• From Monitoring to Enforcement: The Three Layers of AI Agent Compliance
    Most AI governance tools only solve one-third of the compliance problem. There are three distinct layers — monitoring, incident generation, and runtime intervention — and understanding the difference between them is not an academic exercise. For enterprises deploying agents in regulated environments, it is the difference between a defensible compliance...
  • The Agent Dilemma: Power vs. Control — and Why Orchestration Is Now the Missing Layer
    OpenClaw went viral, got absorbed by OpenAI, and accidentally started a fight with an insurance company. It perfectly illustrates the core tension in enterprise AI deployment: the agents powerful enough to be useful are the ones with the least governance. Here's why orchestration is the missing layer.
  • Mapping the EU AI Act to AI Agent Compliance
    We’ve spent the past few months mapping EU AI Act requirements to what AI agents actually need to do at runtime. We’re sharing our findings because honestly, we think more people should be building agents—but in a way that’s compliant from day one.
  • An Agentic World: What Happens When AI Agents Become Colleagues
    Imagine a morning in 2030 where AI agents handle the noise, while you focus on strategy. This isn't science fiction—it's closer than you think. Based on the prologue of 'AI Agents at Work.'