5 ms·

> Another common argument I've heard is that Generative AI is helpful when you need to write code in a language or technology you are not familiar with. To me t

• socalgal2 1y ago
  To add, another experience I had. I was using an API I'm not that familiar with. My program was crashing. Looking at the stack trace I didn't see why. Maybe if I had many months experience with this API it would be obvious but it certainly wasn't to me. For fun I just copy and pasted the stack trace into Gemini. ~60 frames worth of C++. It immediately pointed out the likely cause given the API I was using. I fixed the bug with a 2 line change once I had that clue from the AI. That seems pretty useful to me. I'm not sure how long it would have taken me to find it otherwise since, as I said, I'm not that familiar with that API.
  • nottorp 1y ago
    You remember when Google used to do the same thing for you way before "AI"? Okay, maybe sometimes the post about the stack trace was in Chinese, but a plain search used to be capable of giving the same answer as a LLM. It's not that LLMs are better, it's search that got entshittified.
    • Philpax 1y ago
      Google has never identified the logical error in a block of code for me. I could find what an error code was, yes, but it's of very little help when you don't have a keyword to search.
    • FranzFerdiNaN 1y ago
      It was just as likely that Google would point you towards a stackoverflow question that was closed because it was considered a duplicate of a completely different question.
    • jasode 1y ago
      >You remember when Google used to do the same thing for you way before "AI"? [...] stack trace [...], but a plain search used to be capable of giving the same answer as a LLM. The "plain" Google Search before LLM never had the capability to copy&paste an entire lengthy stack trace (e.g. ~60 frames of verbose text) because long strings like that exceeds Google's UI. Various answers say limit of 32 words and 5784 characters: https://www.google.com/search?q=limit+of+google+search+string https://www.google.com/search?q=limit+of+google+search+strin... Before LLM, the human had to manually visually hunt through the entire stack trace to guess at a relevant smaller substring and paste that into Google the search box. Of course, that's do-able but that's a different workflow than an LLM doing it for you. To clarify, I'm not arguing that the LLM method is "better". I'm just saying it's different.
      • nottorp 1y ago
        That's a good point, because now that I think of it, I never pasted a full stack trace in a search engine. I selected what looked to be the relevant part and pasted that. But I did it subconsciously. I never thought of it until today. Another skill that LLM use can kill? :)
      • swader999 1y ago
        Those truly were the dark ages. I don't know how people did it. They were a different breed.
    • 1y ago
  • adriancr1 1y ago
    You missed out on developing debugging skills. Analyzing crash dumps and figuring out what's going on is a pretty useful skill.
• turtlebits 1y ago
  It's perfect for small boilerplate utilities. If I need a browser extension/tampermonkey script, I can get up and running quickly without having to read docs/write manifests. These are small projects where without AI, I wouldn't have bothered to even start. At its least, AI can be extremely useful for autocompleting simple code logic or automatically finding replacements when I'm copying code/config and making small changes.
• thedelanyo 1y ago
  So AI is basically best as a search engine.
  • groestl 1y ago
    That's right.
  • cess11 1y ago
    I mean, it's just a compressed database with a weird query engine.
  • jrm4 1y ago
    As I've said a bunch. AI is a search engine that can also remix its results, often to good effect.
  • antisthenes 1y ago
    Alwayshasbeen.jpg meme. I mean yes, current large models are essentially compressing incredible amounts of content into something manageable by a single Accelerator/GPU, and making it available for retrieval through inference.
• nikanj 1y ago
  And ChatGPT never closes your question without answer because it (falsely) thinks it's a duplicate of a different question from 13 years ago
  • nottorp 1y ago
    But it does give you a ready to copy paste answer instead of a 'teach the man how to fish' answer.
    • addandsubtract 1y ago
      Not if you prompt it to explain the answer it gives you.
      • nottorp 1y ago
        Not the same thing. Copying code, even with comprehensive explanations, teaches less than writing/adjusting your own code based on advice.
        • elbear 1y ago
          It can also do that if you ask it. It can give you exercises that you can solve. But you have to specifically ask, because by default it just gives you code.
          • nottorp 1y ago
            Of course, I originally was picking on Stack Overflow's moderation. Which strongly discouraged trying to teach people.
