4 posts
Mapping Beacon and AgentSH to the cybersecurity kill chain, showing where each product breaks the attacker's sequence in supervised and unsupervised AI environments.
Many AI agent incidents occur not because systems break rules, but because they follow them perfectly. When autonomy meets human permission models, authorized actions can still become unsafe.
Most agent “guardrails” live before execution (prompts) or after execution (logs). This post explains why that leaves you with hope and hindsight, and why real control must exist at the execution layer.
What we are seeing as AI agents start taking real actions, and why human speed oversight cannot keep up with machine speed execution.