I've done some things

I was recently talking with our awesome UI/UX designer, Ilia, about a problem he was having with Perl. He mostly develops in JavaScript and web technologies, but his front-end obviously has to interact sometimes with the Perl in Webmin. And, sometimes he has to write some Perl, which is not an area he has had any experience with before working with us. Perl can be a tricky language for beginners to the language because of a few quirks that make it behave in seemingly bizarre ways.

We recently had an issue on a customer’s system where DNS wasn’t responding. In this case, the problem ended up being in “the last place I looked for it”, I thought I’d scribble down my thought process when troubleshooting BIND. This process looks similar for most network services, but I’ll be using BIND for this example. In this case, the user gave us literally no information to go on, other than “BIND isn’t working, there must be a bug in Webmin.

I try every new small model that comes along. At the very least, I’ll give it a run through my Nelson security auditing benchmark suite to see if the new thing can topple the current tiny model champs, Gemma 4 31B and Qwen 3.6 27B, which are very closely matched and punch well above their weight, defeating several much larger models. Poolside has released a few models, and I’ve tried Laguna XS.

The best way to buy AI inference is usually a subscription. It’s well-known that a $20 or $100 or $200 subscription from Anthropic or OpenAI is the most cost-effective way to buy access to their models, by far. One report said a $200 subscription could provide ~$9000 or ~$12000 worth of tokens at API rates from Anthropic and OpenAI, respectively. I haven’t done the precise math on this, but I have tried nearly every AI coding subscription now, as I subscribed to almost everything to run new benchmarks of security vulnerability auditing capabilities of the major models using their own preferred agent (the one made by the model vendor, like Claude Code, or one built for and seemingly having some kind of nod as being a preferred option, like Reasonix) as harness.

I don’t like the verbosity of AI models and I don’t generally like their prose. Some are better than others, some have better prose that makes it less annoying, some are less sychophantic, also less annoying. But, a universal trait of LLMs is they do go on. LLMs love to ramble and there’s very little we can do about it. But, I still try. My AGENTS.md contains the following, lifted directly from Strunk & White’s Elements of Style: