D2 Product Preview | Manual Software: Agentic Safety, Semantic Authorization & Guardrails for Real-World AI Actions

In this session, we explored why agentic AI can be risky: models can sound confident while hallucinating, skipping required steps, or overstepping their authority. We covered semantic authorization, granting permissions based on meaning, context, and output quality, and demoed a control-plane pattern that enforces pre-checks, calibrates thresholds against known-good responses, and records a full audit trail tied to a human owner for real workflows.