Hi Good Morning [FIRST_NAME], Explore the security implications of AI-native infrastructure, including: The changing threat model: How AI agents and MCP servers change who and what can reach your infrastructure, and the new ways credentials can get exposed along the way. Secrets across the AI lifecycle: Where sensitive credentials can end up, from prompts and LLM workflows to the calls an agent makes into your infrastructure. Security patterns that work in practice: How scoped access, dynamic credentials, runtime secret injection, and auditability can help secure machine identities and AI workflows. A path to AI-ready infrastructure: Steps teams can take to strengthen secrets management as AI adoption scales. Get practical guidance on securing the infrastructure behind AI-powered workflows, along with the identities and credentials it depends on.
