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It is opposite for me than what the author describes. With AI I can explore new areas far more effectively. For example, I have never been great with front end

It is opposite for me than what the author describes. With AI I can explore new areas far more effectively. For example, I have never been great with front end web stuff, but asking LLMs to generate something and then looking at the code they built is pretty cool. Of course there are errors and gaffes and weird bits all over, but that helps keep me in the loop and understanding it better. I can now (more) boldly go where I feared to tread before.

grebc 28d ago
Is reading example code uncool?
- Scubabear68 27d ago
  I often find that example code never covers my use cases, and I am left scratching my head over nuances not covered there. With AI, I can describe my exact use case and see what it gives me. Sometimes it will just cough up a furball like a boilerplate example, but usually it gets pretty close, and I can see how my (maybe weird) edge case fits into the framework or API or whatever. It may be that I approach problems in a weird way, and that is why examples are less helpful than with some, but AI generally does better here for me.
  - grebc 27d ago
    Examples are so because they’re just that. Nuance belongs in actual implementation. I guess what you’re saying is you like reading fully fledged code, almost like an apprentice. I would never think to delegate that responsibility to a next word guesser.
FinnLobsien 28d ago
I think the difference is that you read the code and get curious about it rather than glancing at the output and immediately telling it what to correct.
nemesis17 28d ago
I feel the same empowerment. LLMs allow me to tap into my second-order knowledge.
wolvoleo 28d ago
Same here. It really helps me get deep into things that would have been daunting to start due to the boring research work required. I have heavy ADHD and high intelligence (not to brag, it is often more of a burden than a blessing!) so I can understand things really quickly but I have no patience for painstaking research or planning and documentation. I just want to build, to create and make my vision come to life but I'm really one-sided about that. I don't care about how it fits in the organisation process, the governance or where it should be documented. And when I need to learn something new I hate doing courses because they're always too slowly paced for me. All courses are paced for the slowest possible participant. Especially those from the US where trainers have this "training voice" where they speak slowly and articulated and usually non-skippable which makes me scream in agony. My brain can't slow down to that level, I just lose focus then. It's like driving a ferrari at 5km/hr. Especially the non-IT courses are so slow and constantly repeat everything, as if I didn't fully understand them the first time, argh. So I tend to spend my time on these awfully designed mandatory HR courses trying to fuck around in developer mode and re-enable the skip segment features :) The more boring the training the more I learn about moodle and its frameworks. I just love to dive right in and just do something but I often skip that first analysis of what method would be best. And I tend to stick with what I know. Which is often not the best way in a greenfield project. And often the boring first steps are so awful for me that I just put it off. If I do start I often do it half-assed. Then I run into a wall, have to regroup etc. I learn from that (mistakes are always a learing experience), but it's slow going because I take the wrong direction first. AI really helps me get past that first step meaning I actually start it instead of procrastinating the research forever and move onto the next thing. And I can do great things because I know what I want and how I want it. It's a real enabler for me especially something like cowork. It helps me widen my horizon efficiently instead of wasting my time and energy like online courses do. It picks up things that my weak points are (patience) and feeds me information in a highly dense format I can easily digest. Helped by custom prompts of course ("don't tell me I make great decisions, evaluate everything on its merits, just tell me the meat of the content, don't elaborate"). I still work along with it and take ownership of its output, I'm way too much of a control freak to let the AI do everything without understanding it. But it gets me there quicker and it avoids procrastination by skipping the boring steps. I ask it to suggest methods and techniques, compare their pros and cons so I fully understand what I'm selecting for. I have to say this was not really the case with early simple