Back Office · office.temerarii.xyz
One asset, all the way in — composition, the wireframe + storyboard, the output format stack, and the template, all read from the SAME content-index record. The expected output matches what /media surfaces for this post.
post social-W25-Wed-4kind threadweek W25date 2026-06-24campaign thread · Wedpillar multimediabeat Wedasset videoduration 46.7sground redscenes 9

Checklist the per-video bar — engine/sim

98.5/100
plain languagevo coverageno dead airuniquenesscaption fitcompletenesscleanliness
quantitative quality · weights learn from your reviews (engine.sim.memory review social-W25-Wed-4 good|bad)
⚠ 1 flag(s) — not yet ship-ready: copy_generic · see docs/strategy/VIDEO-CHECKLIST.md

Composition comp · template family · expected output

composition SceneReelfamily / template SignalFieldReel
9:16 Reelpending1:1 Squarepending16:9 Widepending9:16 4Kpending1:1 4Kpending16:9 4KpendingGIF (SMS)pending
render pending — silent master not yet on disk
expected output: 0/7 rendered — same matrix the /media preview surfaces for this asset.

Composition layer × scene 9 scenes · 46.7s · comp_id + rendered still + tier + the script

#Layer (comp_id · still · tier)BeatTimecodeMotionLogoAudioVO / on-screen / caption
1s1
matches intent
shared field
signature-3d		open0–5.2sspatial-parallaxicon·white-knockout♪ bed_in
The old way of cutting a long interview ate days of scrubbing footage.
on-screen: Editing a long talk took days
expected on screen: red ground · octa hero in the shared Signal Field · Lumen leads · node-graph · spatial-parallax · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id shared Signal Fieldvisual node-graphshape octaground redtreatment white-knockoutmotion spatial-parallaxpower summoninstrument summon→Editing a long talk took days
2s2
matches intent
shared field
signature-3d		hook5.2–10.4skinetic-buildicon·white-knockout♪ node_lock
Here is the move now: we treat the transcript as the editing timeline.
on-screen: Now the transcript is the timeline
expected on screen: red ground · octa hero in the shared Signal Field · Lumen leads · mark · kinetic-build · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id shared Signal Fieldvisual markshape octaground redtreatment white-knockoutmotion kinetic-buildpower laser-lockinstrument laser-trace→Now the transcript is the timeline
3s3
matches intent
NumberedList
template		teach10.4–15.600000000000001skinetic-buildicon·liquid-chrome♪ node_lock
Transcribe the talk, then cut the boring lines as text, not as video.
on-screen: Transcribe first, then cut the words
expected on screen: red ground · a NumberedList panel over a dimmed Signal Field · Lumen leads · node-graph · kinetic-build · icon·liquid-chrome logo · caption bottom-left
spec (the prompt): comp_id NumberedListvisual node-graphshape octaground redtreatment liquid-chromemotion kinetic-buildpower morphinstrument morph+laser→Transcribe first, then cut the wordscurate items, nodes
4s4
matches intent
ComparisonTable
template		proof15.6–21.1sreceipts-counticon·white-knockout♪ node_lock
Delete a flat sentence in the text and the matching clip drops out too.
on-screen: Delete a sentence, the clip cuts too
expected on screen: red ground · a ComparisonTable panel over a dimmed Signal Field · Lumen leads · receipts · receipts-count · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id ComparisonTablevisual receiptsshape octaground redtreatment white-knockoutmotion receipts-countpower receiptsinstrument spotlight→Delete a sentence, the clip cuts toocurate colA, colB, rows, statsLabels
5s5
matches intent
LogStream
template		diff21.1–26.3scrossfade-8ficon·liquid-chrome♪ node_lock
Reading is faster than scrubbing. You find the gold by skimming, not seeking.
on-screen: Editing words is faster than scrubbing
expected on screen: red ground · a LogStream panel over a dimmed Signal Field · Lumen leads · code · crossfade-8f · icon·liquid-chrome logo · caption bottom-left
spec (the prompt): comp_id LogStreamvisual codeshape octaground redtreatment liquid-chromemotion crossfade-8fpower morphinstrument morph→Editing words is faster than scrubbingcurate codeLines, rows
6s6
matches intent
ChecklistCard
template		teach26.3–31.3skinetic-buildicon·white-knockout♪ node_lock
Let a model read the transcript and mark the lines worth keeping.
on-screen: Let AI mark the strong quotes
expected on screen: red ground · a ChecklistCard panel over a dimmed Signal Field · Lumen leads · node-graph · kinetic-build · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id ChecklistCardvisual node-graphshape octaground redtreatment white-knockoutmotion kinetic-buildpower morphinstrument morph+laser→Let AI mark the strong quotescurate items, nodes
7s7
matches intent
KpiGrid
template		proof31.3–36.3sreceipts-counticon·liquid-chrome♪ node_lock
It surfaces the quotable moments so you build the cut around them.
on-screen: It surfaces the quotable moments
expected on screen: red ground · a KpiGrid panel over a dimmed Signal Field · Lumen leads · receipts · receipts-count · icon·liquid-chrome logo · caption bottom-left
spec (the prompt): comp_id KpiGridvisual receiptsshape octaground redtreatment liquid-chromemotion receipts-countpower receiptsinstrument spotlight→It surfaces the quotable momentscurate kpis, statsLabels
8s8
matches intent
CheatSheet
template		step36.3–41.5skinetic-buildicon·white-knockout♪ node_lock
Transcribe, let AI mark the strong quotes, then cut the dull text out.
on-screen: Transcribe, mark quotes, cut the text
expected on screen: red ground · a CheatSheet panel over a dimmed Signal Field · Lumen leads · pipeline · kinetic-build · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id CheatSheetvisual pipelineshape octaground redtreatment white-knockoutmotion kinetic-buildpower throwinstrument laser-trace→Transcribe, mark quotes, cut the textcurate points, stages, steps, uses
9s9
matches intent
shared field
signature-3d		resolve41.5–46.7scoalescenceicon·white-knockout♪ bed_out
The Big T-M edits the words first, and the video follows the text.
on-screen: The Big T-M edits the words
expected on screen: red ground · octa hero in the shared Signal Field · Lumen leads · coalescence · coalescence · icon·white-knockout logo · caption bottom-left
spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape octaground redtreatment white-knockoutmotion coalescencepower coalescenceinstrument coalescence→The Big T-M edits the words

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)

tiktokHow we cut a long interview fast (AI-assisted): edit the transcript, not the timeline. