Change management frameworks were built for a world where the destination was known. ADKAR - Awareness, Desire, Knowledge, Ability, Reinforcement - assumes you are moving people from a defined current state to a defined future state. That works for an ERP rollout. It breaks when the thing you are changing to keeps changing.

The Governance Speed Problem addressed how fast governance can move. This post addresses a more fundamental question: what does readiness mean when the system being governed was not written by a human and is not maintained by a human? The Other Dimension series assumed a human authored the AI-assisted output and a human maintained it. At Sau Sheong's Levels 3 and above — autonomous agents and collaborative agent networks — that assumption breaks. The code being reviewed was written by an agent. The changes being proposed are written by an agent. The human reviewer is evaluating agent work on agent work. Every readiness component shifts meaning.

Readiness at Portfolio Scale argued that governance is a finite resource and must be triaged by consequence. This post confronts the next constraint: even well-triaged governance can become a bottleneck when the delivery pace is set by agents, not humans. Sau Sheong Chang identified decision speed as the binding constraint in AI-augmented development. The readiness framework tells you what to govern. This post asks how fast governance can move without becoming a rubber stamp.