Don't Be a Meat Proxy

Alex Beaver's biggest problem with AI? It runs on GPUs. A security engineer who thinks about the SOC like a factory floor explains why the best AI projects end with less AI running in production, not more.

Alex and Aaron get into what AI actually looks like inside a SOC: using an agentic SOC for fast coverage, then instrumenting it and converting its repeated tool calls back into cheap, deterministic workflows. Alex walks through his build process — writing the types and schemas himself, then letting Claude Code and Codex fill in the implementation — why models still get third-party schemas wrong, inventing a detection schema to do gap analysis, and why build vs. buy comes down to having someone to call at 3 AM. Plus: how worried defenders should be about offensive AI, where to start if you're new to this, and why "meat proxies" between Jira and an AI won't last.