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I'm dialing back my LLM usage

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Re: I'm dialing back my LLM usage

#241

Post by nativeit »

antonvs wrote: post #185
ymyms wrote: post #173

Earlier quoted context omitted.

One of my favorite ways to use AI is to get me started on things. I tend to drag my feet when starting something new, but LLMs can whip up something quick. Then I look at what it did and usually hate it. Maybe it structured the code in way that doesn't mesh with the way I think or it completely failed to use some new/esoteric library I rely on. That hate fuels me to just do the work myself. It's like the same trick a…

I do the same thing, except if I hate something, I just ask the LLM to fix it. I can usually get to a starting point I'm pretty happy with, then I take over. After that, I may ask an LLM to write particular functions, giving it data types and signatures to guide it.

Does this sound like a fulfilling career to literally anyone?

Re: I'm dialing back my LLM usage

#242

Post by danielbln »

jeremyjh wrote: post #175
gtsop wrote: post #169

Earlier quoted context omitted.

So is the expectation for it to suggest obvious solutions that the majority of people already know? I am fine with this, but let's be clear about what we're expecting

All it can do is predict the next token. So, yes.

If it's still 2020, then yes. In 2025 post-training like RLHF made it that these models do not just predict the next token, the reward function is a lot more involved than that.

Re: I'm dialing back my LLM usage

#243

Post by careful_ai »

Too many of us fall into “prompt autopilot” mode—reaching for AI before we think. Your post calls it out beautifully: step back, reclaim the muscle memory of creative problem solving. LLMs should supplement, not substitute. That discipline often separates thoughtful integration from dependency.

Re: I'm dialing back my LLM usage

#244

Post by seanw444 »

rane wrote: post #207
seanw444 wrote: post #4

This is pretty much the conclusion I've come to as well. It's not good at being an autocomplete for entire chunks of your codebase. You lose the mental model of what is doing what, and exactly where. I prefer to use it as a personalized, faster-iterating StackOverflow. I'll ask it to give me a rundown of a concept I'm not familiar with, or for a general direction to point me in if I'm uncertain of what a good solutio…

I don't have this experience. The mental mode might not be quite as strong, but if you always review the code given carefully, you will have a good pretty idea what is where and how things interact.

It seems to be analogous to just reading a concept, versus reading a concept and taking notes on it to solidify it further. Writing the code myself helps it all solidify in my brain.

Re: I'm dialing back my LLM usage

#245

Post by antonvs »

nativeit wrote: post #241
antonvs wrote: post #185

Earlier quoted context omitted.

I do the same thing, except if I hate something, I just ask the LLM to fix it. I can usually get to a starting point I'm pretty happy with, then I take over. After that, I may ask an LLM to write particular functions, giving it data types and signatures to guide it.

Does this sound like a fulfilling career to literally anyone?

I’m enjoying it - I wouldn’t be doing it otherwise. Perhaps you misunderstood me - I’m using it to automate things that are easy enough to do but time-consuming and generally uninteresting. It’s a useful assistant.

You could make the same comment about managers - does management sound like a fulfilling career to literally anyone (to some, it doesn’t!) Or about working on a team, where colleagues do work that you depend on.

It’s also very similar to the situation with compilers and interpreters for high level languages. An assembly language or machine language programmer might ask “does writing in a high level language sound like a fulfilling career to literally anyone?”

This all makes me suspect that your comment is coming from a place where you’ve already reached a conclusion and are now looking for excuses to justify it. Typical change resistance, essentially.

Re: I'm dialing back my LLM usage

#246

Post by sunrunner »

exceptione wrote: post #237
sunrunner wrote: post #176

Earlier quoted context omitted.

Okay, so you didn't even bother to take a few seconds to step through the video to see if there was anything other than the talking head (I'll help you out a bit, there is). Either way, it's a step-by-step walk through of the ideas of the original article that introduced Conway's Law and a deeper inspection into ideas about _why_ it might be that way. If that's not enough then my apologies but I haven't yet found an…

(I didn't downvote you btw) But anyways, I did step through. And even in the section he should make his point, he couldn't. I rage quit this stuff. Don't take it personally, you might have found great insight from it. But if you want to see my POV: I can scan, like most humans, a large text in seconds, processing it with a massive parallel network. When I find an anchor of interest, I can scan around for more context…

(I also didn't, despite the sentiment ;) )

That's completely fair, and I actually completely agree about the information density thing. I honestly prefer well-written concise documentation over tutorial videos for this same reason, however I've not yet found the equivalent text form of this video yet (automatic transcription aside) so it's really the only example I've got that seems to extract some of the most salient points from Conway's paper and puts forward an idea as to _why_ this phenonemon is. Perhaps a blog post in the making.

Re: I'm dialing back my LLM usage

#247

Post by KoolKat23 »

ymyms wrote: post #173
jm4 wrote: post #120

Earlier quoted context omitted.

I think you described it much more succinctly than most people do. It's been my exact experience as well. The LLM can develop much faster than I can build a mental model. It's very easy to get to a point where you don't know what's going on, a bunch of bugs have been introduced and you can't easily fix them or refactor because you're essentially the new guy on your own project. I find myself adjusting by committing c…

One of my favorite ways to use AI is to get me started on things. I tend to drag my feet when starting something new, but LLMs can whip up something quick. Then I look at what it did and usually hate it. Maybe it structured the code in way that doesn't mesh with the way I think or it completely failed to use some new/esoteric library I rely on. That hate fuels me to just do the work myself. It's like the same trick a…

Breaking writers block, it's a starting point.

Re: I'm dialing back my LLM usage

#249

Post by billbrown »

The use case for LLM assistance that provides value for me is solving obscure lint or static analysis warnings and errors.

I take the message, provide the surrounding code, and it gives me a few approaches to solve them. More than half the time, the resolution is there and I can copy the relevant bit in the literal verbiage. (The other times it's garbage but at least I can see that this is going to require some AI—Actual Intelligence.)

Re: I'm dialing back my LLM usage

#250

Post by Anamon »

koonsolo wrote: post #235
x187463 wrote: post #11

Am I spending too much time on HN or is every post/comment section filled with this same narrative? Basically, LLMs are exciting but they produce messy code for which the dev feels no ownership. Managing a codebase written by an LLM is difficult because you have not cognitively loaded the entire thing into your head as you do with code written yourself. They're okay for one-off scripts or projects you do not intend t…

I use LLM's for my developments constantly, so I have a pretty good grasp of what works and doesn't work. Github copilot really gets it, as in: it's a "co-pilot", and you are the "pilot". LLM's are able to generate code way faster than me, so in a lot of cases, writing a prompt, letting the LLM's generate a diff and me quickly reviewing, is faster than me writing/shuffling all the code. This is basically a "I know wh…

"Also an observation: once the LLM gets it wrong, it will continuously get it wrong"

Oh yes, so very very much! I often see people keep iterating, not just with coding assistants but also general knowledge or research queries, when the first response is obviously wrong. I don't think that has ever ended up in a better response down the line. If the first response is garbage, then that means garbage is all this particular LLM is able to give you in return for what you ask. All the iterating does is travel through randomland - often until the person doing the prompting gets a response which they, for some reason, find more acceptable, even if it's just as wrong as all the others.

Don't give LLM second chances.

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