For example an AGI AI could give you a detailed plan that tells you exactly how to do any and every task. But it might not be able to actually do the task itself, for example manual labor jobs for which an AI simply cannot do unless it also "builds" itself a form-factor to be able to do the job.
The AGI could also just determine that it's cheaper to hire a human than to build a robot at any given point for a job that it can't yet do physically and it would be the AGI
I think might even be simpler than that. It's about the cost. Nobody is going to pay for AI to replace humans if it costs more.
All of us in this sub-thread consider ourselves "AGI", but we cannot do any job. In theory we can, I guess. But in practical terms, at what cost? Assuming none of us are truck drivers, if someone was looking for a truck driver, they wouldn't hire us because it take too long for us to get a license, certified, learn, etc. Even though in theory we probably do it eventually.
Its hilarious reading this article and then the code because despite sometimes being a React hater - the React code is entirely more readable and followable.
Yes there are good frameworks that I'd argue beat React in multiple facets, but Backbone is not it having written it in the past.
- Two way data flow with stores is terrible for predictability
- Batching is not built in by default so you get layout thrashing as your app scales unless you're very careful
- You can easily blow away entire DOM trees if you aren't careful since it does not do any sort of reconciling differences.
- And more.
And the argument about needing to know stuff about the framework is entirely worthless. There are frameworks all over every single programming language ecosystem and ALL of them come with something you have to know about the framework itself, thats the tradeoff you make by picking a framework at all. Can we stop using this as an argument that there is magic or not? Yes React does tend to have a bit more in certain areas but they things they mentioned aren't even close to the worst offendors and have legitimate use cases.
The number of quality of life improvements, performance considerations, warning/DX improvements, etc. Its just not comparable for a small toy example.
Go build a full app with Backbone and React and tell me React wasn't miles easier to reason about and continue adding features.
I agree that all frameworks require learning framework-specific concepts, but I think there's a meaningful difference in what you need to know and how that knowledge transfers.
With Backbone, jQuery, or vanilla JavaScript, you're learning DOM APIs, event patterns, and explicit state management. These are things that are visible, inspectable, and fundamentally close to the platform. When something breaks, you can pop open devtools, see the actual DOM, trace the event handlers, and understand what's happening. The knowledge you gain is transferable. It's about how the web platform actually works.
With React, you're learning abstractions on top of abstractions: virtual DOM diffing, reconciliation algorithms, why objects in dependency arrays cause infinite loops, why your click handler sees stale state, why your input mysteriously cleared itself. This is React-specific magic that doesn't transfer. It's knowledge about how to work around React's mental model, not knowledge about how the web works.
You mention that batching and DOM reconciliation are solvable problems that justify React's complexity. But the article's point is that for most apps -- not Facebook-scale apps with 1,000 components on one page, but normal CRUD apps -- those problems can be solved with simpler patterns and conventions. We don't need a virtual DOM and a sophisticated reconciliation algorithm to build a form validator.
The real question isn't "does React solve problems?" It's "does React's complexity match the complexity of the problems most developers are actually solving?"
> The real question isn't "does React solve problems?" It's "does React's complexity match the complexity of the problems most developers are actually solving?"
Kind of disrespectful to reply to valid criticism of your AI slop article with more AI slop. Write like a human being man, what’s the point?
It's probably a US centric take you're replying to.
Having worked at multiple companies making apps in the US and the company I work at right now which is a company almost everyone knows the name of and the vast majority of our revenue comes from our native apps - practically every feature we build is iOS and web first and only if it performs well do we even consider adding to android most of the time. And it's primarily because product/execs know iOS users are more likely to pay for things.
It's sad as an android user myself, but android is very much a second class citizen in the US
Given how willing basically every major company is to sell your data to make money this is basically already the case and has been for years.
And when governments try to plug up some of the loopholes when it comes to privacy and data sharing, every major company finds some new gap to exploit or just does it illegally without telling anybody until they get found out and pay the fine.
Yes but they obsess over making everything perfectly ssr to the point of both delivering slow and half the time making client side navigations slow as hell after the user is already past the pay walled/marketing material part of your app.
Honestly except for the marketing page and blogs and stuff, most apps are fine without server rendering. In fact I'd say many that avoid server rendering actually feel better simply because next.js makes it really easy to screw up your performance doing it.
Some site have dual pages these days. I guess I should explain… they have a large footprint seo and those pages are static… unless you are logged in, then they are completely different!
I see this happening in finance data sites. Say a page about Apple, has stock price, etc. when logged in, same stuff but 10x data so they layout and everything is different.
The fact that every company feels the need to do this shit simping for Trump just so that they can try not to get put on the chopping block is a shame on this country.
You mean like every company implementing DEI for the last administration? I don't like Trump but this is how both sides have been playing politics. I suspect I'll get downvoted and flagged for this which I think will prove my point.
