[icepat]

I agree. I use LLMs heavily for gruntwork development tasks (porting shell scripts to Ansible is an example of something I just applied them to). For these purposes, it works well. LLMs excel in situations where you need repetitive, simple adjustments on a large scale. IE: swap every postgres insert query, with the corresponding mysql insert query.

A lot of the "LLMs are worthless" talk I see tends to follow this pattern:

1. Someone gets an idea, like feeding papers into an LLM, and asks it to do something beyond its scope and proper use-case.

2. The LLM, predictably, fails.

3. Users declare not that they misused the tool, but that the tool itself is fundamentally corrupted.

It in my mind is no different to the steam roller being invented, and people remaking how well it flattens asphalt. Then a vocal group trying to use this flattening device to iron clothing in bulk, and declaring steamrollers useless when it fails at this task.

[replyifuagree]

>swap every postgres insert query, with the corresponding mysql insert query.

If the data and relationships in those insert queries matter, at some unknown future date you may find yourself cursing your choice to use an LLM for this task. On the other hand you might not ever find out and just experience a faint sense of unease as to why your customers have quietly dropped your product.

[babyent]

I hope people do this and royally mess shit up.

Maybe then they’ll snap out of it.

I’ve already seen people completely mess things up. It’s hilarious. Someone who thinks they’re in “founder mode” and a “software engineer” because chatgpt or their cursor vomited out 800 lines of python code.

[actinium226]

Probably better to have AI help you write a script to translate postgres statements to mysql

[icepat]

Right, which is why you go back and validate code. I'm not sure why the automatic assumption that implementing AI in a workflow means you blindly accept the outputs. You run the tool, you validate the output, and you correct the output. This has been the process with every new engineering tool. I'm not sure why people assume first that AI is different, and second that people who use it are all operating like the lowest common denominator AI slop-shop.

[snackernews]

In this analogy are all the steamroller manufacturers loudly proclaiming how well it 10x the process of bulk ironing clothes?

And is a credulous executive class en masse buying into that steam roller industry marketing and the demos of a cadre of influencer vibe ironers who’ve never had to think about the longer term impacts of steam rolling clothes?

[freedomben]

> porting shell scripts to Ansible

Thank you for mentioning that! What a great example of something an LLM can pretty well do that otherwise can take a lot of time looking up Ansible docs to figure out the best way to do things. I'm guessing the outputs aren't as good as someone real familiar with Ansible could do, but it's a great place to start! It's such a good idea that it seems obvious in hindsight now :-)

[icepat]

Exactly, yeah. And once you look over the Ansible, it's a good place to start and expand. I'll often have it emit hemlcharts for me as templates, then after the tedious setup of the helm chart is done, the rest of it is me manually doing the complex parts, and customizing in depth.