6 ms·

What you consider fun isn't universal. Some folks don't want to just tinker for half an hour, some folks enjoy getting a particular result that meets specific g

What you consider fun isn't universal. Some folks don't want to just tinker for half an hour, some folks enjoy getting a particular result that meets specific goals. Some folks don't find the mechanics of putting lines of code together as fun as what the code does when it runs. That might sound like paid work to you, but it can be gratifying for not-you.

chung8123 9mo ago
For me it all the build stuff and scaffolding I have to get in place before I can even start tinkering on a project. I never formally learned all the systems and tools and AI makes all of that 10x easier. When I hit something I cannot figure out instead of googling for 1/2 hour it is 10 minutes in AI.
- mbirth 9mo ago
  The difference is that after you’ve googled it for ½ hour, you’ve learned something. If you ask an LLM to do it for you, you’re none the wiser.
  - hyperadvanced 9mo ago
    You can study the LLM output. In the “before times” I’d just clone a random git repo, use a template, or copy and paste stuff together to get the initial version working.
    - inferiorhuman 9mo ago
      Studying gibberish doesn't teach you anything. If you were cargo culting shit before AI you weren't learning anything then either.
      - ben_w 9mo ago
        Necessarily, LLM output that works isn't gibberish. The code that LLM outputs, has worked well enough to learn from since the initial launch of ChatGPT. This even though back then you might have to repeatedly say "continue" because it would stop in the middle of writing a function.
        inferiorhuman 9mo ago
        Necessarily, LLM output that works isn't gibberish. Hardly. Poorly conjured up code can still work.
        ben_w 9mo ago
        "Gibberish" code is necessary code which doesn't work. Even in the broader use of the term: https://en.wikipedia.org/wiki/Gibberish https://en.wikipedia.org/wiki/Gibberish Especially in this context, if a mystery box solves a problem for me, I can look at the solution and learn something from that solution, c.f. how paper was inspired by watching wasps at work. Even the abject failures can be interesting, though I find them more helpful for forcing my writing to be easier to understand.
      - oblio 9mo ago
        It's not gibberish. More than that, LLMs frequently write comments (some are fluff but some explain the reasoning quite well), variables are frequently named better than cdx, hgv, ti, stuff like that, plus looking at the reasoning while it's happening provides more clues. Also, it's actually fun watching LLMs debug. Since they're reasonably similar to devs while investigating, but they have a data bank the size of the internet so they can pull hints that sometimes surprise even experienced devs. I think hard earned knowledge coming from actual coding is still useful to stay sharp but it might turn out the balance is something like 25% handmade - 75% LLM made.
        inferiorhuman 9mo ago
        they have a data bank the size of the internet so they can pull hints that sometimes surprise even experienced devs. That's a polite way of phrasing "they've stolen a mountain of information and overwhelmed resources that humans would use to other find answers." I just discovered another victim: the Renesas forums. Cloudflare is blocking me from accessing the site completely, the only site I've ever had this happen to. But I'm glad you're able to have your fun. it might turn out the balance is something like 25% handmade - 75% LLM made. Doubtful. As the arms race continues AI DDoS bots will have less and less recent "training" material. Not a day goes by that I don't discover another site employing anti-AI bot software.
        ben_w 9mo ago
        > they've stolen a mountain of information In law, training is not itself theft. Pirating books for any reason including training is still a copyright violation, but the judges ruled specifically that the training on data lawfully obtained was not itself an offence. Cloudfare has to block so many more bots now precisely because crawling the public, free-to-everyone, internet is legally not theft. (And indeed would struggle to be, given all search engines have for a long time been doing just that). > As the arms race continues AI DDoS bots will have less and less recent "training" material My experience as a human is that humans keep re-inventing the wheel, and if they instead re-read the solutions from even just 5 years earlier (or 10, or 15, or 20…) we'd have simpler code and tools that did all we wanted already. For example, "making a UI" peaked sometime between the late 90s and mid 2010s with WYSIWYG tools like Visual Basic (and the mac equivalent now known as Xojo) and Dreamweaver, and then in the final part of that a few good years where Interface Builder finally wasn't sucking on Xcode. And then everyone on the web went for React and Apple made SwiftUI with a preview mode that kept crashing. If LLMs had come before reactive UI, we'd have non-reactive alternatives that would probably suck less than all the weird things I keep seeing from reactive UIs.
  - spankibalt 9mo ago
    I don't think "learning" is a goal here...
  - qudat 9mo ago
    Wrong. I will spend 30 minutes having the LLM explain every line of code and why it's important, with context-specific follow-up questions. An LLM is one of the best ways to learn ...
    - _ikke_ 9mo ago
