AI agents could dissolve the friction that keeps justice expensive
It restructures who holds legal power, where authority comes from, and when law intervenes.
What 100 scenarios reveal about AI risk in legal conflict resolution
The scenarios expose trade-offs that current regulatory frameworks are not designed to handle.
Five layers that separate real governance from compliance theater
Read with a highlighter. There are a lot of pages. Most of them earn their place.
Microsoft's Argos and the verification layer AI agents actually need
The framework trains AI agents to be right for the right reasons — not just right by coincidence. For AI governance, that distinction is everything.
Not all AI agents carry the same legal risk
Not all AI agents carry the same legal risk. Your governance framework should distinguish between reflex agents, learning agents, and multi-agent systems — because the liability profile is fundamentally different. https://www.databricks.com/blog/types-ai-agents-definitions-roles-and-examples
Observational memory changes the AI governance equation
AI agents are moving from retrieving data to building memories about users. Most privacy frameworks weren't designed for that shift — and the gap is widening fast.
When agents forget, who's accountable?
Engineers call this context management. Lawyers should call it something else: selective deletion with no retention policy.
Memory-driven AI agents create governance problems, not just engineering ones
AI agents with memory aren't just smarter — they're harder to govern. Each memory layer creates distinct privacy and retention obligations product counsel needs to address at the architecture stage.
