THE JEV DEMOS SENT ME DOWN A RABBIT HOLE now i have 144

The clip posted with this case (hosted by the collector’s media CDN); original post on X · 22s.

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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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