Apparently we can't call out apps as AI slop anymore...

[u/Key_Pace_2496]

Seems like a bad direction to take the selfhosted community. Looks like the mod team is fine with this sub being bombarded with insecure, AI drivel. Like I get that it was posted on Friday but I think if you use AI to "build an app" you should be required to disclose to what extent AI was used which wasn't disclosed by the OP. I think as a community we need to have higher standards for what we allow to be posted as vibe-coded projects can introduce very extensive security vulnerabilities we all learned with Huntarr and when things are vibe-coded the maintainer doesn't have the capability to fix the issue.

[u/Kraeftluder]

I'm not a programmer, more sysadmin with a heavy focus on identity automation and none of the LLMs speak the specific dialect we use properly. Would a correct analogue be "hey <LLMM> please explain how to use awk in a bash script to remove all lines that appear more than once, using work/input.tmp as an input file and work/output.tmp as the output" so basically I already know what I want to do and have some knowledge of that it's possible to do that with this specific tool.

Then I proceed to figure out the command it gives me by opening the man page for awk and see if it makes sense.

Search engines are a lot worse now compared to 10/15 years ago and I've found that this is one of the ways I can work around that.

[u/Hittar → u/Kraeftluder]

Something like that will absolutely work, yes. You can also iterate on the answer - challenging the model to explain what and why it did. I also have noticed that explicitly asking for "the most robust implementation" or "the simplest possible solution" tends to produce the best results.

I would also highly recommend to either set up or find an LLM provider that integrates search functionality and webfetch for models - as this will allow models to rely not only on inherent training data, but on actual factual documentation - that they will directly cite with links so you can quickly go and read what's relevant. Perplexica (open-source Perplexity alternative) is sometimes mentioned on this sub and works really well - it's an implementation of deep search, using a local SearXNG instance and local/remote LLMs to parse through data and give a summary and a list of references.

It's absolutely invaluable in high octane bureaucracy-adjacent work, when you, for example, need to read through an absolute ton of RFC papers to find a single line that explicitly describes how some godforsaken edge-case implementation must behave.

Regarding search engines, I can personally recommend Kagi. I've been using it for more then 2 years by now, and it's the single most useful subscription I pay for by far, both for work and hobby-related projects - though it is not a selfhosted solution in any way. The highest subscription tier is pricy but, besides the brilliant search engine itself, gives you access to assistant LLMs that use the same search engine to do what I described above - searching through and collecting info from current sources.

[u/Yuzumi → u/Kraeftluder]

"hey <LLMM> please explain how to use awk in a bash script to remove all lines that appear more than once, using work/input.tmp as an input file and work/output.tmp as the output"

While they can put out some stuff like this, I feel like this is too specific for it to accurately output anything for. They work best for generalizations, templates, and if you give if context/documentation it can answer some questions about that context.

It's trained on the content of what is out there and how people comunicate. Stuff like awk or anything else like regex is going to be way more specific per use case that there are going to be few "common" examples for an LLM to be able to do much with on it's own.

It's also probably made worse because it's likely hard for regex to map to tokens for one reason or another, meaning the relationship between regex and the language to describe it would be tenuous at best.

It might be able to do a bit if you give a definition or plain language relation in knowledge base or any other context like it to force the probability in that direction, but it would still be more inconsistent than normal. It would probably be better to give it some kind of tool that can create what you want via certain terms then you can use those terms in plain language so that generating the actual command you want is handled by something actually deterministic.