Technology

I think that certain things will be fairly resistant to forking, even by AI. Foundational software like the kernel, compilers, basic tools, databases, and so on will likely benefit more from being used as the standard/vanilla version rather than a modded version (especially a vibe-modded one).

But people and companies will experiment with this for sure and it wouldn't surprise me if some of the less software-competent hardware companies start making their Linux forks or drivers with LLMs, at least for a couple of years in the near future.

I also think that this will shift lots of companies further away from GPL toward MIT/BSD, because they'll want a fully moddable source but they won't want to share what they're vibecoding.

Non AI code has been crashing down for decades, controlled chaos, continuous improvement. We have lots of tools to put metrics on that, and AI assisted code is fairly well crushing those metrics. It's not 100% self sufficient code creation Nirvana, but it might be fairly compared to the Cotton Gin in terms of making the field workers more productive in the delivery of market ready code/cotton.

What happened to those developments that started in the 70s where you have automatic formal proofs that a piece of code does what it is supposed to do?

The stochastic parrots we have today are pretty good at doing that kind of tedious, extensive, franky mind numbingly boring stuff. They're also fast enough that you can "afford" to take the time / effort required to do those kinds of proofs where they are warranted - it makes them "a good idea" in a lot more places than they used to be when they were so much more expensive to perform.

modern AI can be used to generate formal lean proofs:

• https://www.scientificamerican.com/article/what-happens-when-ai-starts-checking-mathematicians-work/
• https://lemmy.world/post/50205770

If Vibe coding means people who don't know how to code creating code... yeah, that's kind of like giving people who don't know how to paint an airless gun and 5 gallon bucket and telling 'em to go for it on this building here...

This is the key point.

From my reading that is not the limit in how they are using AI. It seems like they are accepting LLM generated code as inputs.

This pretty much compromises the whole project as far as I am concerned.

There’s a difference between vibe coding and the hundred other ways to “use AI” on a project.

I am not talking about the Linux kernel or the Rust project - they have stabdards way above average commercial projects - but generally "using ai" in practice means to use it for code generation. Then, programmers are expected to review the output but are not given extra time for it. This creates an extremely slippery slope leading to mostly unsupervised code creation. Also because reading and understanding buggy third party code means more effort than writing new code.

Then there is the idea to get rid of the bugs by "debugging", but debugging is frankly not a software engineering strategy, because you can always just recognize a fraction of the bugs that your process created in the first place. Debugging is also more expensive tha writing good code.

Then, what makes the process between product managers and software developers very often a bit friction-loaded is that good developers always want to have clear specifications what they are supposed to build.

LLM code generation largely replaces clear specifications with plausible assumptions. That appears to make the process fast, but the result is often wrong. At times obviously wrong, and at times subtly and catastrophically wrong.

It's funny because anyone seeing this as black and white clearly hasn't ever opened an IDE.