Phil Royer is a security engineer at 7AI, and AI runs through nearly every part of his day. Ask him where it shows up in his work, and he'll tell you it's easier to list the places it doesn't.
Much of that work happens in layers. Phil kicks off an agent, it hands work to other agents, and those agents spin up a few more. "It's like agents talking to agents, sometimes three levels down," he says.
On the security operations side, Phil spends his time thinking like an attacker. He digs into 7AI's observability layer, maps out how someone could get in, builds detections to catch it, and runs investigations to prove the platform finds what matters. AI speeds up every step of that loop, so he can test more ideas and tighten coverage faster.
On the R&D side, his role looks like software engineering with the focus shifted upstream. Phil puts his energy into spec design and the data analysis that shapes each decision, while agents take on most of the hands-on coding. He's worked this way long enough that writing large chunks of code by hand feels like a skill from another life. "A little scary," he admits, "but it's highly effective."
The same habit follows him out the door, because Phil is a self-described running nerd.
Every run he logs on Strava produces a GPX file full of elevation, pace, heart rate, and route data. The apps give him a summary, but he always wants to go deeper. So he hands his files to DeepSeek and starts asking questions. How steep was that climb really? How fast did a friend run a certain stretch of the course? What do his heart rate and lactate say about where he is in training? In a few minutes, he has a clear picture of how he's doing and exactly what to work on next.
Whether it's an attacker's path or his own race splits, Phil's approach stays the same: bring AI the raw data, ask sharp questions, and put his own time into the decisions.
"I love working in security," he says. "Bringing AI to that has been a whole new level on top of that, and I'm just excited to see where we take this next."
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