THE JEV DEMOS SENT ME DOWN A RABBIT HOLE now i have 144
Mapped 144 YouTube videos into a topic wall and generated three video ideas, using precomputed title labels rather than a live Jev run.
The original post
THE JEV DEMOS SENT ME DOWN A RABBIT HOLE
now i have 144 youtube uploads turning into a content map on one screen
here’s the concept i built ↓
144 real videos from 4 AI channels
→ thumbnails form a wall
→ titles get tagged by topic and hook
→ the wall reorganizes into a topic map
→ three video ideas close out the sequence
the part i like most: you can see the source material behind the ideas
this is a concept demo with precomputed, title-based labels — not a live Jev run or a speed benchmark
next experiment: pick one idea, build it, show the result
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Engagement when collected
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, video, animation & media. 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.
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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post