LLMs

My relationship with LLMs is much like smokers' with cigarettes: I know they're bad for me, and I'm not proud of using them, but I still reach for them when things get tough. Socially taboo (at least in hacker circles), but also universally accepted. (Despite this metaphor, I don't smoke.)

My own LLM usage#

For all of the research I've been doing for this garden and projects described herein, I've been making a conscious effort to avoid using LLMs.

I don't use LLMs to write code, because I don't trust their output enough to give them free reign, and I like to understand my code. I did use them for small snippets before, but I can count the amount of cases on the fingers of my hands.

(A part of this, I think, is also related to me not really knowing how to review code or work with other people - something I need to work on. But LLM output is a particularily insidious example, since the probabilistic weights machine knows how to be convincing, even if it's not right.)

I do, occasionally, use LLMs for code review. I've found that they're pretty good at spotting simple bugs, and in my kernel work, I've been able to have them compare the vendor driver with the mainline driver to see what is missing and what is implemented.

In kernel development use-cases, though, it greatly helps to have a proper understanding of the actual hardware. LLMs still tend to hallucinate and focus on the wrong problems.

I don't use LLMs for sysadmin work. I generally haven't had much luck with these topics - I've had LLMs hallucinate config options at me about 70% of the time I asked them for something.

Granted, the few times I tried using LLMs for that stuff, it was things that I couldn't find documentation on... which is something they struggle with. See my later point about “LLMs as a last resort”.

I do, occasionally, use LLMs for troubleshooting bugs. They make a pretty good talking rubber duck, though you shouldn't always take their advice at face value. I've had LLMs get me very close to the problem area, only to fall apart at finding the exact problem. I've had LLMs focus on the wrong thing, that I knew for a fact wasn't the issue. I've had LLMs miss the mark completely and give me advice that does not apply to my use case.

They really aren't kidding, your mileage does vary.

I do use LLMs for studying maths for uni, because I usually cram for exams only a short while before them, and need something that can explain a maths problem step-by-step quickly, and answer questions about my understanding, should any arise.

(I know some folks who tried to use LLMs for studying multiple times, and got bogus output every time. I seem to have lucked out (though much of that is because I primarily rely on sources from my lecturers (slides, etc.), rather than asking the LLM to generate everything for me.))

My approach to LLMs#

Generally speaking, I don't trust LLMs to generate correct content. I prefer to write/understand things myself, and only ask the LLM for pointers which I look up in other sources. I don't think that this is an infallible solution, because LLMs lie all the time.

Very often, I'll only throw a subject at an LLM if I'm completely stumped on it, which usually happens when:

• The documentation is tough to find or unreadable (unfortunately LLMs struggle with this even harder than I do, since they'll often just hallucinate things instead);
• There's too many things to look into and I don't know where to start (this is actually something that LLMs are good at, since they'll immediately throw a bunch of trustworthy-sounding keywords at you. I usually follow it up with a DuckDuckGo search (or grep the code if I'm asking about a particular project) for those keywords).

Using an LLM to power through code feels good in the moment, but it leaves me with a deep dissatisfaction afterwards. I think my brain is already fried enough as-is from the modern internet's attention-span-rotting design (not to mention other struggles with attention deficit and executive dysfunction), and I don't need another tool to deepen those problems.

Plus, there's already research linking AI usage to decreasing durable skill acquisition and/or cognitive decline. People who “vibecode” (that is, offload their code-writing to AI) describe burnout and feeling overloaded. I've witnessed this with my own friends who have fallen into heavy vibecoding, though I also have friends who only moderately use LLMs and seem to be doing fine.

I suspect if I started to rely on LLMs (that is, use them any more than I do now), I'd very quickly fall into vibecoding.

I prefer not to take the risk.

LLMs in open source#

A few thoughts on LLMs in open source projects:

• Using LLMs to respond to somebody's issues, be it on an issue tracker or support chat, is absolutely horrible and antisocial behavior. If I wanted to know what an LLM thinks about the subject, I'd just ask it directly. Wikis and support channels are for human help.
• Using LLMs to write code raises red flags for the quality of the projects for me, and for many others as well.
  • Vibecoded (fully written by AI) projects are something I avoid completely.
• Strangely enough, I don't particularily care about “licensing” concerns. I'm fine with my code being laundered through the LLM machine. I don't particularily care about the licensing of LLM output. I think copyright as it currently is should be abolished, and the anti-genAI movement is too pro-copyright.
• LLM policies are… tough. Just thinking about them makes my brain twist and turn. I think LLM code review is fine, but LLM generated code isn't. I think LLM translations are fine, but writing with LLMs isn't. A lot of policies either outright ban all forms of generative AI or go in the other extreme and embrace its usage (see AGENTS.md files).
  • At the end of the day, though, the purpose of anti-LLM policies is to scare off vibecoders, not to explicitly vet any and all potential AI-generated code, but it still feels heavy-handed. My personal policy is this: if you consider yourself a vibecoder, AI engineer or similar, the communities I'm in are probably not for you. If you brag about LLM usage, I'll think you're lame. If you just occasionally use genAI as a helper (like I do), I don't really care.