That’s how you, an experienced programmer, use it.
What does this do to beginners that are just learning to program? Is this helping them by forcing them to become critical reviewers or harming them by being a bad role model?
What does this do to beginners that are just learning to program? Is this helping them by forcing them to become critical reviewers or harming them by being a bad role model?
The UI for an LLM answer would have difficulty replicating the same thing since every answer is (probably) a new one and you have no input from other people about this answer too.
Edit: After writing my reply, I saw that roughly four other people (so far) made the exact same point and posted it a couple of minutes before. I think your question is a good one (made me think a little) and apologies it feels like you're being piled on.
Chat interface has an advantage of having user-specific context and follow up questions, so it can filter and refine answers for the user.
With StackOverflow search it's up to the user to judge whether the answer they've found applies to their situation.
But it will continue to outright lie to you in those follow-ups.
https://chatgpt.com/share/767d2810-b38f-46e2-8cde-09248bb636...
LLMs totally have a beginner problem. It's much like the problem where a beginner knows they need to look something up but can't figure out the right keywords to search for.
Also chatgpt has never called me an idiot for asking a stupid question, having not read the question properly, and making the assumption it was the same as an existing question after skimming it. I wouldn't ask SO a question these days, the response is more likely to be toxic than helpful.
It’s like the saying “the fog of war” (at best you have incomplete and flawed information). Programming is just like that
I'd argue the best way to learn is to read a lot of production-quality code to get a sense of structure and best practices in any given language.
Debugging is the primary skill of a programmer. 90% of programming is fixing bugs, the other 10% is writing bugs.
Maybe the LLM is teaching debugging by giving bad examples :)
I don't think this is a valid comparison. If you'd read 10,000 hours of sheet music I'd wager you'd know how to read music.
At the first lesson he realised that the characters he thought he knew how to pronounce didn't sound much like he was used to. Mongolian is generally written with cyrillic plus a few more characters, so he expected it to be like russian or bulgarian with a few more sounds.
This is not the case. Mongolian is much closer related to korean and tibetan, and commonly sounds something like drunk cats haggling over something deceased.
I find it to be roughly the same with introductory or otherwise shallow learning material about programming. You can read as many tutorials as you want, you'll still suck at it.
When the LLM:s invent books like SICP, The Art of Computer Programming, Purely Functional Data Structures, Gang of Four, then they might become tutors in this area. To me it seems they struggle hard with anything longer than a screenful.
I agree, but it's better foundation than getting something to compile and thinking you "get it."
Harming them.
I told a new grad employee to write some unit tests for his code, explained the high level concepts and what I was looking for, and pointed him at some resources. He spun his wheels for weeks, and it turned out he was trying to get ChatGPT to teach him how to do it, but it would always give him wrong answers.
I eventually had to tell him, point blank, to stop using ChatGPT, read the articles, and ask me (or a teammate) if he needed help.
Answers don't exist in a vacuum. The chat interface allows feedback and corrections. Users can paste an error they're getting, or even say "it doesn't work", and GPT may correct itself or suggest an alternative.
> Answers don't exist in a vacuum. The chat interface allows feedback and corrections. Users can paste an error they're getting, or even say "it doesn't work", and GPT may correct itself or suggest an alternative.
I think you're making the mistake of viewing the job as a black box that produces output.
But what you're proposing is a terrible way to develop someone's skills and judgement. They won't develop if they're getting their hand held all the time (by an LLM or a person), and they'll stagnate. The problem with an LLM, unlike a person, it that it will hold your hand forever without complaint, while giving unreliable advice.
Getting some results with the help of infinitely-patient GPT may motivate people to learn more, as opposed to losing motivation from getting stuck, having trouble finding right answers without knowing the right terminology, and/or being told off by StackOverflow people that's a homework question.
People who want to grow, can also use GPT to ask for more explanations, and use it as a tutor. It's much better at recalling general advice.
And not everyone may want to grow into a professional developer. GPT is useful to lots of people who are not programmers, and just need to solve programming-adjacent problems, e.g. write a macro to automate a repetitive task, or customize a website.
> ...People who want to grow, can also use GPT to ask for more explanations, and use it as a tutor. It's much better at recalling general advice.
The psychology there doesn't make sense, since the technology simultaneously takes away a big motivation to actually learn how to get the result on your own. It's like giving a kid a calculator and expecting him to use it to learn mental arithmetic. Instead, you actually just removed the motivation for most kids to do so.
I think there's a common, unstated assumption in tech circles that removing "friction" and making things "easier" is always good. It's false.
Also, a lot of what you said feels like a post-hoc rationalization for applying this particular technology as a solution to a particular problem, which is a big problem with discourse around "AI" (just like it was with blockchain). That stuff is just in the air.
> ...and/or being told off by StackOverflow people that's a homework question.
IMHO, that's the one legitimately demotivating thing on your list.
I think we all partly learnt about code quality by having our code break things in the real world.
That's why classes are taught by professors and not undergrads. Professors are at least supposed to know what they don't know.
When students think of ChatGPT as their drunk frat bro they see doing keg stands at the Friday basement party rather than as an expert they use it differently.