question/answer LLMs. The hallucinations were too bad, the searches too limited. The knowledge too hit and miss. It would come up with wrong stuff or overlook the best options. But the new high-context agentic technologies like cowork that really investigate the source material for the purposes I provide, they really are a game changer for me. For example, I recently asked it about an obscure error I'd been having. Previous simple LLMs would just collapse into a directionless troubleshooting mode, "Did you try...?". Cowork actually went and retrieved all the relevant code from github without being asked to do so, and evaluated what would have happened in the background for that message to appear. Really good to see because it's exactly what I would have done. But I would have taken much more time to do it. So no, for me it's not making me lose savviness. It's helping me grow it in exactly the way that's efficient for me.
titularcomment 28d ago
With all due respect, what you're describing doesn't quite spell learning in my opinion. Sure, its better to read the code of an application you envisioned to learn a programming language rather than an unrelated convulated program; but you're still offloading your thought process to the LLM. You're not quite seeing why it chose A instead of B, and why it uses that struct instead of the other. And honestly, the LLM doesn't quite know why it chose that either.
- phoghed 28d ago
  Nowhere did they say it’s learning. They said they can do more stuff now, it’s exploration.
  - titularcomment 28d ago
    The original article talks about 'savvy', which is to me an essence of learning. If 'exploration' is looking at walls of code you don't understand but the linter makes them look cool, you don't need LLMs for that.
    - Scubabear68 27d ago
      Who said I was "looking at walls of code [I] don't understand"? Really, you are reading a lot into this without context. I've been working software development for close to 40 years now. I've worked in plenty of languages, software stacks, ecosystems, from assembler to VAXen to Unix (pre-dating Linux), to cloud stacks to...well, a lot of systems. The software ecosystem has ballooned so tremendously in that time frame that no human can really be an expert in all of them, or even in a tiny subset of all of them. As I mentioned in another comment, I couldn't be bothered to keep up with the Javascript/Typescript/Web front end drama. I don't do rollercoasters, and that ride is enough to make even the staunchest stomach heave with distress from the endless loop-de-loops. With LLMs, I can describe a little problem unique to my problem space, inspect the output, research it and even reverse engineer it, and see how well it fits (or doesn't). This is not unlike being a software engineering manager leading teams. When I said being able to see the results was "cool", I did not mean or imply it was about me trying to "look cool". In fact, I really don't know where that is coming from. I do this for my day job and also on the side for a lot of different causes and personal projects, and no one could give a rats ass about how "cool" I am. Seriously. People need to stop taking this all so personally. It's a tool. Maybe you all need to step back to my world in 1981 when I first started playing with code as a kid, and compare it to 2016. The advances from '81 to '16 are probably far more dramatic than what AI is doing now.
jhhh 28d ago
I agree with the exploration aspect of AI. I don't have it create code for me but I have certain longer threads about topics that I think are interesting but would not have approached without it. Previously you would've had to find an entire textbook or class on a subject that may not have been quite what you were looking for if you were just interesting in poking around in a topic to start. Like I have a long running chat about making databases and WALs that I don't think I'd have started if I had to dive fully into a course on writing a database from scratch (if that even exists).
_the_inflator 27d ago
How large are your projects? What kind of? Just curious. No right or wrong answer possible.
duxup 27d ago
Being able to ask the dumb questions but then get focused on something more technical is so nice. Get examples on demand. It helps me pickup and understand new things pretty fast.
prewett 26d ago
It's great for stuff I don't care about, like figuring out complicated SQL queries, and then turning them into sqlalchemy! There's nothing so unfun as spending a day trying to get a complex query working, as you slowly discover more odds and ends about SQL than you ever thought it could ever possibly have. But if I end up feeding it JIRA tickets, playing agent management, and being QA on the other side, that's really not the job I signed up for.

