We just cracked how to make a great Meta ad using Jev ( a

@ajaypv4 Ajay Ponna Venkatesh · Sep 20, 2026 · case #863083 · listed via Jev Hub

Still from the clip posted with this case; watch it in the original post on X.

Graded 302 Meta ads from 8 beauty brands with Jev across 9 dimensions to find what makes ads work.

The original post

We just cracked how to make a great Meta ad using Jev ( a classifier model from TypeSafe AI. ) We pulled around 2,000 real ads from 8 beauty brands off Meta’s Ad Library and graded 302 of them with Jev across 9 dimensions: hook, format, funnel stage, CTA, claim risk and

Engagement when collected

Likes1

Bookmarks0

Reposts0

Replies0

Quotes0

Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.

Where this case fits

Filed under classification & data extraction, sales, ads & marketing. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the classification & data extraction page.

🗂️ Classification & data extraction 📈 Sales, ads & marketing