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The way I see it is AI collapses hierarchy. Abstraction layers will become more flat both in software and in society. Because ultimately software and layers of

• yoz-y 26d ago
  I am honestly _astonished_ that the current crop of agents are not all written natively for every platform. I tried porting a moderately complex workout app that I’ve built over years (and which includes a whole agentic loop) from web to iOS native. It took me a couple of evenings. There is now no excuse to not offer a native experience for every supported platform when you are a bigger company. Make one of the platforms using good coding practices. Vibe code the others from the source using a proper test battery.
  • piker 26d ago
    Because it’s too complex and not worth the effort. Most users will not care about or perceive the benefit. If they delegate that responsibility to Google via Electron, they can focus on features/bug fixes that move the needle.
    • yoz-y 26d ago
      What effort ? I’ve started seeing this attitude more and more. We had a thing that took a week to do before. Now it takes a morning. So we refuse to spend half a day polishing it because it’s too annoying. Once the initial port is done, keeping platforms in sync is fast. Not to mention that a harness that would automate this would be valuable. I run codex on an old rpi, it eats 190M of ram for what essentially is a telnet client.
      • piker 26d ago
        You're mistaken if you think it has ever taken a week to port (and support) an application to native primitives.
        • simianwords 26d ago
          ?? Bun rewrite?
          • deleted 26d ago
            [deleted]
    • pydry 26d ago
      This isnt how a company which has "solved programming" would act. Especially since users do prefer a native experience and having their RAM conserved.
      • raincole 26d ago
        This is exactly how a company would act when they notice millions of people downloading and using their ram-hungry electron app. There is just no reason to not act this way.
    • weiran 26d ago
      Also the part people forget is the significant coordination cost of having multiple teams work on multiple native codebases. I hate Electron apps with a passion, but I can understand why the AI companies are using it.
  • testdelacc1 26d ago
    I have a question about web to iOS native. How do you distribute that app? I’m assuming you’re paying $99 yearly to distribute through the App Store? Is this app meant just for you or for anyone to find? Reason I’m asking is because I’d like to make native iOS apps just for myself rather than progressive web apps. But I haven’t understood the best way to distribute.
    • kolinko 26d ago
      If just for yourself, get an Apple Dev account and use TestFlight
      • testdelacc1 26d ago
        Do I need to upload a new build of the app every 90 days? I’d prefer the app to just work forever without thinking about it.
        • weiran 26d ago
          You need a paid dev account for that. I think self signed installs can run for a year.
      • pprotas 26d ago
        Or just build and deploy to your iPhone from XCode. No need for TestFlight or paying money for a dev account.
    • yoz-y 26d ago
      Just for myself and friends. Using local deployment and internal TestFlight.
  • lelanthran 26d ago
    Could be that models are not yet at the point where they are able to write code as well as we think they can. I mean, there's a limit on the complexity of a phone workout app, but almost unbounded complexity in even simple business apps.
  • novok 26d ago
    If you actually try to implement the same app in multiple platforms from the same spec, you'll notice very quickly that AI makes the best quality UIs out of typescript electron or direct web. It accomplishes it's task the fastest, with the least lines of code and with the least bugs. Also hot patching updates works best with web. And I say this as a person who isn't a web dev, but a mobile dev. This is why. AIs are also really good at translating one complete app from one language to another where nothing changes. You'll also notice that new features will be implemented better in typescript web than iOS going further. I think this is why OpenAI changed their native swift chatgpt desktop app into web electron too.
    • yoz-y 26d ago
      As I said. I did a large migration from a PWA to iOS, with a pretty custom UI. It took a while, but it only took days. A full rewrite would be months of work the old way.
• musically_ut 26d ago
  There are two forces here and they point in opposite directions. I wrote about this a few months ago: https://blog.musicallyut.xyz/2026/06/02/the-mote-in-ais-eye.html https://blog.musicallyut.xyz/2026/06/02/the-mote-in-ais-eye.... The one you're describing is the pull down. The AI doesn't need the library as a comprehension aid, so it drops a layer and writes the ten lines it actually needs. There's a second reason it might do this: it doesn't trust code written by other AIs, and pulling the functionality in-house shrinks the surface area it has to reason about. But there's also a pull up. Writing code is getting cheap; making it hardened may not, and that gap doesn't close just because token prices do. If that holds, the economical arrangement is that someone (OSS or SaaS) ships vetted blocks and each user grows their own feature layer on top with their own agent. Which means the stack gets taller rather than flatter. The top layer is bespoke per user instead of shared, and the bottom layer matters more, not less, because everyone is depending on the same small set of audited pieces.
