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Overconfidence. These people think they are much smarter than others to be caught.

So far most of the "discussion" on this thread is why did he post this. He just posted what he thought others missed, if people find it useless it will further down the page. TLDR, I find the comments under that thread questioning why he posted even more pointless.

>> Any definitive claim to know what are the right things kids should learn in a moment of rapid technological shift is probably garbage and just a projection of our own biases.

I'm not really sure what point you are making here. We can talk about stuff based on what we know now. AI definitely isn't there yet. Even adults are figuring it out, the limits of its capabilities and shortcomings. Its not even been 5 years, and we want to change everything everywhere.

So if we don't know if we should or should not, and take into account all the hype, marketing, hype, advantages and some potential disadvantages (which are quite serious) why not just go ahead when there is more confidence.

Also house is built in 1890s. Had renovations, but who knows how much more work it needs.

Totally agree!

For anyone who still thinks kids should use AI, another argument to make is we are still figuring out AI (hence the constant debate on it, hype, uncertainty, boundaries of its capabilities etc etc). I don't think anyone with right mind can disagree with that. Keeping that mind, wouldn't it make sense to at-the-very-least tread with caution when it comes to kids.

> Sure, they're losing a whole lot of money too. Same goes for almost every other hyper-growth company in the history of tech

That doesn't mean anything. There are examples to make both ways. E.g. WeWork

You can switch to local models for tasks/use-cases where you don't need top tier models.

>> Let’s face it: by the time I manually ship version 1.0 of a product, the AI-assisted version could have been deployed 10x faster. By then, enough real-world feedback would have surfaced to identify the major issues, and tools like Claude Code would make it possible to fix and ship version 2.0 at an incredible pace.

Really depends on what you are shipping, what your users expect and what your personal preference is. I do not want to go 10x on products that need high performance / high reliability, is deployed at large scale where its not easy to undo. But for other stuff, sure why not. The problem is everyone just puts everything in same basket. Either way, AI is useful but not to the same extent people claim it to be.

Types are useful for squeezing more performance.

By that logic, most politicians making election promises didn’t lie or under delivered. They just changed their minds.

What are you saying then? Don't question or point out things that seem weird? Drink the kool-aid?

dot-com bubble? It's less about black or white, and more about how much of it. Nothing weird to me about caring given how it all also impacts peoples lives and much wilder all these numbers are becoming.

Its a polarizing world with AI. There are fanboys drinking the kool-aid blindly listening to whatever Sammy/Dario/... say as gospel, and on other side there are haters who again blindly reject the fact that these AI tools can be actually be useful. I think that's what the politics is.

I've read the details, strategy, extensive test suite etc. I'm sorry, I don't think "they have access to Claude Mythos" is the rationale to it unless you truly believe the marketing 100%.

I think we'll just see how it all turns out. Maybe check back in a year or two on hwo it all goes. Anyone who says they "know" or are "very sure" this is the right path or wrong path is plain stupid IMO. Having seen how things work in big companies with high market visibility, I believe there is non-trivial chance this driven mostly as marketting stunt (particularly in current climate) and decision isn't purely based on best interest of Bun's future and longevity.

>> same people that made bun have made this decision

Are they the same people though? Their interests, goals, environment, incentives, boss etc etc all changed after they got acquired by Anthropic. Its not uncommon for a big company to acquire a smaller one and completely destroy that product to serve the parent company's goal.

> Saying "because they vibe coded we are dropping support for Bun" sounds political.

I disagree that this is a political stance. People based on their experiences have formed opinions on whether they trust that model of development or not. Bun having taking extreme measure of going 100% in within a week is itself extreme positioning from their side which will likely result in extreme reactions because depending on who you are and your experience you'd bet on the fact that it may or may not work out.

DMV (at-least in Bay Area) is exponentially better and straighforward than any of processes around immigration / visa renewals.

I'm sorry, I don't consider them "great songs". Obviously, different people have different taste.

>> Meanwhile, songs are hitting number one on some charts on Spotify that people think are humans and are actually AI. And Spotify has to start labelling them as such. One AI "band" had an entire album of hits.

There is quite some questions around that. Music is subjective and obviously different people have different taste, but I wouldn't call any of them to be actual good music / real hits.

>> LLM discovered a new way to reason about a conjecture

I wasn't questioning LLMs ability to prove things. Parent threads were talking about building new kind of maths , or approaching it in a creative/artistic way. Thats' what I was referring to.

