Making autonomous security systems safe, accountable and governable.
Agentic AI Security Model safety is not agent safety. Confusing the two may become one of the more consequential mistakes we make as AI moves from answering questions to taking actions. Agentic AI security is the practice of keeping an autonomous AI agent safe while it acts, not just while it answers. It sits downstream… Read More »Your AI Agent Is Safe. Until It Starts Acting.
Many objections to belief-state planning are framed as concerns about scalability. In practice, they are concerned about visibility. Systems that avoid explicit belief do not eliminate uncertainty; they merely conceal it. This concealment can appear efficient, but it comes at a cost that is paid later often at the point where decisions matter most. This… Read More »Combinatorial Belief States Are the Cost of Explicit Uncertainty
For most of the past decade, the trajectory of large language model research followed a familiar arc: scale up the compute, widen the data, tune the alignment, ship the product. Each new generation of models arrived with modestly improved benchmark scores, better instruction-following, and marginally reduced hallucination rates. Opus replaced Sonnet. Sonnet replaced Haiku. The… Read More »Demystifying Claude Mythos Preview: The Model That Changed Cybersecurity Forever
This article is a continuation of Why LLMs Are Not Planning Machines. In that earlier post, the core claim was simple: large language models can generate plausible action sequences, but they do not plan. They lack a mechanism to reason over uncertainty across time. This follow-up post focuses on what is missing. The missing abstraction is the… Read More »Belief State: Why AI Planning Fails Without It
In the course of my work with LLMs, I’ve been examining a recurring pattern in how large language models are being used inside real systems. In many settings, I observed that LLMs are treated as planners where they are used to generate multi-step workflows, remediation strategies, operational playbooks, and even “autonomous” action sequences. These plans… Read More »Why LLMs Are Not Planning Machines (And What It Means)