I don’t have ai psychosis myself but man did Claude Code make it easy to see how people could develop it. I guess it makes sense too considering humans thought ELIZA was intelligent. My employer does some AI stuff and I think it just took me a while to understand how these LLMs appear to people outside that sphere.
There were some last year specifically for games on SteamOS vs Windows, like this: https://arstechnica.com/gaming/2025/06/games-run-faster-on-steamos-than-windows-11-ars-testing-finds/
Even that is just confusing. I sometimes use Perplexity (because Pro comes with my bank account - neobanks have zero focus). And by default it remembers things you say. So when I ask a question sometimes it will randomly decide to bring in something else I asked about before. E.g. I sometimes use it to look up programming related stuff, and then when I ask something else it will randomly research whatever language it thinks I like now in that context too and do things like suggest an anime based on my recent interest in Rust for no good reason.
Tbh I think the Sun Ray thin terminals were pretty cool at the time. Not really cloud because it was an enterprise product 20 years ago, so they used servers hosted by the enterprise. But at the time this idea of taking my entire desktop session with me via my employee badge felt pretty cool. Of course only supporting X11 sessions on Solaris meant that nobody outside Sun wanted it though but that’s not really a problem with the concept as such.
In October 2025, so much later.
Yeah, it’s a major pain at my work because our cloud doesn’t support Macs (like e.g. AWS would), so we run a server room with a bunch of Macs that we wouldn’t otherwise need.
You could also just only use Macs. In theory ARM Macs let you build and test for macOS (host or vm), Linux (containers or vm), Windows (vm), iOS (simulator or connected device), and Android (multiple options), both ARM and x86-64.
At least in theory. I think in practice I’d go mad. Not from the Linux part though. That part just works because podman on ARM Macs will transparently use emulation for x86 containers by default. (You can get the same thing on Linux too with qemu-user-static btw., for a lot more architectures too.)
Damn you’re running a whole production pipeline and it only takes two minutes? That’s pretty good. I’ve worked with projects that take tens of minutes, if not hours, just to compile.
At work we have CI runs that take almost a week. On fairly powerful systems too. Multiple decades of a “no change without a test case” policy in a large project combined with instrumented debug builds…
Tbf we don’t run those on every single change though. The per change ones take a couple hours only.
I’m not sure I’m on board with this “fewer CVE’s reported means the product is more secure” logic in this article…
Due to the blank between Harada and TEKKEN, the title reads like he said TEKKEN as he imagined it is dead, but what he actually wrote is his X handle (with the underscore), so he’s talking about himself.
I have written code this holiday, but I was afk on vacation for a month in November. That was a good reset too. But tbh I like programming, the reset is more for the other circumstances of my work.
I was surprised how many of these I’ve actually done at some point in the last 35 years.
scopeguard would be one way to get defer in Rust
In Rust you’re kind of stuck with it, but at the end of the day combined return types are just syntactic sugar for something a lot of languages can do. Even in plain old C there’s a pattern where you pass pointers to your return and/or error variables. In many languages you can return structs or similar. In some I’d argue it looks nicer than having to write Result<>, e.g. in Python or in Swift you can just return a tuple by putting things in parentheses. (Of course you can also still use something more explicit too. But if every function returned (result, error) by default and every call was like result, error = fn(), I don’t think it’d be necessary.)
However I don’t really know of any language where people prefer to use this over exceptions if exceptions are available. Even in C some people used to use setjmp/longjmp in macros to implement exceptions. Exceptions have their problems but people seem to overwhelmingly be in favor of them.
Personally I like exceptions in languages that have some kind of built-in “finally” for functions. For example defer in Swift. You can have proper error handling for a lot less typing in many cases because passing through exceptions is fine if your defer blocks handle the cleanup. And if you do want to handle an exception, Swift also has optionals, and a try? that transparently converts a return value into an optional that’s nil when an exception was thrown, and a coalescing operator ??, which means you can catch exceptions and provide a default value on one line, instead of a 4-5 line try…catch/except block or an error checking conditional for every call.
