Policy Drift Ledger

What it does

Policy Drift Ledger is a governance layer for operational tooling that depends on evolving rules, prompts, and retrieval context. Instead of treating model behavior as something opaque, the system records every recommendation with the exact configuration that produced it.

The result is a workflow that feels much more like a controlled operations platform than a black-box assistant. Reviewers can inspect source evidence, see which policy version applied at the time, and compare today's behavior against historical runs.

Core workflow

1. A workflow run starts with a policy-aware review request.
2. The service snapshots the active policy version, prompt template, retrieval parameters, and model settings.
3. Evidence references and generated recommendations are written to an append-only log.
4. A human reviewer accepts, edits, or overrides the recommendation.
5. Drift jobs compare behavior across versions and surface meaningful deltas in dashboards.

Architecture notes

The most important modeling choice is separating machine suggestions from decisions of record. That keeps the human review step explicit and prevents downstream systems from pretending that a draft recommendation is equivalent to an approved outcome.

The second major choice is using append-only events. For drift analysis, mutable rows are not enough. Teams need to reconstruct what the system knew, what it suggested, and what changed later.

Suggested metrics

• Recommendation override rate by policy version
• Outcome deltas after prompt or retrieval changes
• Time to investigate unexpected behavior shifts
• QA sampling coverage by workflow type