I can't speak for maths of hard science as I'm not trained in that, but the creativity aspect in code is definitely lacking when it comes to LLMs. May not matter down the line.

What's your basis for assuming LLM is capable of doing this?

I honestly don't know personally either way. Based on my limited understanding of how LLMs work, I don't see them be making the next great song or next great book and based on that reasoning I'm betting that it probably wont be able to do whatever next "Descartes, Newton, Leibnitz, Gauss, Euler, Ramanujan, Galois" are going to do.

Of course AI as a wider field comes up with something more powerful than LLM that would be different.

Or maybe you just aren't that good of an engineer (or whatever profession you are into) and find the easiest group to blame on your failures. I found that people who often are quick to judge and group of people in one bucket based on their color/ethnicity/gender/... are often not that bright people and like to focus on directing it on others. Somewhat like MAGA.

What percent of laid of employees do you think are H1Bs?

and hence reading code is unnecessary because how well LLMs understand and converts my prompts is almost equivalent to how well compilers can understand programs and turn into assembly. The prompts carry equal amount of ambiguity as the prompts I would write to define the behavior and want.

You are right about that but that's talking about what you generate but not what the output does. My point is that the compilers still designed to preserve semantic equivalence. semantic equivalence makes sense here because there are semantics well defined for both input and output. That bit is supposed to be deterministic. If something breaks that that is a bug.

I just don't think comparing with compilers is a good argument.

>> "we're already not writing machine code by hand for 50 years, how is AI different from a higher level language?"

I never got that argument. Compilers are formally proven, deterministic algorithms . If you understand what compiler does, you can have pretty good idea what it will produce. If it doesn't do that, its a bug. Definition of correctness is well defined by semantic equivalence.

LLMs are none of that. Its a fuzzy system that approximates your intent and does its best. I can make my intent more and more specific to get closer to what I want, but given all that is just regular spoken language its still open to interpretation. And all that is still quite useful, but I don't get the assembly language comparison here.

Maybe we do different things. Not that you are wrong about spending less time on things that you don't care about, but at the same time all that mechanical things helps you build a really good mental model of your product from high level design to individual classes. If I already have a good mental model of that I can direct AI to make really good changes fast, if I don't I will get things done ... but it does end up with less than ideal changes that compounds over time.

What you said: "figure out how to do unfamiliar thing" -- is correct, and will get things done, but overall quality, maintainability or understanding how individual pieces work...that's what you don't get. One can argue who care about all that as AI can take care of that or already can. I don't think its true today at-least.

>> Bad engineers continue being bad, good engineers continue being good.

I don't know if good engineers can necessarily continue to be good. There is limit to how much careful consideration one can give if everything is on an accelerated timeline. Regardless good or not, there is limit on how much influence you have on setting those timelines. The whole playing field is changing.

>> It will not all go well. The fear and anxiety about AI is justified; we are in the process of witnessing the largest change to society in a long time, and perhaps ever. We have to get safety right, which is not just about aligning a model

The question is what are they doing about "getting safety right" and are they doing enough. To me it seems like all the focus is on hyper growth, maximum adaptation and safety is just afterthought. I understand its competitive market, and everyone is doing it, but its just hollow words. Industries that cares about safety often tend to slow down.

Yeah, and all the little quirks here and there I had with emacs or things that I wish I had in workflow, I can just fix/have it without worrying about spending too much time (except sometimes maybe). The full Emacs potential I felt I wasn't using, I'm doing it and now I finally get it why Emacs is so awesome.

E.g. I work on a huge monorepo at this new company, and Emacs TRAMP was super slow to work with. With help of Claude, I figured out what packages are making it worse, added some optimizations (Magit, Project Find File), hot-loaded caching to some heavyweight operations (e.g. listing all files in project) without making any changes to packages itself, and while listing files I added keybindings to my mini buffer map to quickly just add filters for subproject I'm on. Could have probably done all this earlier as well, but it was definitely going to take much longer as I was never deep into elisp ecosystem.

Claude has really helped me improve my Emacs config (elisp) substantially, and sometimes even fix issues I've found in packages. My emacs setup is best it has ever been. Can't say it just works and produces the best solution and sometimes it would f** up with closing parens or even make things up (e.g. it suggest load-theme-hook which doesn't exist). But overall, changing things in Emacs and learning elisp is definitely much easier for me (I'm not good with elisp, but pretty good Racket programmer).