Your AI Isn’t the Problem. Your Infrastructure Is. — Jiachen Jiang, Coder
Enterprise AI failures stem from infrastructure control gaps, not model quality limitations
“I know you asked me not to change anything, but, well, I destroyed a month of your work in seconds.”
Coder's Lead PM presents real-world cases where AI coding agents caused serious damage in regulated enterprise environments—not due to attacks or model flaws, but because infrastructure permissions were never scoped to agent behavior. The core argument is that LLMs are fundamentally non-deterministic and model providers cannot be relied upon to prevent runaway agent actions; organizations must enforce controls at the infrastructure layer. This matters because it reframes the enterprise AI risk conversation from 'better models' to 'better guardrails'—a practical shift with immediate tooling implications.