---
title: "Immutable Reports and Expert Approval: Turning Automated Results into Deliverables"
slug: "immutable-report-expert-approval"
language: "en"
tags: ["전문가 승인","sag 기술","아키텍처","플랫폼 운영"]
created: "2026-09-01T00:00:00.000Z"
published: "2026-10-08T10:00:31.043Z"
updated: "2026-10-08T10:00:38.993Z"
sample: false
---

# Immutable Reports and Expert Approval: Turning Automated Results into Deliverables

## Definition in one sentence

**Expert approval** is a delivery structure that stores automated outputs as immutable revisions and has a reviewer approve a specific hash.

> Key answer: If a draft changes while its previous approval remains in place, the result received by the customer may differ from the one that was reviewed.

## Why is this technology needed?

If a draft changes while its previous approval remains in place, the result received by the customer may differ from the one that was reviewed.

## How it works

Create a canonical hash of the content and evidence, and generate a new revision for each change. Bind approval to the revision hash, and require another review for changes made after approval.

When designing the system, consider more than accuracy. Define latency, cost, data boundaries, refresh intervals, and behavior in case of failure as well, so that results can be reproduced in production. It is safer to leave values that automation cannot determine with confidence as unmeasured or requiring review rather than changing them to 0 or success.

## Connection to SAG technology

SAG reports and approvals are linked by content hash. A report with missing critical evidence cannot be approved, and only approved revisions are eligible for customer export.

## Practical checklist

- Ensure that approval refers to the exact content hash
- Record changes as new revisions
- Confirm that approval fails when evidence is missing
- Distinguish failure, empty results, and permission errors from success
- Revalidate before and after changes under the same conditions

## Research and official documentation

- [Official Google guide to AI features in Search](https://developers.google.com/search/docs/appearance/ai-features)

The reference documents support the underlying principles and recommendations. They do not guarantee search visibility, AI mentions, rankings, or revenue. The actual effects of implementation should be verified using service data and observations under the same conditions.

## How to continue exploring this technology

Review tenant permissions, job retries, caching, and approval history.

- [Designing a stable customer space](/ko/blog?tag=%ED%94%8C%EB%9E%AB%ED%8F%BC%20%EC%9A%B4%EC%98%81)
- [Feature guide FAQ](/en/faq)