Jesse Zhang

In the early days, we have a customer that is essentially like a large ticketing platform.

And one of the things that would happen was someone came in, they couldn't find their ticket.

I looked into their account.

It's like, hey, there's no tickets here.

And then they were just like, okay, well, what I'm going to do is I'm going to show up to the events and I'm going to find eight homeless people from the city and bring them with me.

And the agent was like,

Oh my God, that's so awesome that you're thinking about doing something nice for the community.

Things like that where it's like, okay, I would not expect that to happen.

So those are just like tuning you have to do over time.

And generally it's in the spirit of that where you're trying to find the right level of guardrail and flexibility.

I think that's the name of the game with R Space at least.

And that's sort of the way we design our product and why probably the number one reason we've been successful so far.

is that what Gen AI really unlocks is super flexible, super personalized.

One way you can think about it is like in the old days to map out a conversation, you just build a gigantic tree of decisions.

And that's very hard because no one likes that experience.

And you ask something that's not quite one of the branches and it just forces you down that branch and there's no way to go back.

And what ALM does is it extracts a lot of that tree into the neurons of a language model.

So that's really powerful.

On one end of the spectrum, you're just looking for flexibility and root power and being able to sound really human-like.

But with the enterprise, there are a lot of things we don't necessarily want that as much.