Originally published on tamiz.pro.
We have spent two decades obsessed with determinism. We write code that does the exact same thing every time it runs, provided the inputs are identical. We build type systems to eliminate ambiguity at compile time and unit tests to verify state transitions at runtime. Then came Large Language Models (LLMs)—engines of pure, beautiful probability—and we tried to force them into our rigid, deterministic boxes.
The result is what I term AI Psychosis: the chaotic, often invisible behavior of AI agents when they are allowed to loop, self-correct, and interact with fragile modern infrastructure without hard boundaries. As we ship tools like the OpenAI Agents SDK, we aren't just solving coding problems; we are exposing a deep, uncomfortable truth about the software engineering landscape: our stack is brittle, and stochastic actors will find every crack.
This isn't a LLM problem. It's a software engineering problem wearing a mask.
The Rise of the Stochastic Actor
