Reinventing Control Theory One Feature at a Time: The Fallacy of Agentic Loops (medium.com) AI

The article argues that “agentic loops” in AI coding—adding agents to monitor, review, and iterate over each other’s work—amount to a fragmented, hype-driven rediscovery of control theory without the full methodology needed for safe, reliable operation. It warns that probabilistic agents validating one another are not automatically a robust control system unless stop conditions, trusted signals, authority, boundaries, and fallback paths are explicitly designed, and it urges teams and leadership to address hard operational and financial questions before deploying such loops.