      As long as what it says is reliable and not made up.
      - anakaine 9mo ago
        I feel like we are just covering whataboutism tropes now. You can absolutely learn from an LLM. Sometimes.documentation sucks and the LLM has learned how to put stuff together feom examples found in unusual places, and it works, and shows what the documentation failed to demonstrate. And with the people above, I agree - sometimes the fun is in the end process, and sometimes it is just filling in the complexity we do not have time or capacity to grab. I for one just cannot keep up with front end development. Its an insurmountable nightmare of epic proportions. Im pretty skilled at my back end deep dive data and connecting APIs, however. So - AI to help put together a coherent interface over my connectors, and off we go for my side project. It doesnt need to be SOC2 compliant and OWASP proof, nor does it need ISO27001 compliance testing, because after all this is just for fun, for me.
      - qudat 9mo ago
        That's true for internet searching. How many times have you gone to SO, seen a confident answer, tried it, and it failed to do what you needed?
        Anamon 9mo ago
        Then you write a comment, maybe even figure out the correct solution and fix the answer. If you're lucky, somebody already did. Everybody wins. That's what LLMs take away. Nothing is given back to the community, nothing is added to shared knowledge, no differing opinions are exchanged. It just steals other people's work from a time when work was still shared and discussed, removes any indication of its source, claims it's a new thing, and gives you no way to contribute back, or even discuss it and maybe get confronted with different opinions of even discovering a better way. Let's not forget that one of the main reasons why LLMs are useful for coding in the first place, is that they scraped SO from the time where people still used it.
  - CamperBob2 9mo ago
    I don't want to waste time learning how to install and configure ephemeral tools that will be obsolete before I ever need to use them again.
    - ggggffggggg 9mo ago
      Exactly, the whole point is it wouldn’t take 30 minutes (more like 3 hours) if the tooling didn’t change all the fucking time. And if the ecosystem wasn’t a house of cards 8 layers of json configuration tall. Instead you’d learn it, remember it, and it would be useful next time. But it’s not.
    - Akronymus 9mo ago
      And I don't want to use tools I don't understand at least to some degree. I always get nervous when I do something but don't know why I do that something
      - xnx 9mo ago
        Depends on what level of abstraction you're comfortable with. I have no problem driving a car I didn't build.
        Akronymus 9mo ago
        I didnt build my car either. But I understand a bit of most of the main mechanics, like how the ABS works, how powered steering does, how an ICE works and so on.
  - visarga 9mo ago
    Why train to pedal fast when we already got motorcycles? You are preparing for yesterday's needs. There will never be a time when we need to solve this manually like it's 2019. Even in 2019 we would probably have used Google, solving was already based on extensive web resources. While in 1995 you would really have needed to do it manually. Instead of manual coding training your time is better invested in learning to channel coding agents, how to test code to our satisfaction, how to know if what AI did was any good. That is what we need to train to do. Testing without manual review, because manual review is just vibes, while tests are hard. If we treat AI-generated code like human code that requires a line-by-line peer review, we are just walking the motorcycle. How do we automate our human in the loop vibe reactions?
    - ben_w 9mo ago
      Yes and no. Yes, I recon coding is dead. No, that doesn't mean there's nothing to learn. People like to make comparisons to calculators rendering mental arithmetic obsolete, so here's an anecdote: First year of university, I went to a local store and picked up three items each costing less than £1, the cashier rang up a total of more than £3 (I'd calculated the exact total and pre-prepared the change before reaching the head of the queue, but the exact price of 3 items isn't important enough to remember 20+ years later). The till itself was undoubtedly perfectly executing whatever maths it had been given, I assume the cashier mistyped or double-scanned. As I said, I had the exact total, the fact that I had to explain "three items costing less than £1 each cannot add up to more than £3" to the cashier shows that even this trivial level of mental arithmetic is not universal. I now code with LLMs. They are so much faster than doing it by hand. But if I didn't already have experience of code review, I'd be limited to vibe-coding (by the original definition, not even checking). I've experimented with that to see what the result is, and the result is technical debt building up. I know what to do about that because of my experience with it in the past, and I can guide the LLM through that process, but if I didn't have that experience, the LLM would pile up more and more technical debt and grind the metaphorical motorbike's metaphorical wheels into the metaphorical mud.
      - visarga 9mo ago
