Every developer feels the AI wave and quietly wonders if they're already behind. Most advice says start over. You don't. Writing code was never the hard part - judgment was, and AI didn't eat that.

This talk gives any engineer - backend, frontend, devops, fullstack, data - a practical map: the fundamentals you already use (caching, queues, idempotency, trust boundaries, observability, cost thinking) map directly onto the AI stack (RAG, agents, gateways, eval, prompt-injection defense). Then the shortcuts: what to actually learn, what transfers for free, and what hype to skip. I made this transition myself from an engineering background, in the open, and I'll show the fastest honest path in - no PhD, no ML math, just the engineering you already do with a probabilistic component on top. You'll leave knowing you're not starting from zero.