AI

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.

The authors suggest treating AI agents as "legal actors" — entities that bear duties — without granting them legal personhood.

Contextual AI's Agent Composer makes the case that the real enterprise AI bottleneck isn't the model — it's context, auditability, and governance baked into the infrastructure from day one.

Enterprise AI doesn't need models that can do everything. It needs models scoped to the problem. Constraint isn't a limitation — it's a governance feature.

Most companies are still debating whether to adopt AI agents. Reload is already building the HR platform to manage them. That's the gap between strategy decks and product roadmaps.

Engineers call this context management. Lawyers should call it something else: selective deletion with no retention policy.

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.

AI and platform engineering are converging. For governance teams, that means the platform — not the policy doc — is where your AI guardrails actually live. The architecture matters.