Can You Buy Your Way to DevSecOps Success? | Arcjet’s David Mytton

**Andrew Zigler** (0:09)
Welcome to Dev Interrupted. I'm your host, Andrew Zigler.

**Ben Lloyd Pearson** (0:13)
And I'm your host, Ben Lloyd Pearson.

**Andrew Zigler** (0:15)
In today's news, we're talking about a few topics. Top of mind for me is Google's new AI search mode. Another one is a new buzzword I was reading about called AX, and not like an ax that you hit someone with, but actually agent experience. There was another one, AWS formed an internal agentic AI group. That was pretty cool. And I found some sweet, sweet useless apps online. Ben, what do you want to talk about first?

**Ben Lloyd Pearson** (0:46)
As much as I love useless apps, I think we should dive into the Google search.

**Andrew Zigler** (0:52)
Okay, so we've been talking about the search war between AI and Google on this podcast for a few weeks now. Google search has unveiled a new AI mode that lets you ask complex questions with many different parts directly into the search bar. Before, what might have been five or ten, or maybe even many more individual queries by you? As you try to understand a question or seek something out online, you can now explore these search results in a more natural conversation like way with Google.

**Ben Lloyd Pearson** (1:26)
Yeah, it seems that Google search lives to see another day. It's kind of extraordinary to think about how much our typical research process has changed in such a short amount of time. The way we used to acquire information just feels like a distant dream at this point. But I think this is also a great example of how disruption from AI doesn't necessarily mean death. A lot of people are concerned about whose jobs are going to get taken or what sort of industries it's going to wipe out.
I think the reality is more like AI is going to disrupt us, but it's probably not going to wipe out swaths of professional jobs overnight. There's a lot of room to just adapt and leverage all the benefits that these tools are bringing us.

**Andrew Zigler** (2:12)
What I see here is Google taking another bite back from AI and the ongoing search wars, earning back a little bit of that market share. I think we've all had our mixed experiences going to Google and getting AI results or answers in response to your queries. And so one step further towards a better version of that goal is really great. And like what you were saying, I think that there's more disruptions always on the horizon. They come from everywhere. But ultimately what this disruption means is a higher demand for more unique experiences because now you can go to Google and ask that really in-depth, maybe even personal question and crawl across a lot of real-time resources in a way that maybe before you were using an LLM for anyways.
It's going to create a more personalised experience for everyone online, which I think is going to just increase the demand for more jobs and more professionals and more technologists that come in and create these personalised experiences for people with the technology.

**Ben Lloyd Pearson** (3:08)
Yeah, and this ties nicely into the article that I wanted to bring up today. And that's this concept of agent experience. So maybe this is disrupting DevEx, or at least that's the point of this article that I read this week. And the whole point is that we have to start focusing on agent experience, which is defined as the holistic experience that AI agents have as the user of a product or platform. So think about how everything is sort of built for humans as the end user, like the web, for example.
Most websites are built for a human to visually analyze them and extract information from them. And if you're a bot that's just like scraping text off of a website, the web actually looks entirely different to you. And in that same way, AI agents are the same. The patterns that work for humans aren't always going to work for these agents, at least not in an optimal way. This article highlights two ways that agents are getting integrated into products. The first is vertical. That's like what we were talking about with the Google search example. And that's where you have tighter integrations of internal AI into your product. In addition to Google search, adding these new AI capabilities, Google also adds Gemini buttons to Google Docs, for example. And then the other side of that is horizontal, so making it easier for external agents to interact with your platform. So think about bringing more select external models into a platform to leverage capabilities that it has.