Minus the Hype — thread-minus-the-hype-W50-Mon

post thread-minus-the-hype-W50-Monkind threadweek W50date 2026-12-14campaign thread · Monpillar staff_trainingbeat Monasset videoduration 27.7sground blackscenes 5

Checklist the per-video bar — engine/sim

81.6/100

plain languagevo coverageno dead airuniquenesscaption fitcompletenesscleanliness

quantitative quality · weights learn from your reviews (engine.sim.memory review thread-minus-the-hype-W50-Mon good|bad)

⚠ 6 flag(s) — not yet ship-ready: copy_genericlow_vo_coveragedead_airgeneric_scene · see docs/strategy/VIDEO-CHECKLIST.md

Composition comp · template family · expected output

composition SceneReelfamily / template BoldStatement

9:16 Reelrendered1:1 Squarepending16:9 Widepending9:16 4Kpending1:1 4Kpending16:9 4KpendingGIF (SMS)pending

▶ open rendered mp4

expected output: 1/7 rendered — same matrix the /media preview surfaces for this asset.

Composition layer × scene 5 scenes · 27.7s · comp_id + rendered still + tier + the script

#	Layer (comp_id · still · tier)	Beat	Timecode	Motion	Logo	Audio	VO / on-screen / caption
1	still pending matches intent shared field signature-3d	hook	0–5.0s	kinetic-build	icon·liquid-chrome	♪ node_lock	The pitch: AI builds the dashboard and tells you what to do. on-screen: "AI handles your analytics dashboard"
	expected on screen: black ground · knot hero in the shared Signal Field · Magister leads · mark · kinetic-build · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape knotground blacktreatment liquid-chromemotion kinetic-buildpower laser-lockinstrument laser-trace→"AI handles your analytics dashboard"
2	still pending matches intent CodeWindow template	diff	5.0–11.4s	crossfade-8f	icon·ember-fill	♪ node_lock	Our real flow: a human chooses the one north-star metric, and the model writes the query and the chart on-screen: Reality: pick the metric, then query
	expected on screen: black ground · a CodeWindow panel over a dimmed Signal Field · Magister leads · code · crossfade-8f · icon·ember-fill logo · caption bottom-left spec (the prompt): comp_id CodeWindowvisual codeshape knotground blacktreatment ember-fillmotion crossfade-8fpower morphinstrument morph→Reality: pick the metric, then querycurate codeLines, windowTitle
3	still pending matches intent ChecklistCard template	teach	11.4–17.7s	kinetic-build	icon·wireframe	♪ node_lock	The real cost of an auto-built dashboard is forty charts and zero decisions. Name your one metric first. on-screen: The cost: charts no one reads
	expected on screen: black ground · a ChecklistCard panel over a dimmed Signal Field · Magister leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id ChecklistCardvisual node-graphshape knotground blacktreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→The cost: charts no one readscurate items, nodes
4	still pending first render · fix pending ComparisonTable templatedead_airgeneric_scene	proof	17.7–22.7s	receipts-count	icon·white-knockout	♪ node_lock	Minus the Hype
	expected on screen: black ground · a ComparisonTable panel over a dimmed Signal Field · Magister leads · receipts · receipts-count · icon·white-knockout logo · caption bottom-left spec (the prompt): comp_id ComparisonTablevisual receiptsshape knotground blacktreatment white-knockoutmotion receipts-countpower receiptsinstrument spotlight→Minus the Hypecurate colA, colB, rows, statsLabels
5	still pending first render · fix pending shared field signature-3ddead_airgeneric_scene	resolve	22.7–27.7s	coalescence	icon·ember-fill	♪ bed_out	Minus the Hype
	expected on screen: black ground · knot hero in the shared Signal Field · Magister leads · coalescence · coalescence · icon·ember-fill logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape knotground blacktreatment ember-fillmotion coalescencepower coalescenceinstrument coalescence→Minus the Hype

Format stack 3 aspects · same scenes[], re-cropped

9:16

1080×1920

Stories · TikTok · YouTube Shorts · Reels

1:1

1080×1080

LinkedIn · Facebook · Instagram

16:9

1920×1080

X/Twitter · YouTube · LinkedIn video

Channels 9 destinations

LinkedInX/TwitterYouTubeInstagramFacebookThreadsTikTokPinterestBluesky

Social captions supplemental published copy · per channel (comp_id level)

tiktokThe pitch: AI builds your analytics dashboard and tells you what to do. The real flow: a human picks one north-star metric, then the model writes the query and the chart. Skip that and you get 40 charts no one reads. (AI-assisted)

instagram"AI handles your analytics dashboard." The real flow: A human picks the one metric that matters. Then the model writes the query and the chart. Skip that step and you get 40 charts and zero decisions. Name your one metric first. #analytics #dashboards #datatips #marketingdata #thebigtm

linkedinThe pitch: AI builds your analytics dashboard and tells you what to do. Here is the real flow we use. A human picks the one north-star metric first. Then the model writes the query and builds the chart around it. The takeaway: the cost of an auto-built dashboard is 40 charts and zero decisions. The model is good at building charts and bad at knowing which one matters. Name your one metric before you let it build anything.

x"AI handles your analytics dashboard." Real flow: a human picks the one metric, then the model writes the query and chart. Skip that and you get 40 charts no one reads. Name your metric first. temerarii.xyz

facebookThe pitch is that AI builds your dashboard and tells you what to do. The real flow: a person picks the one metric that matters, then the model writes the query and the chart. Skip that and you end up with 40 charts and no decisions. Name your one metric first, then let the tool build.

threads"AI handles your analytics dashboard." Real flow: a human picks the one north-star metric, then the model writes the query and the chart. The cost of skipping that? 40 charts and zero decisions. Name your one metric first.

pinterestAI analytics dashboards explained without the hype: a human picks the one north-star metric first, then the model writes the query and builds the chart. Skip that step and you get forty charts and zero decisions. Name your one metric first for dashboards that drive action.

bluesky"AI handles your analytics dashboard." Real flow: a human picks the one metric, then the model writes the query and chart. Skip it and you get 40 charts no one reads. Name your metric first.

youtubeTitle: AI Dashboards: Pick One Metric Before the Model Builds Anything The pitch says AI builds your analytics dashboard and tells you what to do. Here is the real flow: a human picks the one north-star metric first, then the model writes the query and the chart around it. Skip that step and you get forty charts and zero decisions. Name your one metric first. More method at temerarii.xyz

Cross-links every lens is a view on this one record

→ Wireframe · scenes → Calendar week → Media (audience preview)→ Storyboard hub → Day view → Channel view