            • elbear 1y ago
              Oh, I missed that. I also missed that about StackOverflow, although I wasn't active there. It sounds like the motto of SO was "Solve problems!" instead of "Teach people how to solve problems!".
• plasticeagle 1y ago
  ChatGPT and Gemini literally only know the answer because they read StackOverflow. Stack Overflow only exists because they have visitors. What do you think will happen when everyone is using the AI tools to answer their questions? We'll be back in the world of Encyclopedias, in which central authorities spent large amounts of money manually collecting information and publishing it. And then they spent a good amount of time finding ways to sell that information to us, which was only fair because they spent all that time collating it. The internet pretty much destroyed that business model, and in some sense the AI "revolution" is trying to bring it back. Also, he's specifically talking about having a coding tool write the code for you, he's not talking about using an AI tool to answer a question, so that you can go ahead and write the code yourself. These are different things, and he is treating them differently.
  • socalgal2 1y ago
    > ChatGPT and Gemini literally only know the answer because they read StackOverflow. Stack Overflow only exists because they have visitors. I know this isn't true because I work on an API that has no answers on stackoverflow (too new), nor does it have answers anywhere else. Yet, the AI seems to able to accurately answer many questions about it. To be honest I've been somewhat shocked at this.
    • b112 1y ago
      It is absolutely true, and AI cannot think, reason, comprehend anything it has not seen before. If you're getting answers, it has seen it elsewhere, or it is literally dumb, statistical luck. That doesn't mean it knows the answer. That means it guessed or hallucinated correctly. Guessing isn't knowing. edit: people seem to be missing my point, so let me rephrase. Of course AIs don't think, but that wasn't what I was getting at. There is a vast difference between knowing something, and guessing. Guessing, even in humans, is just the human mind statistically and automatically weighing probabilities and suggesting what may be the answer. This is akin to what a model might do, without any real information. Yet in both cases, there's zero validation that anything is even remotely correct. It's 100% conjecture. It therefore doesn't know the answer, it guessed it. When it comes to being correct about a language or API that there's zero info on, it's just pure happenstance that it got it correct. It's important to know the differences, and not say it "knows" the answer. It doesn't. It guessed. One of the most massive issues with LLMs is we don't get a probability response back. You ask a human "Do you know how this works", and an honest and helpful human might say "No" or "No, but you should try this. It might work". That's helpful. Conversely a human pretending it knows and speaking with deep authority when it doesn't is a liar. LLMs need more of this type of response, which indicates certainty or not. They're useless without this. But of course, an LLM indicating a lack of certainty, means that customers might use it less, or not trust it as much, so... profits first! Speak with certainty on all things!
• PeterStuer 1y ago
  I love leaning new things. With ai I am learning more and faster. I used to be on the Microsoft stack for decades. Windows, Hyper-V, .NET, SQL Server ... . Got tired of MS's licensing BS and I made the switch. This meant learning Proxmox, Linux, Pangolin, UV, Python, JS, Bootstrap, NGinx, Plausible, SQLite, Postgress ... Not all of these were completely new, but I had never dove in seriously. Without AI, this would have been a long and daunting project. AI made this so much smoother. It never tires of my very basic questions. It does not always answer 100% correct the first time (tip: paste in the docs of specific version of the thing you are trying to figure out as it sometimes has out-of-date or mixed version knowledge), but most often can be nudged and prodded to a very helpfull result. AI is just an undeniably superior teacher than Google or Stack Overflow ever was. You still do the learning, but the AI is great in getting you to learn.
  • rootnod3 1y ago
    I might be an outlier, but I much prefer reading the documentation myself. One of the reasons I love using FreeBSD and OpenBSD as daily drivers. The documentation is just so damn good. Is it a pain in the ass at the beginning? Maybe. But I require way less documentation lookups over time and do not have to rely on AI for that. Don't get me wrong, I tried. But even when pasting the documentation in, the amount of times it just hallucinated parameters and arguments that were not even there were such a huge waste of time, I don't see the value in it.
• greybox 1y ago
  I trust chatgpt and gemini a lot less than stackoverflow. On stackoverflow I can see the context that the answer to the original question was given in. AI does not do this. I've asked chatgpt questions about cmake for instance that it got subtly wrong, if I had not noticed this it would have cost me aa lot of time.
