Katie Bianchi

So we knew we couldn't sit back and observe that we had to lead. And I think to do that well, we had to return to the start in many ways, especially from a customer experience perspective. So- You know, we had to rethink everything we knew about how we did things through the lens of this incredibly powerful technology that was hitting the scene.

So we knew we couldn't sit back and observe that we had to lead. And I think to do that well, we had to return to the start in many ways, especially from a customer experience perspective. So- You know, we had to rethink everything we knew about how we did things through the lens of this incredibly powerful technology that was hitting the scene.

And it really forced us to go back to the start and learn about the way things were done so we could actually learn about how to do them better with AI.

And it really forced us to go back to the start and learn about the way things were done so we could actually learn about how to do them better with AI.

And it really forced us to go back to the start and learn about the way things were done so we could actually learn about how to do them better with AI.

Just as a quick, quick overview, you know, at the end of the day, my role is all about how to get our customers deployed fully and reliably. how to get them to value and continue to deliver value, and how to ensure that whatever we've deployed for them stays technically healthy as they grow, change, and scale with us.

Just as a quick, quick overview, you know, at the end of the day, my role is all about how to get our customers deployed fully and reliably. how to get them to value and continue to deliver value, and how to ensure that whatever we've deployed for them stays technically healthy as they grow, change, and scale with us.

Just as a quick, quick overview, you know, at the end of the day, my role is all about how to get our customers deployed fully and reliably. how to get them to value and continue to deliver value, and how to ensure that whatever we've deployed for them stays technically healthy as they grow, change, and scale with us.

So as you think about that landscape of work, we're really in the execution and scaling phase. We continue to experiment because the technology changes so quickly that you have to continue to experiment at the rate the technology is changing to figure out how to apply it. But AI is already embedded in how we resolve every single technical support case.

So as you think about that landscape of work, we're really in the execution and scaling phase. We continue to experiment because the technology changes so quickly that you have to continue to experiment at the rate the technology is changing to figure out how to apply it. But AI is already embedded in how we resolve every single technical support case.

So as you think about that landscape of work, we're really in the execution and scaling phase. We continue to experiment because the technology changes so quickly that you have to continue to experiment at the rate the technology is changing to figure out how to apply it. But AI is already embedded in how we resolve every single technical support case.

And we focused first on technical support, given what we knew to be a really massive opportunity to completely change and delight our customers and respond cases much more quickly, even the more complex ones. So we've also started the journey to actually how we embed AI and the way that we deploy our products and drive value for our customers.

And we focused first on technical support, given what we knew to be a really massive opportunity to completely change and delight our customers and respond cases much more quickly, even the more complex ones. So we've also started the journey to actually how we embed AI and the way that we deploy our products and drive value for our customers.

And we focused first on technical support, given what we knew to be a really massive opportunity to completely change and delight our customers and respond cases much more quickly, even the more complex ones. So we've also started the journey to actually how we embed AI and the way that we deploy our products and drive value for our customers.

Yeah. It's interesting. We did. We focused first on areas where scale and complexity were slowing customers down. And for us, that was support and deployment. And if I think about

Yeah. It's interesting. We did. We focused first on areas where scale and complexity were slowing customers down. And for us, that was support and deployment. And if I think about

Yeah. It's interesting. We did. We focused first on areas where scale and complexity were slowing customers down. And for us, that was support and deployment. And if I think about

how I think about like the one, two, three of implementation, the first part is fixing the foundation and making sure that your data and your processes and how people access both and how you feed those into AI sort of has to be central, but we didn't just focus. on the quick wins. We focused on what it would take to solve our hardest and most complex problems as well.

how I think about like the one, two, three of implementation, the first part is fixing the foundation and making sure that your data and your processes and how people access both and how you feed those into AI sort of has to be central, but we didn't just focus. on the quick wins. We focused on what it would take to solve our hardest and most complex problems as well.

how I think about like the one, two, three of implementation, the first part is fixing the foundation and making sure that your data and your processes and how people access both and how you feed those into AI sort of has to be central, but we didn't just focus. on the quick wins. We focused on what it would take to solve our hardest and most complex problems as well.