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.

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.

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.

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.

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.

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.

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

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.

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.