It is so bizarre the way some people act like all DEI policies were introduced between January 2021 and January 2025. I can understand being against the policies, but people are just straight lying about how, why, and when those policies came to be.
And Trump isn't the first person to push for hiring in America or other such things. Under both Obama and Biden companies, government and academia significantly increased DEI spending. Multiple executive orders were signed by both to promoted DEI.
Fun fact, my comment said nothing against DEI and you assuming I did more or less summarizes modern political discourse on both sides. Even implying something isn't 200% amazing means you must be utterly opposed to it's very concept.
>Fun fact, my comment said nothing against DEI and you assuming I did more or less summarizes modern political discourse
Fun fact, my comment said nothing in support of DEI and you assuming I did more or less summarizes modern political discourse.
DEI was not implemented "for the last administration" like you implied. My comment was not even really about DEI, it was criticizing you for implying something that wasn't true. And you seem to know it yourself with the way you subtly shifted the conversation from "the last administration" to "under both Obama and Biden", pushing the age of these policies back another 12 years.
Maybe some companies implemented DEI because civil rights matter to people? And those that care have kept it.
Trump just cut a bunch of money to blue state projects. Did the last admin do that to the red states? 60% of Biden’s infrastructure bill went to red states.
> Maybe some companies implemented DEI because civil rights matter to people? And those that care have kept it.
And some companies care about hiring in America and always have. This is an article about Google which dropped DEI the second it could. Clearly it didn't really care.
Personally I use filter and map (and others like .some, .every .flat and flatmap etc) all the time but I avoid reduce.
filter and map immediately tell me what the purpose of the loops are - filter things and transform things. A for loop does not do this.
To someone familiar with functional programming these are very normal and easier to read and grep than just a loop. In other words filter and map give additional context as to the intent of the loop, a bare for loop does not.
Not to mention this is not abnormal in languages outside of JS, even non-functional ones.
That said Ive seen too many convoluted uses of reduce that I just avoid it out of principle.
Yeah, the "problem" with reduce is that it can do anything, and so doesn't offer much over a traditional for loop with mutable local variables to accumulate into. Of course, if you can replace a reduce() with a filter and/or map or whatever (which more clearly states intent), by all means do so!
If you really need arbitrary computation, I'm not sure there's any real readability benefit to reduce() over local mutation (emphasis on local!). Sure, there's immutability and possibly some benefit to that if you want to prove your code is correct, but that's usually pretty marginal.
Reduce can be very useful to signal that the state used is inherently limited. My rule of thumb is to use reduce when the state is a primitive or composed of at most two primitives, and a for loop otherwise. What counts as "primitive" depends on the language of choice and abstraction level of the program, of course.
Fair observation, but just opening a local lexical scope (in an expression-oriented language) can help with that. Also ... something something ST monad :)
I like map() and filter() in Python, but unfortunately they’re 2nd class citizens compared to list comprehensions, which continue to get optimizations to further increase their speed.
I like comprehensions as well - and their syntax is quite readable - but I’d like for the two to be more at parity.
One of the main reasons that map() and filter() don’t get optimizations in Python is because they’re lazy.
It’s a lot easier to optimize comprehensions because you can make a lot more guarantees about what doesn’t happen between iterations: the outer stack doesn’t move, the outer scope can be treated as static for purposes of GC-ing its locals, various interpreter-internal checks for “am I in a new place/should I become aware of a new scope’s state?” can be skipped, the inner generator can use a simplified implementation since it never needs to work with manual send(), and so on.
Map/filter can’t take advantage of any of those assumptions; they have to support being passed around to different arbitrary places each time next() is called on them, and have to support infinite sequences (so do comprehensions technically, but the interpreter can assume infinite comprehensions will terminate in fairly short order via OOM lol).
That said, there are likely optimizations that could be applied for the common cases of “x = list(map(…))” and “for x in filter(…):” (in nongenerator functions) which allow optimizers to make more assumptions about the outer context staying static.
The price of training and running the models doesn't really change much no matter which region you're hosting/making requests from.
Regional pricing unfortunately doesn't really make much sense for them unless they're willing to take even larger losses, even if it is a barrier to lower income countries/regions.
Don't have a moonlander but I actually did this with my advantage 360 pro. I did not remove the switches but I made them no-ops. The whole left-most and right-most columns of the keyboard are completely unused for me.
If you travel with the keyboard a lot maybe its an issue since its extra weight/space, but if not I don't see it really hurting much.
For example an AGI AI could give you a detailed plan that tells you exactly how to do any and every task. But it might not be able to actually do the task itself, for example manual labor jobs for which an AI simply cannot do unless it also "builds" itself a form-factor to be able to do the job.
The AGI could also just determine that it's cheaper to hire a human than to build a robot at any given point for a job that it can't yet do physically and it would be the AGI