Earned Autonomy

说明与用途

基于四阶证据阶梯的LLM内容自动发布流程，从人工审核到完全自主发布的逐步转变。

问题

How to safely let an LLM publish content to production without human oversight while ensuring quality and trust.

结果

After implementing a rung-based evidence ladder, the pipeline achieved fully autonomous article publishing with consistent quality metrics (groundedness 0.98, banned phrases 0, cost $2.26 per article).

工作流

• 1. Run LLM in shadow mode, log outputs
• 2. Compare shadow outputs to existing production, score with judges
• 3. Promote to advisory if shadow passes thresholds
• 4. Move to assisted: run with checks, allow human veto
• 5. Reach autonomous rung: publish without human intervention
• 6. Continuously monitor scorecard and demote if metrics slip

证据

The rewrite stage of my pipeline is on rung four. The ops-doctor that diagnoses its failures is on rung one.

来源

The scorecard has been green for long enough to trust, against a threshold you set before you saw the numbers.

来源