DARMA™

DARMA is not a checklist. The sequence is the architecture.

Delegation comes first because no agent should act without a defined human intervention point. Before anything else, the system must know when to stop and ask.

Authorization comes second because principles must be encoded, not declared. A governance policy that lives in a document does not constrain an agent at runtime.

Runtime comes third because what an agent is permitted to do and what it actually does are not the same thing. Enforcement requires observation at the execution boundary.

Model Integrity comes fourth because the three layers above assume the model behaving is the model that was verified. That assumption must be tested, not trusted.

Accountability closes the loop because governance without consequence is theater. Every action requires a trace. Every trace requires an owner.

Consider an organisation that deploys an AI agent for customer support. Authorization is in place — only approved staff have access. Runtime logging is active. The Audit Ledger documents every session. Delegation is defined. Everything looks correct.

Three months later, the LLM provider updates the model. No one in the organisation is notified. The agent's responses shift subtly — it starts recommending products it never recommended before, or it handles complaints with a different tone. Logs still show AUTHORIZED. Because nothing in the other four layers checks whether the model's behaviour has changed.

With Model Integrity, Agent Shield Runtime would have flagged the process as DRIFTING within the first 24 hours after the model update. The organisation would have known before their customers noticed.