Aaron Levie

If we can shorten the product feedback cycle that normally happens, which is you release something, you listen to customers, it takes a couple of months.

If we can internally just learn those things very quickly, we can recycle that back into the product roadmap and then improve our own internal development velocity.

So we're using it selfishly for our product teams

To then also see, oh, wait a second, we ran into this issue where people want to share prompts, but we don't have a useful mechanism for sharing those prompts.

Let's go build a prompt library, like those kind of things.

I think as an industry, we're very early in what is a normalized sort of metric to quantify AI-driven productivity.

I think there's a range of approaches that you can take.

We've actually explicitly said that right now we're still in the journey to figure out what metric we're going to land on.

There's an easy one, which is sort of like, how much money did I save directly?

Then there's another one, which is how much money in productivity or hours or system time did I have cost avoidance on?

So that's like, if I had done this with human labor, it would have cost this much.

And then a third easy one is just like, what are the hours, tokens, some metric of just sheer output coming from the AI that now you're utilizing?

Right now, we're actually way more focused and I'm very comfortable being more in the in the we actually want like 1000 flowers to bloom mode.

I don't know if I would feel comfortable if I were like at JP Morgan with that strategy.

But being on the front lines of a software company that that is fundamentally, you know, becoming an AI first company, I don't mind a little bit of a period of let's just let's let everybody go and test and push these systems.

And I think

I think the best scenario for us right now is this idea of revealed preference, right?

Like, let's just like see what people actually do.

And almost by definition, the market, you know, we set very high goals for anybody working in the company.

And so it's quite easy just to then let the market decide how to use AI to accomplish those goals.