        > But if I didn't already have experience of code review, I'd be limited to vibe-coding (by the original definition, not even checking). Code review done visually is "just vibe testing" in my book. It is not something you can reproduce, it depends on the context in your head this moment. So we need actual code tests. Relying on "Looks Good To Me" is hand waving, code smell level testing. We are discussing vibe coding but the problem is actually vibe testing. You don't even need to be in the AI age to vibe test, it's how we always did it when manually reviewing code. And in this age it means "walking your motorcycle" speed, we need to automate this by more extensive code tests.
  - enraged_camel 9mo ago
    >> The difference is that after you’ve googled it for ½ hour, you’ve learned something. I've been programming for 15+ years, and I think I've forgotten the overwhelming majority of the things I've googled. Hell, I can barely remember the things I've googled yesterday.
    - rob74 9mo ago
      Additionally, in the good/bad old days of using StackOverflow, maybe 10% of the answers actually explained how that thing you wanted to do actually worked, the rest just dumped some code on you and left you to figure it out by yourself, or more likely just copy & paste it and be happy when it worked (if you were lucky)...
  - deleted 9mo ago
    [deleted]
  - fleroviumna 9mo ago
    [dead]
  - ajmurmann 9mo ago
    I don't think I'll learn anything by yet again implementing authentication, password reset, forgotten password, etc.
  - dcre 9mo ago
    This is just not true. I have wasted many hours looking for answers to hard-to-phrase questions and learned very little from the process. If an LLM can get me the same result in 30 seconds, it's very hard for me to see that as a bad thing. It just means I can spend more time thinking about the thing I want to be thinking about. I think to some extent people are valorizing suffering itself.
    - codr7 9mo ago
      Learning means friction, it's not going to happen any other way.
      - onemoresoop 9mo ago
        Some of it is friction, some of it is play. With AI you can get faster to the play part where you do learn a fair bit. But in a sense I agree that less is retained. I think that is not because of lack of friciton, instead is the fast pace of getting what you want now. You no longer need to make a conscious effort to remember any of it because it's effortless to get it again with AI if you ever need it. If that's what you mean by friction then I agree.
      - mountain_peak 9mo ago
        "What an LLM is to me is the most remarkable tool that we've ever come up with, and it's the equivalent of a e-bike for our minds"
        codr7 9mo ago
        Which is about as useful as a bike for our airplanes.
      - dcre 9mo ago
        I agree! I just don’t think the friction has to come from tediously trawling through a bunch of web pages that don’t contain the answer to your question.
  - qualifck 9mo ago
    Not necessarily. The end result of googling a problem might be copying a working piece of code off of stack exchange etc. without putting any work into understanding it. Some people will try to vibe out everything with LLMs, but other people will use them to help engage with their coding more directly and better understand what's happening, not do worse.
  - ragequittah 9mo ago
    Usually The thing you've learned after googling for half an hour is mostly that google isn't very useful for search anymore.
jimbokun 9mo ago
The difference is whether or not you find computers interesting and enjoy understanding how they work. For the people who just want to solve some problem unrelated to computers but require a computer for some part of the task, yes AI would be more “fun”.
- phil21 9mo ago
  I don’t find this to be true. I enjoy computers quite a bit. I enjoy the hardware, scaling problems, theory behind things, operating systems, networking, etc. Most of all I find what computers allow humanity to achieve extremely interesting and motivating. I call them the worlds most complicated robot. I don’t find coding overly fun in itself. What I find fun is the results I get when I program something that has the result I desire. Maybe that’s creating a service for friends to use, maybe it’s a personal IT project, maybe it’s having commercial quality WiFi at home everyone is amazed at when they visit, etc. Sometimes - even often - it’s the understanding that leads to pride in craftsmanship. But programming itself is just a chore for me to get done in service of whatever final outcome I’m attempting to achieve. Could be delivering bits on the internet for work, or automating OS installs to look at the 50 racks of servers humming away with cable porn level work done in the cabinets. I never enjoyed messing around with HTML at that much in the 90s. But I was motivated to learn it just enough to achieve the cool ideas I could come up with as a teenager and share them with my friends. I can appreciate clean maintainable code, which is the only real reason LLMs don’t scratch the itch as much as you’d expect for someone like me.
  - tjr 9mo ago
    What I really enjoy in programming is algorithms and bit-twiddling and stuff that might be in Knuth or HAKMEM or whatever. That’s fun. I like writing Lisp especially, and doing cool, elegant functional programs. I don’t enjoy boilerplate. I don’t necessarily enjoy all of the error checking and polishing and minutia in turning algorithms into shippable products. I find AI can be immensely helpful in making real things for people to use, but I still enjoy doing what I find fun by hand.
  - girvo 9mo ago
deleted 9mo ago
[deleted]

