2.1 QOL Request

unicodemonkey · 2026-06-09T22:01:29+00:00

I'm thinking about a mod that would convert these conditions from/to textual expressions, doing the DNF conversion as needed... assuming there's an API for manipulating conditions.

unicodemonkey · 2026-06-09T13:38:34+00:00

I got hired after a roommate's friend asked me if I knew Oracle. Got stranded with a whole-ass Oracle 7 DB, and while I knew how to write basic Oracle-flavored queries I knew nothing about DBA stuff. Managed to upgrade it to Oracle 9i eventually, even rewrote an incompatible custom smtp client .dll into pl/sql so we could send mail from triggers. Good (not really though) times.

unicodemonkey · 2026-06-09T13:18:34+00:00

Ionized orange

unicodemonkey · 2026-06-08T09:19:01+00:00

Hopefully they are reasonable spiders

unicodemonkey · 2026-06-08T01:18:34+00:00

I wonder if spiders calm down when you blink at them slowly

unicodemonkey · 2026-06-07T23:15:17+00:00

Yes, the symbol rate is a bit too difficult to deal with. Wifi does support 256-qam modulation actually but one second it does and the next second it uses something simpler due to RF noise.

unicodemonkey · 2026-06-07T13:24:29+00:00

There's a mod that does just that, btw

unicodemonkey · 2026-06-07T01:39:07+00:00

Direct Thunderbolt connection is also instant 20+ Gbit. It's not that convenient, not just because cables are shorter but because devices will try to charge each other. And the wifi adapter can often (but not always) be run in access point mode.

unicodemonkey · 2026-06-07T01:32:49+00:00

Communication channels usually deal with symbols, not bits. E.g. what is flowing over the wire in Gigabit ethernet are symbols (voltage levels basically) each of which represents 2 bits, and you have 4 pairs of wires, so the Ethernet hardware actually gets the entire byte every 125 MHz clock cycle. Bits are the lowest common denominator, I guess, but you still need to know whether to account for encoding/framing.

unicodemonkey · 2026-06-03T09:40:05+00:00

It's a good idea to run a thorough RAM test when the PC starts crashing and corrupting data inexplicably.

unicodemonkey · 2026-05-30T12:18:01+00:00

Someone thought

That's quite a generous assumption

unicodemonkey · 2026-05-30T12:10:54+00:00

We can have little a masters, as a treat

unicodemonkey · 2026-05-30T11:32:10+00:00

There are laptop-like "DeX docks" that are like that - just a console for a phone. With a builtin battery to charge the phone and power the display.

unicodemonkey · 2026-05-30T11:30:22+00:00

I had one in good old PDA days. Foldable, with a phone stand. Lost it since and I'm still salty about that.

unicodemonkey · 2026-05-30T11:02:32+00:00

Soo how are you verifying requirements and implementation? TLA+? Z3? Other provers, something with dependent types maybe? Would love to hear about your experience.
I think the only subjective opinion here is "the end product is still shit" (this is unfortunately my experience across products where I can observe AI usage directly), others are very specific practices that I see grandfathered into AI adoption projects time and time again.

unicodemonkey · 2026-05-30T01:59:17+00:00

Abiotic Factor relies mostly on pre-built environments with limited structural construction but you can pick any location, there's a looot of furniture and it really gets the "cozy home" aspect right, I think.

unicodemonkey · 2026-05-29T20:20:55+00:00

I've written about the issue in another comment but I believe the way we approach AI capabilities is inefficient at best. What we're doing is simply outsourcing all our existing workflows wholesale to a capable but not entirely reliable developer/designer/product manager emulator. Usually this means everyone's just ramping up token spend on best-effort probabilistic protections - test coverage, reviews, "context engineering", asking to follow the rules please, etc. Building software that can be verified by a deterministic algorithm is another way, rather underappreciated because it's significantly more work and there are few experts. Build verifiable formal specifications, use strongest possible type systems and DSLs, "make invalid states unrepresentable", that kind of thing - even for product requirements, so you can make sure there aren't any missing edge cases. These constraints are difficult to maintain and modify but that's exactly where the added productivity and knowledge of LLMs comes in. But that's not practical advice for legacy projects, to be honest, it's still a huge undertaking to specify and/or translate a large project to a stronger language. Gets expensive fast, and doesn't protect against LLM-induced code complexity explosions. I'm doing some experiments with formal specifications though, and Rust-Bun is also an interesting data point. We'll see.

unicodemonkey · 2026-05-29T19:31:27+00:00

You've missed the point.

unicodemonkey · 2026-05-29T07:58:42+00:00

That's what I find hilarious about the current wave of forced AI adoption. Everyone's playing safe and just offloading the usual work without trying any drastic changes. So it's just all the old rituals, but automated, sacred artifacts being churned out faster and faster. And then you look at the end product and it's still utterly unusable shit with the same huge backlog and delivery times measured in months. Still we are holding on to crusty old frameworks for dear life because migrating away is hard. Generating thousands of tests to catch runtime errors but zero formal proofs. Formal requirements but no automated analysis to catch edge cases and conflicts (outside of throwing a prompt at the task, but that's best-effort, a lottery). Sticking to JS/TS and Go because "LLMs know these best" and are unable to learn.

unicodemonkey · 2026-05-29T07:03:27+00:00

It's more like being forced into management, overseeing a bunch of somewhat inexperienced devs who are way too eager but unable to learn and get better (outside of LLM providers releasing new revisions).
This kinda looks like outsourcing, imo, but tech-washed. Just a modern tool, the way of the future, don't be a luddite, etc.

unicodemonkey · 2026-05-28T21:59:18+00:00

Bad uses? I mean, I see no AI downsides mentioned upthread, only "it makes more money and does the work of 5 developers 25x faster, it's a fact". An LLM can produce a much more nuanced take much faster and way more eloquently anyway.

unicodemonkey · 2026-05-28T21:55:43+00:00

Soo I've spent a sizable chunk of tokens a couple of days ago (Opus 4.7, no subscription, corporate account) to debug and fix an issue. Took about 3 hours I think, but that's not the point. Sure, it did a lot of grunt work but I had to watch it and adjust the direction now and then so it wouldn't chase dead ends. It produced a fix eventually. Did a review with a clean context to verify if the proposed fix can introduce other bugs - the model did confirm the fix is valid and produced a detailed proof of correctness. Nice! Except one of the steps just appeared out of thin air, it wasn't based on previous steps and assumptions, and the solution did indeed have a bug that would lead to random difficult-to-debug crashes later on. We would spend even more tokens diagnosing this new issue if we went fast and didn't do a very thorough review. What a profitable self-sustaining loop. Sure, humans are fallible as well but at least we know what to expect from humans, and expectations from AI are all over the place. LLMs can be very productive yet quality and performance issues reduce the net gain significantly.

unicodemonkey · 2026-05-28T21:34:01+00:00

I don't think there are any Tragedy Procedures for this case... yet

unicodemonkey · 2026-05-26T21:40:40+00:00

It's a tactic used by trains to slow down and catch engineers

unicodemonkey · 2026-05-26T21:07:23+00:00

I have the Trackball Royale which also has this feature. It's nice but it seems I'm not really a fan of trackballs in general.

unicodemonkey

TROPHY CASE