You missed the point.

A friend of mine made a tea-timer app for the iPhone. Where you enter what tea you are making and it sets the correct number of minutes. Today, people would ask ChatGPT before they go on the App Store to search for something like that. That's the point. Not what YOU would do, but what the general public does. And for Jane Doe, ChatGPT has replaced a lot of these specialty apps.

Skills are great until they aren't. The problem is exactly what you say: You can literally create a skill by telling the LLM to create a skill. Which is... why the f do I need to make a skill if the AI already knows how to do it?

Properly created skills, that include reference material, specific instructions, and expert knowledge the LLM doesn't have or that's buried somewhere under 10 layers of reddit posts is genuinely useful. But most skills aren't. I'm constantly underwhelmed by hyped-up skills that, when I look at them, turn out to be bland, basic instructions.

This seems like a great pick if you want to be absolutely sure that your computing stays between you, the techbros, republican loyalists in 'national security'; and possibly an Israeli software partner or two.

At least no chicom lithium stealing your thoughts.

"with some employees complaining about issues with style, paragraph formatting, blank pages, and challenges with tracking changes." sounds like they got the replacement they were looking for to me.

That's why it's on Slashdot. High value thefts are increasing but most are by traditional methods. Fraudulent pickups and carrier impersonation are simple, easy and allow ample time to unload cargo.

Value rose ~725 million dollars for 2025 so a drop in the economic swimming pool. That's hardly impressive in an economy the size of the US.

High value load tracking and hiring private security guards will be natural responses.

Reddit drama is hardly "news" and but does drive monetizable view counts. Posting reddit drama on Slashdot drives views because Slashdot is a general news site.

Ideological communities are prone to infighting because humans enjoy competing virtue displays. Weak communities will render themselves irrelevant. Effective communities will thrive. Water is wet.

Where AI proves sufficiently useful it will be used but there is no need for everyone to use AI.

But again that's backwards. I let my AI coding assistant write tests exactly so that I have a reproducible, deterministic ground truth that I can inspect for logic errors. If you let the AI do the testing directly, it's a toss-up if today it feels like it or it decides that your desired result is "everything green" so it'll just give you that answer without actually testing anything.

LLMs obviously aren't human. But that's not the point. The point is that you don't need to know a programming language to program a computer.

For example: Especially in the early days of smartphones, there were mountains of small tools that did something that's essentially a simple script. Egg timers, remind-me-tomorrow apps, tons of stuff that's basically a wrapper around a web search, and so on. Almost all of those are today something ChatGPT can do, and are easy enough to describe.

I didn't mean to imply that it is a single monolithic application, it does consist of several, but the relations must be pretty tight for there to be an article not even about language-independence; but about support for a single additional language, one often targeted by "C but cleaned up" efforts,

I was honestly surprised to see this myself. Regardless of its reputation for being more monolithic than classic init systems it still is, and has to be, capable of interacting with basically any flavor of service you'd want a service manager to manage; and I would assume that it doesn't include a d-bus implementation in order to not be capable of abstracted inter-process communication.

No doubt there are considerations at work here that I'm not smart enough to grasp; if you aren't having a bad time handling x.509 certificates you probably aren't doing it carefully enough; but I would not have expected it to be remarkable at all for a certificate-wrangling component to be implemented in a different language than some of the other components.

I assume that this is more pragmatic than just waiting for Sam to finish lying about transcendent AGI; but it feels a little dissonant to have the botmongers going back and forth between praising the glorious natural-language suitability of their progeny and putting together an entire platform, with more apparent effort than they have dedicated to human UI/UX considerations since sometime in win7(excluding dark pattern R&D) to aid you in discovering your sins against bot comprehensibility and fixing them.

I've actually outsourced the first iteration of that to AI. :-)

At the end of coding sessions, I generall ask it to spin up an adversial agent whose task it is to find flaws, inconsistencies, mistakes, bugs, etc.

I'd still strongly recommend to anyone shipping AI-generated code to have a thorough human code review, but for a first pass at surface level, the AI can check itself if it has some kind of separation between the generator and the reviewer.

Personally, after some experimenting, I've concluded that:

• AI is good at implementing known algorithms.
• AI is good in creating code that flows straightforward from a design document.
• AI is good at code reviews and finding bugs.
• AI (unlike me) doesn't mind writing a few hundred tests.
• But, it tends to over-engineering simple tasks to the point of "why does Hello World need enterprise-software levels of abstraction?"
• It struggles with code that doesn't have a known solution.
• It's difficult to get it into a different lane once it started going down the wrong way.

What I use it for these days is rapid prototyping. Using AI I can make a functioning prototype of an idea I have in a few days instead of a few weeks. I can quickly test out an idea for a feature or change in my existing codebase.

What I also have been using it for a while is as a code-reviewer and for someone like me who is mostly working solo, that's an insanely valuable thing. Not just the bugs themselves, but also the ability to discuss code with someone. Basically, AI is a rubber ducky that replies.

Mickeysoft lost the plot again.

The game-changing element of LLMs and agents is that they have a non-computer-language interface - you can talk to them in plain English (or Chinese or whatever). This makes complex computer interactions available to a much wider audience than any previous computing invention. Adapting humans to the AI is getting that backwards. It's a sign you don't understand the first thing about why AI is so widely successful.

I predict this will be an abject failure and a year from now will quietly be pushed to the very back of the bottom-most drawer, never to be spoken off again (though it is getting crowded in there for M$).

Meanwhile, in the real world, everyone I've talked to about these things already has a skills file to teach the AI about their personal coding style. This is what actual humans came up with, independently several times, and it works: Adapt the AI to you. Plus we've been writing coding style guides for humans for a long time now, we've got plenty of experience doing that at least somewhat right.

I'm not really qualified to deliver a good holy war; but it does seem like there may be something to the criticism that monolithic integration has gone a bit far if supporting one utility being written in a different language is a special feature rather than a matter of the rest of the system not knowing or caring what is on the opposite side of an interface so long as it can act as expected.

You can't really beat the fundamental economics of software development: expensive to do right but cheap to copy means that you really, really, want to share a problem with as many other people as possible(unless your whole business is being uniquely good at solving whatever the problem is; but that typically isn't the case for this sort of software). Applies to both proprietary and FOSS: relatively mass-market software is often pretty cheap for what you get; really oddball niche stuff is frequently both pricey and terrible; while your life is going to get steadily more miserable if you are personally responsible for handling backports and fixes for some internal fork of a long-EOL version of an OSS package.

The big difference, at least potentially, is that, while it tends not to be economic to DIY, licenses that give you the right to DIY also give you the right to pay someone else to do it for you; or to form a coalition of people with similar problems and have everyone pitch in to pay someone to do it for you. You still need to either eat the cost of maintaining an internal fork or putting together some sort of coalition of people with similar problems to be the openJDK 8 forever pals and share the cost of maintenance; but the vendor can't just stop selling you licenses if they want you to move to their cloud offering or whatnot.