it. So only tutorials and Q&A sites remain besides of API dumps.
Which is a great opportunity btw to drive forward a transition to a post-monetary, non-commercial post-scarcity open-source open-access commons economy.
i think that represents a huge paradigm shift that we need to contend with. it isn't just "better" research. and i say this as someone who welcomes all of this that has come.
IMO the skill gap just widens exponentially now. you will either have the competent developers who use these tools accelerate their learning and/or output some X factor, and on the other hand you will have literally garbage being created or people who just figure out they can now expend 1/10 the effort and time to do something and just coast, never bother to even understand what they wrote.
just encountered that with some interviews where people can now scaffold something up in record time but can't be bothered to refine it because they don't know how. (ex. you have someone prompting to create some component and it does it in a minute. if you request a tweak, because they don't understand it they just keep trying re-prompt and micromanage the LLM to get the right output when it should only take another minute for someone experienced.)
Strong agree. There have been people who blindly copied answers from Stack Overflow without understanding the code, but most of us took the time to read the explanations that accompanied the answers.
While you can ask the AI to give you additional explanations, these explanations might be hallucinations and no one will tell you. On SO other people can point out that an answer or a comment is wrong.
Are you sure? Because chatbots are used exactly like SO, with the exception of usecases like a) using as glorified template and refactoring engines, b) explain existing codebases, c) automatically add unit tests and context-based documentation. Just open SO and check any random question: how to get a framework to do something, how to configure something, why something worked like this or like that, why did a code block had a bug, etc.
Agree. Ai answers actually work and are less out of date
Jokes aside, I feel this is really the case. Chatbots have the exact same usecases, but as their response time is measured in seconds instead of days and the responses reflects the context from that moment, this opens the door for more interactive experience and more iterations over the same output.
I feel this anger towards LLMs comes from gatekeepers who felt slighted by having to spend so much effort to reach positions where people with chatbots take instances, and as they can no longer close gates or pull ladders they start to bitch and whine against LLMs. It's as simple as that.
This is it. You will have real developers, as you do today, and developers who are only capable of creating what the latest AI model is capable of creating. They’re just a meat interface for the AI.
No, the problem is created and perpetuated by people defaulting to building communities around Discord servers or closed WhatsApp groups. Those are true information black holes.
And yes, privacy and commons are in opposition. There is a balance to be had. IMHO, in the past few years, we've overcorrected way too much in the privacy direction.
What can possibly go wrong?!?
I think the same tendency of some programmers to just script kiddie their way out of problems using SO answers without understanding the issue will be exacerbated by the proliferation of AI which is much more convincing about wrong answers.
It's not a binary. You don't have to hate or welcome chatbots, no in between. We all use them, but we all also worry about the negatives, same with SO.
So far, AI cannot do that. But it can pretend to, very convincingly.
So now we can get wrong code but written in a more confident language.
If you are lucky it’s a hallucination and the error is obvious.
The lesson to learn is rather that also in "real life", you shouldn't trust confident people.
from what i gather, the training data often contains those same poorly written docs and often a lot of poorly written public code examples, so… YMMV with this statement as it is often fruit from the same tree.
(to me LLMs are just a different interface to the same data, with some additional issues thrown in, which is why i don’t care for them).
> I think we have a lot of old timers ramping up on their version of "I walked 10 miles to school uphill both ways". Not a good look. We old timers need to do better.
it’s a question of trust for me. with great power (new tools) comes great responsibility — and juniors ain’t always learned enough about being responsible yet.
i had a guy i was doing arma game dev with recently. he would use chatgpt and i would always warn him about not blindly trusting the output. he knew it, but i would remind him anyway. several of his early PRs had obvious issues that were just chatgpt not understanding the code at all. i’d point them out at review, he’d fix them and beat himself up for it (and i’d explain to him it’s fine don’t beat yourself up, remember next time blah blah).
he was honest about it. he and i were both aware he was very new to coding. he wanted to learn. he wanted to be a “coder”. he learned to mostly use chatgpt as an expensive interface for the arma3 docs site. that kind of person using the tools i have no problem with. he was honest and upfront about it, but also wanted to learn the craft.
conversely, i had a guy in a coffee shop recently claim to want to learn how to be a dev. but after an hour of talking with him it became increasingly clear he wanted me to write everything for him.
that kind of short sighted/short term gain dishonesty seems to be the new-age copy/pasting answers from SO. i do not trust coffee shop guy. i would not trust any PR from him until he demonstrates that he can be trusted (if we were working together, which we won’t be).
so, i get your point about doom and gloom naysaying. but there’s a reason for the naysaying from my perspective. and it comes down whether i can trust individuals to be honest about their work and how they got there and being willing to learn, or whether they just want to skip to end.
essentially, it’s the same copy/pasting directly from SO problem that came before (and we’re all guilty of).
