hckrnws

> While working on Cutlet, though, I allowed Claude to generate every single line of code. I didn’t even read any of the code. Instead, I built guardrails to make sure it worked correctly (more on that later).

Impressive. As a practical matter, one wonders what th point would be in creating a new programming languages if the programmer no longer has to write or read code.

Programming languages are after all the interface that a human uses to give instructions to a computer. If you’re not writing or reading it, the language, by definition doesn’t matter.

I've been wondering if a diffusion model could just generate software as binary that could be fed directly into memory.

I don’t agree with the idea that programming languages don’t have an impact of an LLM to write code. If anything, I imagine that, all else being equal, a language where the compiler enforces multiple levels of correctness would help the AI get to a goal faster.

A good example of this is Rust. Rust is by default memory safe when compared to say, C, at the expense of you having to be deliberate in managing memory. With LLMs this equation changes significantly because that harder/more verbose code is being written by the LLM, so it won't slow you down nearly as much. Even better, the LLM can interact with the compiler if something is not exactly as it should.

On a different but related note, it's almost the same as pairing django or rails with an LLM. The framework allows you to trust that things like authentication and a passable code organization are being correctly handled.

That is why Typescript is the main one used by most people vibe coding, The LLMs do like to work around the type engine in it sometimes, but strong typing and linting can help a ton in it.

> If you’re not writing or reading it, the language, by definition doesn’t matter.

By what definition? It still matters if I write my app in Rust vs say Python because the Rust version still have better performance characteristics.

In principle (and we hope in practice) the person is still responsible for the consequences of running the code and so it remains important they can read and understand what has been generated.

I think we're going to see a lot more of this. I've done a similar thing, hosting a toy language on haskell, and it was remarkably easy to get something useful and usable, in basically a weekend. If you keep the surface area small enough you can now make a fully fledged, compiled language for basically every single purpose you'd like, and coevolve the language, the code, and the compiler

AI written code with a human writted blog post, that's a big step up.

That said, it's a lot of words to say not a lot of things. Still a cool post, though!

The AI age is calling for a language that is append-only, so we can write in a literate programming style and mix prompts with AI output, in a linear way.

That’s git commits.

or css

Now anyone can be a Larry Wall, and I'm not sure that's a good thing.

> I’ve also been able to radically reduce my dependency on third-party libraries in my JavaScript and Python projects. I often use LLMs to generate small utility functions that previously required pulling in dependencies from NPM or PyPI.

This is such an interesting statement to me in the context of leftpad.

I'm imagining the amount of energy required to power the datacenter so that we can produce isEven() utility methods.

[dead]

Next you can let Claude play your video games for you as well. Gads we are a voyeuristic society aren’t we.

I am kind of doing that now. I put Kimi K2.5 into a Ralph Loop to make a Screeps.com AI. So far its been awful at it. If you want to track its progress, I have its dashboard at https://balsa.info