Beth

Most likely because of how it's designed to not be the same.

You may get like, people are seeing these random,

blogs or websites that aren't even ranked at all show up.

And that could be related to personalization that created to, or it could be also related to just like the large cycle model saying, Hey, here's what we show, like what is regularly shown.

Why don't we show you this one?

So for anybody to, I think.

Think about, hey, we've got the answer to GEO, AO.

And I was like, I don't.

Because one, there's a pattern of randomness to it, which is kind of built in.

But it also, it's heavy personalization for everybody.

So it's a completely different way to think about it.

And then I want to add one more layer in that.

That's great that you're using a large language model, but as more and more of us use a GenSpark, use agent mode, use Gemini agent, we're not searching anymore.

It's our agent doing, preparing the search, planning the search, executing the search, and just coming back with us, not just the answer, but like,

we just gave it a goal and there's the answer.

So how are you preparing for that?

There is no one really is talking about optimizing for agents.

They're just optimizing for large language models.

Right.

So it's just a commentary of just like what's interesting in the space.