Andrej Karpathy

Some people completely reject all of LLMs, and they are just writing by scratch.

I think this is probably not the right thing to do anymore.

The intermediate part, which is where I am, is you still write a lot of things from scratch, but you use the autocomplete that's basically available now from these models.

So when you start writing out a little piece of it, it will autocomplete for you, and you can just tap through, and most of the time it's correct.

Sometimes it's not, and you edit it.

But you're still very much the architect of what you're writing.

And then there's the vibe coding.

You know, hi, please implement this or that, you know, enter, and then let the model do it.

And that's the agents.

I do feel like the agents work in very specific settings, and I would use them in specific settings.

But again, these are all tools available to you, and you have to learn what they're good at and what they're not good at and when to use them.

So the agents are actually pretty good, for example, if you're doing boilerplate stuff.

Boilerplate code that's just copy-based stuff, they're very good at that.

They're very good at stuff that occurs very often on the intranet.

because there's lots of examples of it in the training sets of these models.

So there's features of things where the models will do very well.

I would say NanoChat is not an example of this, because it's a fairly unique repository.

There's not that much code, I think, in the way that I've structured it.

And it's not boilerplate code.

It's like actually like intellectually intense code almost.