chung8123 9mo ago

For me it all the build stuff and scaffolding I have to get in place before I can even start tinkering on a project. I never formally learned all the systems and tools and AI makes all of that 10x easier. When I hit something I cannot figure out instead of googling for 1/2 hour it is 10 minutes in AI.

mbirth 9mo ago
The difference is that after you’ve googled it for ½ hour, you’ve learned something. If you ask an LLM to do it for you, you’re none the wiser.
- hyperadvanced 9mo ago
  You can study the LLM output. In the “before times” I’d just clone a random git repo, use a template, or copy and paste stuff together to get the initial version working.
  - inferiorhuman 9mo ago
    Studying gibberish doesn't teach you anything. If you were cargo culting shit before AI you weren't learning anything then either.
    - ben_w 9mo ago
      Necessarily, LLM output that works isn't gibberish. The code that LLM outputs, has worked well enough to learn from since the initial launch of ChatGPT. This even though back then you might have to repeatedly say "continue" because it would stop in the middle of writing a function.
      - inferiorhuman 9mo ago
        Necessarily, LLM output that works isn't gibberish. Hardly. Poorly conjured up code can still work.
        ben_w 9mo ago
        "Gibberish" code is necessary code which doesn't work. Even in the broader use of the term: https://en.wikipedia.org/wiki/Gibberish https://en.wikipedia.org/wiki/Gibberish Especially in this context, if a mystery box solves a problem for me, I can look at the solution and learn something from that solution, c.f. how paper was inspired by watching wasps at work. Even the abject failures can be interesting, though I find them more helpful for forcing my writing to be easier to understand.
    - oblio 9mo ago
      It's not gibberish. More than that, LLMs frequently write comments (some are fluff but some explain the reasoning quite well), variables are frequently named better than cdx, hgv, ti, stuff like that, plus looking at the reasoning while it's happening provides more clues. Also, it's actually fun watching LLMs debug. Since they're reasonably similar to devs while investigating, but they have a data bank the size of the internet so they can pull hints that sometimes surprise even experienced devs. I think hard earned knowledge coming from actual coding is still useful to stay sharp but it might turn out the balance is something like 25% handmade - 75% LLM made.
      - inferiorhuman 9mo ago
        they have a data bank the size of the internet so they can pull hints that sometimes surprise even experienced devs. That's a polite way of phrasing "they've stolen a mountain of information and overwhelmed resources that humans would use to other find answers." I just discovered another victim: the Renesas forums. Cloudflare is blocking me from accessing the site completely, the only site I've ever had this happen to. But I'm glad you're able to have your fun. it might turn out the balance is something like 25% handmade - 75% LLM made. Doubtful. As the arms race continues AI DDoS bots will have less and less recent "training" material. Not a day goes by that I don't discover another site employing anti-AI bot software.
        ben_w 9mo ago
        > they've stolen a mountain of information In law, training is not itself theft. Pirating books for any reason including training is still a copyright violation, but the judges ruled specifically that the training on data lawfully obtained was not itself an offence. Cloudfare has to block so many more bots now precisely because crawling the public, free-to-everyone, internet is legally not theft. (And indeed would struggle to be, given all search engines have for a long time been doing just that). > As the arms race continues AI DDoS bots will have less and less recent "training" material My experience as a human is that humans keep re-inventing the wheel, and if they instead re-read the solutions from even just 5 years earlier (or 10, or 15, or 20…) we'd have simpler code and tools that did all we wanted already. For example, "making a UI" peaked sometime between the late 90s and mid 2010s with WYSIWYG tools like Visual Basic (and the mac equivalent now known as Xojo) and Dreamweaver, and then in the final part of that a few good years where Interface Builder finally wasn't sucking on Xcode. And then everyone on the web went for React and Apple made SwiftUI with a preview mode that kept crashing. If LLMs had come before reactive UI, we'd have non-reactive alternatives that would probably suck less than all the weird things I keep seeing from reactive UIs.
- spankibalt 9mo ago
  I don't think "learning" is a goal here...
- qudat 9mo ago
  Wrong. I will spend 30 minutes having the LLM explain every line of code and why it's important, with context-specific follow-up questions. An LLM is one of the best ways to learn ...
  - _ikke_ 9mo ago
    As long as what it says is reliable and not made up.
    - anakaine 9mo ago
      I feel like we are just covering whataboutism tropes now. You can absolutely learn from an LLM. Sometimes.documentation sucks and the LLM has learned how to put stuff together feom examples found in unusual places, and it works, and shows what the documentation failed to demonstrate. And with the people above, I agree - sometimes the fun is in the end process, and sometimes it is just filling in the complexity we do not have time or capacity to grab. I for one just cannot keep up with front end development. Its an insurmountable nightmare of epic proportions. Im pretty skilled at my back end deep dive data and connecting APIs, however. So - AI to help put together a coherent interface over my connectors, and off we go for my side project. It doesnt need to be SOC2 compliant and OWASP proof, nor does it need ISO27001 compliance testing, because after all this is just for fun, for me.
    - qudat 9mo ago
      That's true for internet searching. How many times have you gone to SO, seen a confident answer, tried it, and it failed to do what you needed?
      - Anamon 9mo ago
        Then you write a comment, maybe even figure out the correct solution and fix the answer. If you're lucky, somebody already did. Everybody wins. That's what LLMs take away. Nothing is given back to the community, nothing is added to shared knowledge, no differing opinions are exchanged. It just steals other people's work from a time when work was still shared and discussed, removes any indication of its source, claims it's a new thing, and gives you no way to contribute back, or even discuss it and maybe get confronted with different opinions of even discovering a better way. Let's not forget that one of the main reasons why LLMs are useful for coding in the first place, is that they scraped SO from the time where people still used it.
