If we build it, then it will frictionlessly tell us what to build.

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 reminds me of a segment I saw about 15 or 20 years ago on a show called "How It's Made" that played on a channel like the Discovery Channel (before all cable became reality TV).

The segment was "How CRTs are Made". I was kind of surprised that CRTs were still being made, but I was especially surprised by the fact that they appeared to be American workers in the factory. They were doing everything pretty much by hand with no automation, and they were making some rather skinny looking CRTs. The show never elaborated on what the CRTs were for, but they sure didn't look like TVs.

I dug into it a bit after that using some clues I noticed in the show, and found out that these were cockpit displays for F15s or similar military aircraft. It's probably an item that you just don't go changing the specs on, and they understandably aren't going to farm out to TCL. I can't imagine how much each one cost, though. And I certainly wouldn't try to rack it up as a "win" for any of GWB's or Obama's trade policies.

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'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.

Who's going to be able to scrounge up an extra 12KB of RAM in today's market?

It looks like if you can't beat 'em, join 'em.

You keep using that word in the narrow terms of a computer programmer who just finished a training course where they drilled in the technical meanings of "authorization" vs "authentication".

However, a news article for the general public is not constrained by that context. The dictionary says that "authorization" in general is permission to do something. If you prompt an AI to do one thing with your bank account, then you didn't give it permission to do something else entirely, even if it got the logon credentials to do so. It wasn't authorized by you to do the other thing.

Here's another example: It's wartime and you got drafted. Usually you're not allowed to kill people, but the government handed you a gun and you're now authorized to kill enemy soldiers. That doesn't mean that you can just shoot your comrade next to you in the trench. And you certainly can't make the claim "But I was authorized to shoot Corporal Smith. You gave me a gun, after all!"

Consider a human analogy: In many cases, people give financial advisors access to one or more of their accounts so that the advisor can make trades or other transactions for the benefit of their clients. However, if an advisor suddenly starts making transactions that do not benefit the clients or are contrary to their agreed instructions, then that activity is unauthorized, even if they have login credentials.

The DOD/DOW have been working on this for a while. They discovered, early on, that the device had a propensity to cause permanent nerve damage.

It's very unlikely the US have fixed that, as they'd largely sidelined the work as a failure. However, at 36%, Trump needs something he can call a win, no matter what the long-term consequences.

Yepp, as I said: The system is built first and foremost to defend itself.

Personally, I don't think that police should have any right whatsoever to enter your digital devices. Yes, including for terrorism and kiddie porn. And I am 100% for us nerds developing defenses against this overreach. This case is a lesson that teaches us distress PINs are a good thing, but we need to improve on them, make it less obvious they were used, etc.