Five Ways AI Agents Actually Fail, and Why Most Security Programs Are Only Built for Two of Them
Most of the industry discourse on agentic AI risk has settled into a comfortable framing: agents get attacked the way models get attacked, through some form of prompt manipulation, and the fix is a better guardrail. I think that framing is dangerously incomplete, and I want to walk through five specific scenarios that make the case directly rather than abstractly. Two of them are manipulation. One exploits trust between agents rather than any single agent's behavior.
