Since my original worries about agentic AI in October last year, advances in their capabilities have been prolific. Tools such as OpenAI’s Codex, Anthropic’s Cowork, and open-source projects like OpenClaw are bringing powerful agentic capabilities within the reach of non-developers. Many are enthusiastically heralding the arrival of a golden agentic age.
My previous advice was always to keep a human-in-the-loop and ensure there is a kill switch, but, as I will explain, this is now impossible in the very scenarios that need it most.
After six months – a long time in AI – my guidance needs an upgrade.
The twin perils of complexity and consequence
Not all agents are created equal, and I find it helpful to think of them in two dimensions: complexity and consequence. In this scheme, complexity is closely related to whether a human can understand an agent’s operations in a timely way, and consequences are defined by what it is capable of doing.