Summary of Presentation: The security implications of AI-generated code aren't a future problem. They're already showing up in pipelines, in vulnerability backlogs, and in the growing gap between how fast code is being written and how fast it's being reviewed. Code volume is on track to increase fourfold, and most security programs weren't designed to absorb that.
This session looks at what that shift means for security leaders and the engineering organizations they partner with. We'll cover how the modern software pipeline creates compounding risk when it's moving faster than it was built to handle, and why models like Anthropic's Mythos represent a step change in the speed and scale of exploitation, not just another threat to add to the list. More importantly, we'll talk about what to do about it. Six concrete steps that security and engineering teams can take together to reduce exposure, shorten remediation cycles, and actually get ahead of the threat rather than just respond to it.
The goal isn't to slow things down. It's to build pipelines that are genuinely fast and genuinely secure, and to give security leaders the language and the framework to make that case inside their organizations.