It’s not just bad optics; it’s destructive. It discourages folks from learning.
AI is just another tool. There’s folks that sneer at you if you use an IDE, a GUI, a WYSIWYG editor, or a symbolic debugger.
They aren’t always boomers, either. As a high school dropout, with a GED, I’ve been looking up noses, my entire life. Often, from folks much younger than me.
It’s really about basic human personal insecurity, and we all have that, to some degree. Getting around it, is a big part of growing up, so a lot of older folks are actually a lot less likely to pull that crap than you might think.
https://en.m.wikipedia.org/wiki/Google_Books
As other AI companies argue, copyright doesn't apply when training, it should give Google a huge advantage to be able to use all the worlds books they scanned.
Of course AI is incredibly useful both for reading foreign language forums and for analysing complex code bases for original research. AI is great for supercharging traditional research
1) There are no idiots who want to do better than AI, and/or
2) All idiots are lazy idiots.
The reason we're even discussing LLMs so much in the first place, is AI can and does things better than "idiots"; hell, it does things better than most people, period. Not everything in every context, but a lot of things in a lot of contexts.
Like run-of-the-mill short-form writing, for example. Letters, notices, copywriting, etc. And yes, it even codes better than general population.
An LLM isn't a mind reader so if you never learn how to seek the answers you're looking for, never curious enough to dig deeper, how would you ever break through the first wall you hit?
In that way the LLM is no different than searching Google back when it was good, or even going to a library.
We never got to the question of recursive or iterative methods.
The most worrying thing is that the LLM were not very useful three years ago when he started university. So the situation is not going to improve.
The reason we ask people to do fizzbuzz is often just to weed out the shocking number of people who cannot code at all.
When the client knows absolutely nothing about it and is not supported by someone competent, they end up employing just anyone.
This applies to both construction, IT and probably everthing.
I think it will be a hot minute before nothing has to be known and all human knowledge is irrelevant, but, specially in CS, there is going to be a tremendous amount of rethinking to do, of what is actually important to know.
LLM are very poor in areas such as real time and industrial automation, as there is very little data available for training.
Even if the LLM were good, we will always need someone to carry out tests, formal validation, etc.
Nobody want to get on a plane or in a car whose critical firmware has been written by an LLM and proofread by someone incapable of writing code (don't give ideas to Boeing ).
The question about Fibonacci is just a way of gently bringing up other topic.
I see nothing mention here as something that a human inherently needs to concern themselves with, because none of these things are things that humans inherently care about. CS as a discipline is a layer between what humans want and how to make computers do these things. If todays devs are so far detached from dealing with 1s and 0s (which is not at all how it obviously had to develop) why would any of the other parts you mention be forever necessary given enough artificial intelligence?
Sure, it's fun (as a discipline) for some of us, but humans inherently do not care about computer memory or testing. A good enough AI will abstract it away, to the degree that it is possible. And, I believe, it will also do a better job than any human ever did, because we are actually really, really bad at these things.
Any difficult problem will take the focus out of coding and into the problem itself.
See also fizz-buzz, which it is even simpler, and people still fail those interview questions.
Really?
If I were to rank the knowledge relevant to this task in terms of importance, or relevance to programming in general, I'd rank "remembering what a Fibonacci number is" at the very bottom.
Sure, it's probably important in some areas of math I'm not that familiar with. But between the fields of math and hard sciences I am familiar with, and programming as a profession, by far the biggest (if not the only) importance of Fibonacci sequence is in its recursive definition, particularly as the default introductory example of recursive computation. That's all - unless you believe in the mystic magic of the Golden Ratio nonsense, but that's another discussion entirely.
Myself, I remember what the definition is, because I involuntarily memorize trivia like this, and obviously because of Fibonacci's salad joke. But I wouldn't begrudge anyone in tech for not having that definition on speed-dial for immediate recall.
> He was unable to explain to me how he would have implemented the Fibonacci sequence without chatGPT.
An appropriate answer could have been "First, I look up what the Fibonacci sequence is on Wikipedia..." The interviewee failed to come up with anything other than the chatbot, e.g. failed to even ask the interviewer for the definition of the sequence, or come up with an explaination for how they could look it up themselves.
I once got that question in an interview for a small startup and told the interviewer: with all due respect what does that have to do with the job I’m going to do and we moved on to the next question (still passed).
