Progressive Delegation

Problem

One-shot deployment swings between two failure modes. Going fully autonomous on day one yields trust incidents because the team has no measured basis for confidence. Going fully supervised forever yields no learning — the team never accumulates the success-rate data that would justify expansion, and the agent's value is capped at 'faster drafter'. Without a per-action ratchet, autonomy decisions are calendar-driven, not evidence-driven.

Solution

Tag each action class with a current autonomy level (draft -> assisted-send -> autonomous). For each class the runtime tracks a rolling success-rate window. Promotion fires automatically when the window clears a bar over enough samples; demotion fires when it drops below. The promotion mechanism is the policy of record, not a verbal decision in standup. The same agent runs many action classes at different levels simultaneously.

When to use

• Multiple action classes with materially different risk.
• Per-class success can be measured online with reasonable delay.
• Stakeholders want autonomy to be a measurement, not a meeting decision.