Sara Madden

But I think if you broaden it out and have a lot more people in the room, you know, rising tides list all boats kind of scenario.

I mean, we're thinking about how to measure effectiveness of AI and how much our engineers are using AI.

And we're looking at what metrics make sense.

And it can't be like a conflict of interest in a kind of scenario.

So you have to look at like the goals for AI that you have as a business and what those outputs are and then measure it that way.

If it's engagement with the particular ID tool that you're using in engineering and you want to make sure people are using tokens, sure.

But obviously it has to just be proportionate to what you want to do for your business.

But I mean, it's important like...

There are a lot of engineers that don't want to adopt AI because they think they're going to displace themselves.

So what are the kinds of AI use cases do you have going on in your environment that you can incentivize engineers to do and then roll with that?

Adoption, speed, accuracy, reinforcement learning models are getting better.

I mean, every time we renew a software license, we ask ourselves, can we replace this with AI?

And I already made that call in a vendor a couple weeks ago.

So it's evolving fast.

So yes, for sure.

I mean, I have my compliance team writing AI little bots and automating responses to audits and customers and displacing vendor solutions we have with that.

And so it's not just the engineers that are using AI now.

I think it's just the broader creativity that I'm seeing across all of the different roles we have to figure out different things to automate and then figure out what else are we going to do with our time.

That's the fun part about where we're at now.

It's everybody's playing with it.