If someone tells you not to do it recursively, you should be able to figure that out too.
Interview nerves might get in your way, but it’s not a trick question you need to memorize.
"Let's implement a function to return us the Nth fibonnaci number.To get a fib (fibonacci) number you add the two previous numbers, so fib(N)=fib(N-1)+fib(N+2). The starting points are fib(0)=1 and fib(1)=1. Let's assume the N is never too big (no bigger than 20)."
And that's a problem if they can't solve it.
OTOH about 15 years ago I heard from a friend that interviewed candidates that some people couldn't even count all the instances of 'a' in a string. So in fact not much has changed, except that it's harder to spot these kind of people.
Instead, you're better off focusing on relevant topics like SQL, testing, refactoring, and soft skills.
These "clever" questions are pointless. They either serve to stroke the interviewer’s ego: "Look, I know this CS 101 problem because I just looked it up!", or to create a false image of brilliance: "Everyone here can invert binary trees!"
But I agree you can hire a shitty programmer, because his soft skills are amazing. I worked with people that wouldn't contribute much to the code, but created a culture and improved processes in the company. But you should be aware that you are not hiring for a coding position then.
that's why i'd ask about duff's device. I often admit i am no programmer or developer, here on HN, and that's true. I've only ever implemented recursion when it's part of the pattern or when "learning" a language.
my understanding is that recursion is great for tight, small loops, where you need to do say 0<n<10 loops. But if you can't guarantee the tight loop every time, i.e., if it is a dynamic part of business logic or whatever, then you run the risk of blowing up the stack, or heap, or whatever it is. I don't remember which, and i could look it up; but my point is most developers don't need to know if the stack is at risk rather than the heap if your recursive call ends up being called a lot of times.
But i really would ask about duff's; me and a friend came up with a use for duff's device maybe 2005 or 2006, and tested it, and published it as part of a forum argument; but i am curious if anyone else could "come up with one" or "remember one" that isn't the "de-facto duff's device demonstration".
IDE's are fantastic tools - don't get me wrong - but if you can't navigate a file system, work to understand the harness involved in your build system, or discern the nature of your artefacts and how they are loaded and interact in your target system, you're not doing yourself any favours by having the IDE do all that work for you.
And now what we see is people who not only can't program without an IDE, but can't be productive without a plugin in that IDE, doing all the grep'ing and grok'ing for them.
There has been a concerted effort to make computers stupider for stupid users - this has had a chilling effect in the development world, as well. Folks, if you can't navigate a filesystem with confidence and discern the contents therein, you shouldn't be touching the IDE until you can.
Unfortunately they also project their ignorance, so there’s massive pushback from more senior employees when anyone who does understand tries to untangle the mess and make it more robust.
The same thing will happen with these ML tools in the future, mark my words: writing code will come to be seen as “too complex and error prone” and barely working, massively inefficient and fragile generated code bases will be revered and protected with “don’t fix what isn’t broken”
I have very early (and somewhat fond) memories of reviewing every single index card, every single hole in the punch-tape, every single mnemonic, to ensure there were no undiscovered side-effects.
However, there is a point where the directory structure is your friend, you have to trust your colleagues ability to understand the intent behind the structure, and you can leverage the structure to gain great results.
Always remember: software is a social construct, and is of no value until it is in the hands of someone else - who may, or may not, respect the value of understanding it...
His justification was that some AI had endorsed it as the correct method. There are already out there salaried professionals supporting such flawed logic.
When they are stuck without it, they get hopelessly lost. They feel strangled, distracted, and find it hard to focus on the road. For about 3 days. Then they pretty quickly get up to speed, and kinda remember where they used to make the left turns when they had GPS, and everything is dandy.
But it happens so infrequently, that it's really not worth the time thinking about it.
And the truth is, I am just guessing what happens after 3 days - since anyone who grew up with GPS will never be that long without it.
Otherwise I recall an old saying: 'Robots will take the job of engineers as soon as being able to figure out and make what the client needs, not what the client asks. I think we are safe'. Along this, I hope AI becomes a good tool, subordinate, or maximum a colleague. But not a father figure for big infants.
Its one thing to have the AI work through the materials and explain it.
Its another thing to have lost a lot of the background information required to sustain that explanation.
Greater productivity, is of course, a subjective measure. If that's all that matters, then being glib is perfectly acceptable. But, the value of that productivity may change in a different context - for example, I find it very difficult to go back to AI-generated code some months later, and understand it - unless I already took the time earlier to discern the details.