• BlackFly 1y ago
  One of the many ways that search got worse over time was the promotion of blog spam over actual documentation. Generally, I would rather have good API documentation or a user guide that leads me through the problem so that next time I know how to help myself. Reading through good API documentation often also educates you about the overall design and associated functionality that you may need to use later. Reading the manual for technology that you will be regularly using is generally quite profitable. Sometimes, a function doesn't work as advertised or you need to do something tricky, you get a weird error message, etc. For those things, stackoverflow could be great if you could find someone who had a similar problem. But the tutorial level examples on most blogs might solve the immediate problem without actually improving your education. It would be similar to someone solving your homework problems for you. Sure you finished your homework, but that wasn't really learning. From this perspective, ChatGPT isn't helping you learn.
  • blueflow 1y ago
    You parent searches for answers, you search for documentation. Thats why AI works for him and not for you.
    • ryaniscool 1y ago
      You're completely missing his point. If nobody figures things out for themselves, there's a risk that at some point, AI won't have anything to learn on since people will stop writing blog posts on how they figured something out and answering stack overflow questions. Sure, there is a chance that one day AI will be smart enough to read an entire codebase and chug out exhaustively comprehensive and accurate documentation. I'm not convinced that is guaranteed to happen before our collective knowledge falls off a cliff.
      • blueflow 1y ago
        Read it again, slowly. FSVO "works": Thats why AI works for him and not for you. We both agree.
    • BlackFly 1y ago
• yard2010 1y ago
  I think the main issue here is trust. When you google something you develop a sense for bullshit so you can "feel" the sources and weigh them accordingly. Using a chat bot, this bias doesn't hold, so you don't know what is just SEO bullshit reiterated in sweet words and what's not.
• raxxorraxor 1y ago
  For anything non-trivial you have to verify the results. I disabled AI autocomplete and cannot understand how people can use it. It was mostly an extra key press on backspace for me. That said, learning new languages is possible without searching anything. With a local model, you can do that offline and have a vast library of knowledge at hand. The Gemini results integrated in Google are very bad as well. I don't see the main problem to be people just lazily asking AI for how to use the toilet, but that real knowledge bases like stack overflow and similar will vanish because of lacking participation.
• perrygeo 1y ago
  > Getting answers to those question is learning, regardless of where the answer comes from. Sort of. The process of working through the question is what drives learning. If you just receive the answer with zero effort, you are explicitly bypassing the brain's learning mechanism. There's huge difference between your workflow and fully Agentic AIs though. Asking an AI for the answer in the way you describe isn't exactly zero effort. You need to formulate the question and mold the prompt to get your response, and integrate the response back into the project. And in doing so you're learning! So YOUR workflow has learning built in, because you actually use your brain before and after the prompt. But not so with vibe coding and Agentic LLMs. When you hit submit and get the tokens automatically dumped into your files, there is no learning happening. Considering AI agents are effectively trying to remove any pre-work (ie automating prompt eng) and post-work (ie automating debugging, integrating), we can see Agentic AI as explicitly anti-learning. Here's my recent vibe coding anecdote to back this up. I was working on an app for an e-ink tablet dashboard and the tech stack of least resistance was C++ with QT SDK and their QML markup language with embedded javascript. Yikes, lots of unfamiliar tech. So I tossed the entire problem at Claude and vibe coded my way to a working application. It works! But could I write a C++/QT/QML app again today - absolutely not. I learned almost nothing. But I got working software!
  • Eisenstein 1y ago
    The logical conclusion of this is 'the AI just solves the problem by coding without telling you about it'. If we think about 'what happens when everyone vibe-codes to solve their problems' then we get to 'the AI solves the problem for you, and you don't even see the code'. Vibe-coding is just a stop on the road to a more useful AI and we shouldn't think of it as programming.
    • icedchai 1y ago
      It "tells you about it" with code. You can still learn from the code AI has produced. It may be suboptimal or messy... but so is code produced by many of our fellow humans.
• rich_sasha 1y ago
  I sort of disagree with this argument in TFA, as you say, though the rest of the article highlights a limitation. If I'm unfamiliar with the API, I can't judge whether the answer is good. There is a sweet spot of situations I know well enough to judge a solution quickly, but not well enough to write code quickly, but that's a rather narrow case.
• 0x500x79 1y ago
  For one-offs, sure! Go for it. For production/things you will have to manage long-term I would recommend learning some of the space given the output of AI and your capability to surpass that pretty quickly.