- CamperBob2 9mo ago
  I don't want to waste time learning how to install and configure ephemeral tools that will be obsolete before I ever need to use them again.
  - ggggffggggg 9mo ago
    Exactly, the whole point is it wouldn’t take 30 minutes (more like 3 hours) if the tooling didn’t change all the fucking time. And if the ecosystem wasn’t a house of cards 8 layers of json configuration tall. Instead you’d learn it, remember it, and it would be useful next time. But it’s not.
  - Akronymus 9mo ago
    And I don't want to use tools I don't understand at least to some degree. I always get nervous when I do something but don't know why I do that something
    - xnx 9mo ago
      Depends on what level of abstraction you're comfortable with. I have no problem driving a car I didn't build.
      - Akronymus 9mo ago
        I didnt build my car either. But I understand a bit of most of the main mechanics, like how the ABS works, how powered steering does, how an ICE works and so on.
- visarga 9mo ago
  Why train to pedal fast when we already got motorcycles? You are preparing for yesterday's needs. There will never be a time when we need to solve this manually like it's 2019. Even in 2019 we would probably have used Google, solving was already based on extensive web resources. While in 1995 you would really have needed to do it manually. Instead of manual coding training your time is better invested in learning to channel coding agents, how to test code to our satisfaction, how to know if what AI did was any good. That is what we need to train to do. Testing without manual review, because manual review is just vibes, while tests are hard. If we treat AI-generated code like human code that requires a line-by-line peer review, we are just walking the motorcycle. How do we automate our human in the loop vibe reactions?
  - ben_w 9mo ago
    Yes and no. Yes, I recon coding is dead. No, that doesn't mean there's nothing to learn. People like to make comparisons to calculators rendering mental arithmetic obsolete, so here's an anecdote: First year of university, I went to a local store and picked up three items each costing less than £1, the cashier rang up a total of more than £3 (I'd calculated the exact total and pre-prepared the change before reaching the head of the queue, but the exact price of 3 items isn't important enough to remember 20+ years later). The till itself was undoubtedly perfectly executing whatever maths it had been given, I assume the cashier mistyped or double-scanned. As I said, I had the exact total, the fact that I had to explain "three items costing less than £1 each cannot add up to more than £3" to the cashier shows that even this trivial level of mental arithmetic is not universal. I now code with LLMs. They are so much faster than doing it by hand. But if I didn't already have experience of code review, I'd be limited to vibe-coding (by the original definition, not even checking). I've experimented with that to see what the result is, and the result is technical debt building up. I know what to do about that because of my experience with it in the past, and I can guide the LLM through that process, but if I didn't have that experience, the LLM would pile up more and more technical debt and grind the metaphorical motorbike's metaphorical wheels into the metaphorical mud.
    - visarga 9mo ago
      > But if I didn't already have experience of code review, I'd be limited to vibe-coding (by the original definition, not even checking). Code review done visually is "just vibe testing" in my book. It is not something you can reproduce, it depends on the context in your head this moment. So we need actual code tests. Relying on "Looks Good To Me" is hand waving, code smell level testing. We are discussing vibe coding but the problem is actually vibe testing. You don't even need to be in the AI age to vibe test, it's how we always did it when manually reviewing code. And in this age it means "walking your motorcycle" speed, we need to automate this by more extensive code tests.
- enraged_camel 9mo ago
  >> The difference is that after you’ve googled it for ½ hour, you’ve learned something. I've been programming for 15+ years, and I think I've forgotten the overwhelming majority of the things I've googled. Hell, I can barely remember the things I've googled yesterday.
  - rob74 9mo ago
    Additionally, in the good/bad old days of using StackOverflow, maybe 10% of the answers actually explained how that thing you wanted to do actually worked, the rest just dumped some code on you and left you to figure it out by yourself, or more likely just copy & paste it and be happy when it worked (if you were lucky)...
- deleted 9mo ago
  [deleted]
- fleroviumna 9mo ago
  [dead]
- ajmurmann 9mo ago
  I don't think I'll learn anything by yet again implementing authentication, password reset, forgotten password, etc.
- dcre 9mo ago
  This is just not true. I have wasted many hours looking for answers to hard-to-phrase questions and learned very little from the process. If an LLM can get me the same result in 30 seconds, it's very hard for me to see that as a bad thing. It just means I can spend more time thinking about the thing I want to be thinking about. I think to some extent people are valorizing suffering itself.
  - codr7 9mo ago
    Learning means friction, it's not going to happen any other way.
    - onemoresoop 9mo ago
      Some of it is friction, some of it is play. With AI you can get faster to the play part where you do learn a fair bit. But in a sense I agree that less is retained. I think that is not because of lack of friciton, instead is the fast pace of getting what you want now. You no longer need to make a conscious effort to remember any of it because it's effortless to get it again with AI if you ever need it. If that's what you mean by friction then I agree.
    - mountain_peak 9mo ago
      "What an LLM is to me is the most remarkable tool that we've ever come up with, and it's the equivalent of a e-bike for our minds"
      - codr7 9mo ago
        Which is about as useful as a bike for our airplanes.
    - dcre 9mo ago
      I agree! I just don’t think the friction has to come from tediously trawling through a bunch of web pages that don’t contain the answer to your question.
- qualifck 9mo ago
  Not necessarily. The end result of googling a problem might be copying a working piece of code off of stack exchange etc. without putting any work into understanding it. Some people will try to vibe out everything with LLMs, but other people will use them to help engage with their coding more directly and better understand what's happening, not do worse.
- ragequittah 9mo ago
  Usually The thing you've learned after googling for half an hour is mostly that google isn't very useful for search anymore.

