Will Bryk

I guess you can make the analogy of, like, agents to humans is like humans to sloths.

Okay?

I'm picturing that Zootopia DMV scene.

It's like, imagine we had a great search engine for sloths, and then humans came around.

They're not going to want to use that same search engine.

And so you should think of agents as these crazy creatures that have infinite time.

It's meaningless for them.

They just want to make complex queries very fast and analyze it really fast.

And they want perfect output for their human users.

So you want to build a search engine for that.

So what matters for that type of...

creature, well, lots of different things.

So first of all, you need a search engine that can handle complex queries, right?

Like, you do not want that creature to have to simplify its complex need for its user into simple keyword phrases, because you're just losing information.

So you want somebody that can actually semantically handle complex queries, but also handle keywords, because sometimes you just literally want, hey, like, I have this, uh,

like complex chemical formula like I want that to be part of the document right so you want a tool that can handle both semantic queries keyword queries really just like expose all the fundamental toggles to the agent because the agent by the way has the patience to like you know make a domain filter here and a keyword filter there or like search in this way search in that way so you want to like have a very controllable search engine you know like with Google like you search something and then

you're like, no, wait, that's not what I want.

And then you try to change some keywords and it's like, it's just missing it.

It's not like, it doesn't feel like very controllable, toggleable.

You want the opposite for an agent because the agent is just going to keep searching until it gets to its outcome.