grebc 28d ago

Is reading example code uncool?

Scubabear68 27d ago
I often find that example code never covers my use cases, and I am left scratching my head over nuances not covered there. With AI, I can describe my exact use case and see what it gives me. Sometimes it will just cough up a furball like a boilerplate example, but usually it gets pretty close, and I can see how my (maybe weird) edge case fits into the framework or API or whatever. It may be that I approach problems in a weird way, and that is why examples are less helpful than with some, but AI generally does better here for me.
- grebc 27d ago
  Examples are so because they’re just that. Nuance belongs in actual implementation. I guess what you’re saying is you like reading fully fledged code, almost like an apprentice. I would never think to delegate that responsibility to a next word guesser.

FinnLobsien 28d ago

I think the difference is that you read the code and get curious about it rather than glancing at the output and immediately telling it what to correct.

nemesis17 28d ago

I feel the same empowerment. LLMs allow me to tap into my second-order knowledge.

wolvoleo 28d ago

Same here. It really helps me get deep into things that would have been daunting to start due to the boring research work required. I have heavy ADHD and high intelligence (not to brag, it is often more of a burden than a blessing!) so I can understand things really quickly but I have no patience for painstaking research or planning and documentation. I just want to build, to create and make my vision come to life but I'm really one-sided about that. I don't care about how it fits in the organisation process, the governance or where it should be documented. And when I need to learn something new I hate doing courses because they're always too slowly paced for me. All courses are paced for the slowest possible participant. Especially those from the US where trainers have this "training voice" where they speak slowly and articulated and usually non-skippable which makes me scream in agony. My brain can't slow down to that level, I just lose focus then. It's like driving a ferrari at 5km/hr. Especially the non-IT courses are so slow and constantly repeat everything, as if I didn't fully understand them the first time, argh. So I tend to spend my time on these awfully designed mandatory HR courses trying to fuck around in developer mode and re-enable the skip segment features :) The more boring the training the more I learn about moodle and its frameworks. I just love to dive right in and just do something but I often skip that first analysis of what method would be best. And I tend to stick with what I know. Which is often not the best way in a greenfield project. And often the boring first steps are so awful for me that I just put it off. If I do start I often do it half-assed. Then I run into a wall, have to regroup etc. I learn from that (mistakes are always a learing experience), but it's slow going because I take the wrong direction first. AI really helps me get past that first step meaning I actually start it instead of procrastinating the research forever and move onto the next thing. And I can do great things because I know what I want and how I want it. It's a real enabler for me especially something like cowork. It helps me widen my horizon efficiently instead of wasting my time and energy like online courses do. It picks up things that my weak points are (patience) and feeds me information in a highly dense format I can easily digest. Helped by custom prompts of course ("don't tell me I make great decisions, evaluate everything on its merits, just tell me the meat of the content, don't elaborate"). I still work along with it and take ownership of its output, I'm way too much of a control freak to let the AI do everything without understanding it. But it gets me there quicker and it avoids procrastination by skipping the boring steps. I ask it to suggest methods and techniques, compare their pros and cons so I fully understand what I'm selecting for. I have to say this was not really the case with early simple question/answer LLMs. The hallucinations were too bad, the searches too limited. The knowledge too hit and miss. It would come up with wrong stuff or overlook the best options. But the new high-context agentic technologies like cowork that really investigate the source material for the purposes I provide, they really are a game changer for me. For example, I recently asked it about an obscure error I'd been having. Previous simple LLMs would just collapse into a directionless troubleshooting mode, "Did you try...?". Cowork actually went and retrieved all the relevant code from github without being asked to do so, and evaluated what would have happened in the background for that message to appear. Really good to see because it's exactly what I would have done. But I would have taken much more time to do it. So no, for me it's not making me lose savviness. It's helping me grow it in exactly the way that's efficient for me.

titularcomment 28d ago

With all due respect, what you're describing doesn't quite spell learning in my opinion. Sure, its better to read the code of an application you envisioned to learn a programming language rather than an unrelated convulated program; but you're still offloading your thought process to the LLM. You're not quite seeing why it chose A instead of B, and why it uses that struct instead of the other. And honestly, the LLM doesn't quite know why it chose that either.

phoghed 28d ago
Nowhere did they say it’s learning. They said they can do more stuff now, it’s exploration.
- titularcomment 28d ago
  The original article talks about 'savvy', which is to me an essence of learning. If 'exploration' is looking at walls of code you don't understand but the linter makes them look cool, you don't need LLMs for that.
  - Scubabear68 27d ago
    Who said I was "looking at walls of code [I] don't understand"? Really, you are reading a lot into this without context. I've been working software development for close to 40 years now. I've worked in plenty of languages, software stacks, ecosystems, from assembler to VAXen to Unix (pre-dating Linux), to cloud stacks to...well, a lot of systems. The software ecosystem has ballooned so tremendously in that time frame that no human can really be an expert in all of them, or even in a tiny subset of all of them. As I mentioned in another comment, I couldn't be bothered to keep up with the Javascript/Typescript/Web front end drama. I don't do rollercoasters, and that ride is enough to make even the staunchest stomach heave with distress from the endless loop-de-loops. With LLMs, I can describe a little problem unique to my problem space, inspect the output, research it and even reverse engineer it, and see how well it fits (or doesn't). This is not unlike being a software engineering manager leading teams. When I said being able to see the results was "cool", I did not mean or imply it was about me trying to "look cool". In fact, I really don't know where that is coming from. I do this for my day job and also on the side for a lot of different causes and personal projects, and no one could give a rats ass about how "cool" I am. Seriously. People need to stop taking this all so personally. It's a tool. Maybe you all need to step back to my world in 1981 when I first started playing with code as a kid, and compare it to 2016. The advances from '81 to '16 are probably far more dramatic than what AI is doing now.

jhhh 28d ago

I agree with the exploration aspect of AI. I don't have it create code for me but I have certain longer threads about topics that I think are interesting but would not have approached without it. Previously you would've had to find an entire textbook or class on a subject that may not have been quite what you were looking for if you were just interesting in poking around in a topic to start. Like I have a long running chat about making databases and WALs that I don't think I'd have started if I had to dive fully into a course on writing a database from scratch (if that even exists).

_the_inflator 27d ago

How large are your projects? What kind of? Just curious. No right or wrong answer possible.

duxup 27d ago

Being able to ask the dumb questions but then get focused on something more technical is so nice. Get examples on demand. It helps me pickup and understand new things pretty fast.

prewett 26d ago

It's great for stuff I don't care about, like figuring out complicated SQL queries, and then turning them into sqlalchemy! There's nothing so unfun as spending a day trying to get a complex query working, as you slowly discover more odds and ends about SQL than you ever thought it could ever possibly have. But if I end up feeding it JIRA tickets, playing agent management, and being QA on the other side, that's really not the job I signed up for.