Andrej Karpathy

And LLMs, the way they're trained on the internet, love text.

And so they're perfect text processors, and there's all this data out there, and it's just a perfect fit.

And also we have a lot of infrastructure pre-built for handling code and text.

So, for example, we have Visual Studio Code or, you know, your favorite IDE showing you code.

And an agent can plug into that.

So for example, if an agent has a diff where it made some change, we suddenly have all this code already that shows all the differences to a code base using a diff.

So it's almost like we've pre-built a lot of the infrastructure for code.

Now contrast that with some of the things that don't enjoy that at all.

So as an example, like there's people trying to build automation, not for coding, but for example, for slides.

Like I saw a company doing slides.

That's much, much harder.

And the reason it's much, much harder is because slides are not text.

Slides are little graphics, and they're arranged spatially, and there's visual components to it.

And slides don't have this pre-built infrastructure.

Like, for example, if an agent is to make a different change to your slides, how does a thing show you the diff?

How do you see the diff?

There's nothing that shows diffs for slides.

Someone has to build it.

So it's just some of these things are not amenable to AIs as they are, which is text processors.

And code, surprisingly, is.