From Exception To Foundation: What Mac Teaches Enterprise AI
Some systems look like exceptions until they reveal the architecture everyone else needs next.
Artifact library
Public notes, reference artifacts, and future repository-backed writeups. The goal is to explain intent, constraints, signals, decisions, actions, and evidence without exposing private implementation details.
Some systems look like exceptions until they reveal the architecture everyone else needs next.
Device trust becomes useful when it is visible, measurable, and connected to policy decisions.
GitOps gives enterprise workflows a durable place to express intent before automation turns it into action.
AI workflow execution is only enterprise-ready when permission, policy, approval, action, and evidence are part of the same system.
Evidence should be a system output, not a manual cleanup task after the control has already run.
The first step in automation is not scripting. It is modeling the workflow well enough that the system can govern it.