Rain Paharia

They do get things wrong or they do things suboptimally or they do things in a way that's unmaintainable.

And you do have to pay attention to that, right?

And that is part of the rigor, which is like, okay, like I feel like I have built up some muscles around this from having used it, right?

And so I think part of the rigor is also like getting some practice with like looking at LLM code and reviewing it.

I actually suspect David has a few things to say because I know David and I have had some chats about this.

But for me, there are new vistas that open up and I think that's the way I think David put it.

So there are things that were simply not feasible to do given company priorities and personal life stuff going on and all the different things that are involved in a human's life.

that I feel like have opened up.

For me, the goal of this library was to increase the amount of rigor in our software.

I think it is very cool that it was able to work on this.

This is a way you increase rigor, is you build an abstraction that increases rigor even if it is tedious.

That is an increase in rigor in the overall system.

I think the difference though is that, you know, like LLMs will like do amplify that problem, right?

Like, you know, you can kind of get, I was talking about this with someone like, you can get something that is not great by in like a few minutes as opposed to maybe a few hours.

It's like a gish gallop almost.

I feel like that's how I think about it, right?

Where it's like a gish gallop for issues.

I've luckily not faced too many crap bug reports.

I've seen some AI bug reports, but they've all been very high quality.

Kind of at the standard that