Well that’s true too. As humans we should generally aim to be more cylindrical than spherical.
Well politicians doing politics isn’t getting us anywhere so I’m open to alternatives
The video conferencing platform my work uses works well because it’s a large well-known platform and they punched holes for it into the firewall and the vpn. Not really something a service provider can just replicate.
They could do what Apple did when they replaced the old MacOS with UNIX, which is they shipped an emulator for a while that was integrated really well. They also had a sort of backwards compatible API that made porting apps a bit easier (now removed, it died with 32 bit support).
But in the Windows world, third party drivers are much more important. So in that regard it would be more difficult. Especially if they’re not fully behind it. As soon as they waver and there is some way to keep using traditional Windows, the result will be the same as when they tried to slim down the Windows API on ARM, and then nobody moved away from the APIs that were removed because they still worked on x86, which significantly slowed adoption for Windows on ARM.
It depends on the task. As an extreme example, I can get AI to create a complete application in a language I don’t know. There’s no way that’s not more productive than me first learning the language to a point where I can make apps in it. Just have to pick something simple enough for the AI.
Of course the opposite extreme also exists. I’ve found that when I demand something impossible, AI will often just try to implement it anyway. It can easily get into an endless cycle where it keeps optimistically declaring that it identified the issue and fixed it with a small change, over and over again. This includes cases where there’s a bug in the underlying OS or similar. You can waste a huge amount of time going down an entirely wrong path if you don’t realize that an idea doesn’t work.
In my real work neither of these really happen. So the actual impact is much less. A lot of my work is not coding in the first place. And I’ve been writing code since I was a little kid, for almost 40 years now. So even the fast scaffolding I can do with AI is not that exciting. I can do that pretty quickly without AI too. When AI coding tools appeared my bosses started asking if I was fast because I was using one. No, I’m fast because some people ask for a new demo every week. Causes the same problems later too.
But I also do think that we all still need to learn how to use AI properly. This applies to all tools, but I think it’s more difficult than with other tools. If I try to use a hammer on something other than a nail, it will not enthusiastically tell me it can do it with just one more small change. AI tools absolutely will though, and it’s easy to just let them try because it’s just a few seconds to see what they come up with. But that’s a trap that leads to those productivity wasting spirals. Especially if the result actually somehow still works at first, so we have to fix it half a year later instead of right away.
At my work there are some other things that I feel limit the productivity potential of AI tools. First of all we’re only allowed to use a very limited number of tools, some of them made in-house. Then we’re not really allowed to integrate them into our workflows other than the part where we write code. E.g. I could trivially write an mcp server that interacts with our (custom in-house) ci system and actually increases my productivity because I could save a small number of seconds very often if I could tell an AI to find builds for me for integration or QA work. But it’s not allowed. We’re all being pushed to use AI but the company makes it really difficult at the same time.
So when I play around with AI on my spare time I do actually feel like I’m getting a huge boost. Not just because I can use a claude model instead of the ones I can use at work, but also just basic things like e.g. being able to turn on AI in Xcode at all when working on software for Apple platforms. On my work Macbook I can’t turn on any Apple AI features at all so even tab completion is worse. Or in other words, those realities of working on serious projects at a serious company with serious security policies can also kill any potential productivity boost from AI. They basically expect us to be productive with only those features the non-developer CEO likes, who also doesn’t have to follow any of our development processes…
The bubble thing is more the financial aspect. None of these AI companies are profitable and they also don’t have a clear path to profit. For some time the business plan of Open AI was literally develop advanced AI and then let the AI figure out how to make money. Yet, these companies attract huge amounts of investment and are responsible for basically all of the economic growth in the US.
Nobody thinks there are no uses at all for LLMs or image generation etc. or that people in general hate all AI. It’s a bubble because a lot of money is being invested in something that nobody managed to make profitable yet, so if the investment stops, then these companies will all implode.