Practical guide
Verify an AI-generated summary
Verify against a frozen reviewed set. Check every factual field, URL, number, date, and attribution; reject unsupported output rather than editing it into something that only looks like the model produced.[1][2]
Why this gets difficult
An AI summary can be fluent, cited, and wrong at the same time. Links may be real but unrelated, qualifications can disappear, and generated certainty can exceed the source.[1][2]
A practical way through
- Capture canonical URLs and readable source bodies before generation.[1][2]
- Compare each summary claim with the cited source and surrounding context.[1][2]
- Validate that every rendered URL existed in the source material Scottie read.[1][2]
- Reject and rerun output with invented detail, lost disagreement, or weak provenance.[1][2]
An example
The situation: A summary gives a confident price, launch date, and analyst conclusion while linking only a general product page.[1][2]
What changes: The input snapshot is checked for each claim, missing support causes rejection, and links are reattached programmatically from verified records.[1][2]
What you get: The published brief contains fewer claims but can withstand source-by-source inspection.[1][2]
What to watch for
Sources worth keeping
How Scottie helps
Scottie briefs validate source URL provenance and protect completed digest output from manual rewriting; weak output is rejected and rerun.[3]