This is the one I have my eyes on, though I'd spend money if someone had packaged that with nice hardware for a complete set that I don't need to spend three days to set up.

Another thing that I have found Claude is really good at doing is taking an error from a log and doing a deep dive analysis of what happened. I give it read-only database access, access to www logs, access to application logs, access to a checked out source tree, etc. I paste in the error message (or in some cases paste in a tech support email from a user) and have it write up an analysis, a proposed response to the customer, and any recommendations (if there is a bug or actual problem).

Without buying into the conspiracy theory, but this is why I dislike these short lifetimes. It makes my otherwise 100% autonomous website dependent on an external party. I think I'll go back to also offer the site on unencrypted http instead of making an https redirect.

Though already CI/CD pipelines were choking on the unit tests. So they aren't *free*.

Had an LLM generated request that was pretty straightforward, and the LLM generated 272 unit tests for a very simple function. Can't really afford that.

Also, despite the 272 unit tests, when I tried to try it out in the way a human would, it immediately failed. All the mocking the AI generated never actually properly imitated the real world. However, the submitter was *quite* proud of having hundreds of unit tests, despite them being, in this scenario, utterly worthless.

Like always, more code != more valuable software behavior.

So you have the AI doing overtly silly things. Someone asked to adjust layout to fix a gap in a webpage. Eventually they submitted their pull request, hundreds and hundreds of lines of CSS. Often the exact same rule repeated 5 times, which I'm guessing is how many rounds the operator went with the system before the gap actually closed. The lines were *mostly* just '!important'ing already existing rules, which had no impact, but hey, worth a shot right? Ultimately I discarded the merge request and made the one-line css tweak that was actually relevant.

Then you have the AI doing... well arguably slightly silly things. Like protecting against an invalid value redundantly throughout a call stack. Arguably defensible, as maybe one day the deep function will be called from somewhere else and passing through the error might not present it with the most informative context.

Finally the AI doing... well things the human should have been doing. With the advent of a lot of code scanning, this is less likely, but things like calling functions in C and charging ahead without ever checking the status of the call. functions that, practically speaking, will likely never fail, however you really *should* be being more defensive about the possibility.

The 'human review as a bottleneck' isn't really the angle I would fixate on. Completely unfettered AI usage also stalls out in many situations. If the AI can't get there on its own trivially, then it's going to leave an almost-correct looking mess that isn't quite there but is very hard to get across the finish line. If the AI can get it, then it's probably not 'software being shipped', because while perhaps slightly better than a generic off-the-shelf existing procedure, probably not worth the trouble to 'ship' a solution that largely overlaps with a lot of generic stuff.

Everyone knows that pretty much by definition volumes are low, that's the whole definition of a shortage.

The vendors may still be happy, perhaps even happier if the sky high prices produce at least as much revenue at high margin.

I'm with you, but realistically speaking, if the mindset is already there, the material was likely already at high risk of plausible nonsense, not as thought out as the reality, but something to satisfy a check box for someone else. And the hope for process improvement is frequently not there, as raising a "do we really need to do this" invites "you must not care about safety/security/whatever". In many scenarios *no one* wants to be potentially on the hook for approving a process optimization that ends up biting them because they didn't understand why those things were in the process. Even if it is patently obvious to all involved there's no point, or if there was it was already failing. Frequently process dictated by someone that has no *real* stakes in anything involved, but needs to be performative.

The GenAI approach is the way to pay lip service and skip the debate. And if something messes up? "Ooops, well you know how AI just does that sometimes". I've seen that *so many times* and people just laugh it off and keep slopping and no one is holding folks accountable for failing to audit the AI results adequately. So they get credit when the slop works, and they deflect blame when it doesn't.

It *sounds* like they are using it for generating bureaucratic material.

Certainly comparatively speaking the stakes are just so much lower, but I've seen a bit of that in my company.

In my case, it's material that generally no one reads, or maybe someone that doesn't matter. GenAI has become a way for people to tick the checkboxes that they think don't matter without trying to debate the reason for the checkboxes.

Suppose the question is whether or not some token gesture facilitated by the GenAI *actually* matters but it's easier to "AI it away" than actually hash out that detail. Does it facilitate people who "I know what I'm doing, just let me do what I know is right" proceed without adequate and accurate oversight. Or is it the case that these situations were already ineffective at oversight, but effective at having whatever would have happened either way just happen in slow motion.

We measured the same thing: a hardware raid controller performed better software raided, and the vendor would tell us "were were measuring wrong, here is a super synthetic benchmark that is faster".

My best guess is that the hardware raid inevitably collapsed all the disks into a single IO queue, so workloads with independent IO could be more independently scheduled and serviced in software raid. Alternatively, the software stack has more visibility to the topology and can default to better aligned data layout without the user having to manually tune.

I wondered if, theoretically, the hardware raid could have done better abstracting it to an nvme target. Ultimately though, just not worth the hassle.

So some physicist that evidently doesn't understand a high school level logistic curve predicted the end of the world due to population growth.

Either it was stupid or it was satire, and sadly I can't really guess which is more likely.

No, not at all. The gender pay gap is in the training data thousands of times, from online comments, studies, news articles, etc. Since AI is a dumb machine replicating what it has in its training data, it replicates that.

I'm pretty sure you can find religious believe, superstitions of all kinds, human fallacies and whatever in AI if you provide it with the right setup.

This. No good game was ever created from a single prompt. Not to an AI, not a human development team. Every single person writing those damn "look which game my AI built from a single prompt and $x in tokens!" postings is a newbie and almost certainly has never actually shipped a single game.

Game development can be summed up as endless iterations. Every system you build, every visual you create, every sound, text, button, movement, weapon, skill, powerup needs polishing, refinement and changes. It is never, never good enough the first time.

No it is not, but it IS a very successful platform for a specific subclass of games. If I were in it for the money, I could probably AI refactor some of my earliest games and publish them on Roblox and make a quick buck. If your thing is the kind of games you played on your C64 back in 1793, then Roblox got you covered. Well, if you ignore the scams and money-grabbing.

*sigh* I wish Unity would actually complete some of their dozens half-finished sub-systems instead of constantly chasing the latest trend. It's become really, really annoying. The engine used to be really good. These days, it falls apart if you look at it the wrong way, and at least from the responses to my bug reports it's clear that fixing issues is way down on the agenda.

Maybe this is their attempt to regain grounds in the indie game market - the very market they pushed away by focussing on AAA requirements for years and ignoring the single devs and small teams. If so, I can already tell them that it won't work. We collectively laugh about all the "look what my AI built for me from a single prompt" postings on reddit, where people proudly show off some AI slop that would get them last place at a game jam.

Their AI efforts so far: Tried to build and sell their own AI tools, to a collective yawn from the audience. Built a barely-working MCP server, then deprecated it before it was even finished in order to push a CLI interface to the editor instead, which only works if it's run as the same user as the editor on the same machine. And completely ignores every single advise on workflows and good development practices you can think of.

Unity, I love your engine, I despise your management. Please return to when you were actually good and stop chasing butterflies.

The target audience for this particular rule of the AI Act isn't the producers or users of AI. It is the consumers of content that might be AI generated.

And frankly, letting people know if they see AI content or not is a fair thing to ask.