Walk us through your perspective on open source and why it's so important.

Listen, one of the things that we have seen in the past, in the recent past, is the adoption of AI tooling happens first in the open source community.

We saw this happen with OpenClaw, where as soon as a runtime was put out there, it caught on like wildfire because it solved a very meaningful pain point because it provided a harness that allowed you to be able to run things instead of a Mac mini, and that solved very meaningful problems.

And you saw that it just took off.

There are so many of these AI projects that start out in the open source community.

And it's a very strong indicator for what the community is expecting with respect to these solutions.

And it's very useful.

Give me both the

Let's start with what is going on in the market with AI right now that customers should keep in mind, and how is that changing infrastructure specifically in the world?

Gita, one of the biggest things that we need to start to internalize is the fact that we're moving from chatbots to agents.

And as we move to agents, agents are starting to take actions on behalf of a user.

And it's incredibly important to make sure that there's trusted delegation that's happening where these agents can go out and execute tasks entirely on your behalf.

And so I think the shift that we're starting to see that's happening is with agentic coding, we're noticing that these agents are able to do things that we never thought was possible about six months ago.

It starts out with, you know, and there's a very common pattern, right? It starts out with these agents, you know, when you start using even models, you kind of feel like they're not perfect at the tasks that they're doing.

And then within six months, you suddenly start to realize that those things that you thought was not perfect, it now does those jobs incredibly well.

How should customers think about deploying this? What's your advice to them?

Let's start with what is going on in the market with AI right now that customers should keep in mind, and how is that changing infrastructure specifically in the world?

Gita, one of the biggest things that we need to start to internalize is the fact that we're moving from chatbots to agents.

And as we move to agents, agents are starting to take actions on behalf of a user.

And it's incredibly important to make sure that there's trusted delegation that's happening where these agents can go out and execute tasks entirely on your behalf.

And so I think the shift that we're starting to see that's happening is with agentic coding, we're noticing that these agents are able to do things that we never thought was possible about six months ago.

It starts out with, you know, and there's a very common pattern, right? It starts out with these agents, you know, when you start using even models, you kind of feel like they're not perfect at the tasks that they're doing.

And then within six months, you suddenly start to realize that those things that you thought was not perfect, it now does those jobs incredibly well.

How should customers think about deploying this? What's your advice to them?

Walk us through your perspective on open source and why it's so important.

Listen, one of the things that we have seen in the past, in the recent past, is the adoption of AI tooling happens first in the open source community.

We saw this happen with OpenClaw, where as soon as a runtime was put out there, it caught on like wildfire because it solved a very meaningful pain point because it provided a harness that allowed you to be able to run things inside of a Mac Mini, and that solved very meaningful problems.

And you saw that it just took off.

There are so many of these AI projects that start out in the open source community.

And it's a very strong indicator for what the community is expecting with respect to these solutions.

And it's very useful.

Give me both the

Yeah.

And the next thing that happened was I-- You know, we realized that there are roughly about, you know, um, almost around 60 to 70 different products that we're going out and selling, about 15 to 20 different platforms that these products sit inside of.

Um, it makes it, you know, incredibly interesting to start to think about how do you, how do you go to market with so many different products-

For sure.

So, so we said, "Listen, if we could create a canvas-like experience where they can-- multiple people can come in and collaborate," and then they, and then we power that with a, a model that we are making better.

Like, you know, it's, it's again, not just a single model.

It's a combination of models.

It's got a, uh, the frontier model, a purpose-built model that we have for networks, for security, for observability.

Exactly.

And one of the key things that it is really good at is simplifying things for you.

And so back to your point about, hey, networks seem very complicated.

Now, what AI can do for you is it can really truly simplify, but the important piece that we at Cisco are focused on is making sure that we're simplifying, but it's not at the expense of the sophistication because you still need pretty complex things to be completed, like, from a task perspective, you know, from an, from a configuration perspective.

You gotta do pretty involved things.

So, so it's, it's basically balancing both of those things in a way that is extremely powerful, and that's really what we're doing.

This week, we're announcing Cisco Cloud Control with agentic ops, which is gonna fundamentally change the way you think about how you configure your networks, how you manage your networks, how you monitor it, and, uh, I am beyond excited about it.

Nice.