real programming of course wont go away. But in the public eye it lost its mysticism as seemingly anyone can code now. Of course that aint true and noone managed to create anything of substance by prompting alone.
How do we define real programming?
I'm working on python and JS codebases in my startup. So very high level stuff. However to reason well about everything that goes on in our code is no small feat for an LLM (or a human), if its able to take our requirements , understand the business logic and just start refactoring and creating new features on a codebase that is quite big,
well yeah, that sounds like AGI to me. In that case I don't see why it won't be able to hack on kernels.
The fact that you don't see why is the issue. Both python and JS are very permissive and their runtime env is very good. More often than not, you're just dealing with logic bugs and malformed domain data. A kernel codebase like Linux is one where there are many motivated individual trying every trick to get the computer to do something. And you're usually dealing with leaner abstractions because general safety logic is not performant enough. It's a bit like the difference between a children playground and a construction site.
> More often than not, you're just dealing with logic bugs
Definitely. More often than not you're dealing with logic bugs. So the thing solving them will sometimes have to be able to reason quite well across large code bases (not every bug of course, but quite often) to the point I don't really see how it's different than general intelligence if it can do that well. And if it gets to the point its AGIish , I don't see why it can't do Kernel work (or in the very least - reduce the amount of jobs dramatically in that space as well). Perhaps you can automate 50% of the job where we're not really thinking at all as programmers, but the other 50% (or less, or more, debatable) involves planning, reasoning, debugging, thinking. Even if all you do is python and js.
> So the thing solving them will sometimes have to be able to reason quite well across large code bases
The codebase only describes what the software can do currently, never the why. And you can't reason without both. And the why is the primary vector of changes which may completely redefines the what. And even the what have many possible interpretations. The code is only one specific how. Going from the why, to the what, to a specific how is the core tenet of programming. Then you add concerns like performance, reliability, maintainability, security...
Once you have a mature codebase, outside of refactoring and new features, you mostly have to edit a few lines for each task. Finding the lines to work one requires careful investigation and you need to carefully test after that to ensure that no other operations have been affected. We already have good deterministic tools to help with that.
I agree with this. An AI that can fully handle web dev is clearly AGI. Maybe the first AGI can't fully handle OS kernel development, just as many humans can't. But if/once AGI is achieved it seems highly unlikely to me that it will stay at the "can do web dev but can't do OS kernel dev" level for very long.
real programming of course wont go away. But in the public eye it lost its mysticism as seemingly anyone can code now. Of course that aint true and noone managed to create anything of substance by prompting alone.