• mcrk 26d ago
  > Now not anymore you just need to tell the LLM and it does it in both, and you get better results too. That's weird I just asked fable to build airbnb app clone and it didn't do a good job. Am I using the wrong model?
  • onion2k 26d ago
    That probably means Fable doesn't have enough understanding of what AirBNB is in order to build a clone. If you think about it, people don't really write much about how an app like that actually works. They write about the impact on travel, the impact on property prices, how to use it to book a vacation, and a bit about how it's a two-sided market place app, but not so much about what it actually does. I assume that Fable has no access to it apart from the listing pages so it can't see behind the scenes to the property management side or the AirBnB admin stuff. The code isn't open so Fable isn't learning from that. There's probably a bunch of clones on Github but quality will vary. If you want a clone of an app like that you'll need to build a large amount of context first, and even then you'll probably miss a lot.
• totetsu 26d ago
  Or it actually entrenches hierarchies.. and it's just that so many CS majors got caught up in the discursive pleasure of poopooing social sciences that they don't actually have a good graspe on how power operates in society..
• Xirdus 26d ago
  Maybe not all AIs, but LLMs benefit immensely from abstraction. They are trained on human code, and human code usually uses very high abstraction - so high abstraction is overrepresented in training data compared to low level implementations. It also drastically reduces number of tokens, and that has downstream effect of better utilization of context window and whatnot. We are not yet at the point where AI can use low-level code as building snippets the same way it can use high-level libraries; most likely we won't be for a long time.
  • raincole 26d ago
    I've never encountered a case where I tell AI just uses plain JavaScript instead of React and it doesn't result in much cleaner code.
    • skydhash 26d ago
      Have you tried using it in the case where React is actually a good help (very interactive apps)? And try to generate vanilla code for that as well?
    • ordersofmag 26d ago
      If what you're trying to build is a perfect match for the full set of abstractions React provides then it's gonna be cleaner to use React than have AI re-invent it. But most cases I run into don't fit that description.
    • Xirdus 25d ago
      Note that even "plain" JavaScript is very high-level with tons of abstractions. Most website features are one-liners that call into browser APIs where the actual implementation lives.
• imtringued 26d ago
  No it means that libraries that chose the wrong level of abstraction will die out, particularly the ones that have an insufficient number of levers to pull. This is because of the rationale that makes you ignore the library: AI lets you build a competitor, but there is no rule that says you have to. You build the library because the existing one makes what you want impossible, otherwise you would have just let the AI write on top of it.
• lelanthran 26d ago
  > The way I see it is AI collapses hierarchy Right. Because the owners of capital will let you have access to the largest models, without which you can't compete with them. I think that there is a high probability of increased inequality, just like the how the added productivity in the past led to large gains for the capital holders, and next to no gains for the other 90%.
  • HEmanZ 26d ago
    Why do they even need to do that? It could be all open and you still can’t compete. The models could be all completely open weight forever and you still can’t compete with capital. How are you going to pay for the models or the electricity or the hardware? How are you going to compete against a swarm of ai agents that were spun up 6 months before you with 100x the capital whatever small amount of capital you scraped together doing one of the last few human jobs? Not with your human intelligence, which is now useless compared to machine intelligence. Maybe with luck, but at that point we’re all just at the casino.
• loh 26d ago
  There is still a lot of work do be done surrounding the systems AI integrates for us, and as a sibling comment mentioned, AI's ability to use various abstractions is incredibly beneficial, as it results in fewer tokens (not reinventing the wheel) and can provide more consistent/predictable polished results. If you're building something trivial like a basic web page or a very simple one-off script, sure, abstractions would be overkill. But if you're building something that needs to scale and interface with many other systems and work perfectly on every available platform, we still need abstractions that AI can work with. I don't think we've seen the end of the library/framework churn from the last few decades before AI, but I do think we will eventually settle on an "optimal approach" where the average developer no longer has to consider tool A versus tool B for basically every common use case. Future libraries and frameworks will be designed specifically for AI to "understand". Most LLM training data is based on the old way of building software, and while it is pretty good at it, I think we'll see major improvements (and counterintuitively, less AI slop) as the underlying abstractions and AI models adapt to the new paradigms and workflows enabled by AI.