jimbokun 9mo ago

The difference is whether or not you find computers interesting and enjoy understanding how they work. For the people who just want to solve some problem unrelated to computers but require a computer for some part of the task, yes AI would be more “fun”.

phil21 9mo ago
I don’t find this to be true. I enjoy computers quite a bit. I enjoy the hardware, scaling problems, theory behind things, operating systems, networking, etc. Most of all I find what computers allow humanity to achieve extremely interesting and motivating. I call them the worlds most complicated robot. I don’t find coding overly fun in itself. What I find fun is the results I get when I program something that has the result I desire. Maybe that’s creating a service for friends to use, maybe it’s a personal IT project, maybe it’s having commercial quality WiFi at home everyone is amazed at when they visit, etc. Sometimes - even often - it’s the understanding that leads to pride in craftsmanship. But programming itself is just a chore for me to get done in service of whatever final outcome I’m attempting to achieve. Could be delivering bits on the internet for work, or automating OS installs to look at the 50 racks of servers humming away with cable porn level work done in the cabinets. I never enjoyed messing around with HTML at that much in the 90s. But I was motivated to learn it just enough to achieve the cool ideas I could come up with as a teenager and share them with my friends. I can appreciate clean maintainable code, which is the only real reason LLMs don’t scratch the itch as much as you’d expect for someone like me.
- tjr 9mo ago
  What I really enjoy in programming is algorithms and bit-twiddling and stuff that might be in Knuth or HAKMEM or whatever. That’s fun. I like writing Lisp especially, and doing cool, elegant functional programs. I don’t enjoy boilerplate. I don’t necessarily enjoy all of the error checking and polishing and minutia in turning algorithms into shippable products. I find AI can be immensely helpful in making real things for people to use, but I still enjoy doing what I find fun by hand.
- girvo 9mo ago

deleted 9mo ago

[deleted]