Showcase · AI Output Review
How the product marketing team at Clockfold Technologies gets a human AI Output review of model-drafted release notes before they reach customers.
Fictional example: Clockfold Technologies and the people named here are invented. The documents and findings are illustrative and do not come from a QueryTek client.
Clockfold Technologies product marketing used an internal large language model to draft customer-facing release notes for its scheduling product. The risk team wants a person to check accuracy, unsupported claims, and tone before publication.
Product marketing removes two claims the release did not support, replaces the generic opening, and publishes release notes that match the changelog.
1. Bailey Robbins · Client user
Uploads the model-drafted release notes in the portal.
2. Oliver Winslow · Review lead
Assigns the document to a trained reviewer.
3. Daniel Dunwoody · Reviewer
Checks each claim against the source changelog, flags unsupported claims and tone problems, and submits the scorecard.
4. Oliver Winslow · Review lead
Checks the scorecard and approves it for delivery to the client.
Every finding is written by a trained reviewer and approved by a review lead before the client sees it.
Fictional example: Clockfold Technologies and the people named here are invented. The documents and findings are illustrative and do not come from a QueryTek client.
AI Output Evaluation Report
AI Output Review
6.1 / 10 overall
| Dimension | Score |
|---|---|
| Voice specificity | 5 |
| Structure and rhythm | 7 |
| Lexical tics | 5.5 |
| Reasoning depth | 6 |
| Audience presence | 6.5 |
| Trust calibration | 4.5 |
Critical
Scheduler 4.2 is 100% secure and never loses data.
Absolute claim with no support in the changelog. Remove it, or name the specific control this release adds.
High
Calendars now sync up to 10x faster.
The source gives no measurement. Ask engineering for the benchmark or drop the number.
Medium
In today’s fast-paced world, time is everything.
Generic opener typical of unedited model output. Lead with what changed for the customer.
Low
“Robust” appears six times in 400 words.
Repeated filler word. Replace with the specific behavior each time or cut it.
Positive
Upgrade steps: back up, install, re-link calendars.
Accurate against the changelog and easy to follow.
The upgrade section is accurate. Two claims are unsupported and one is an absolute security promise; remove or substantiate them before publishing.
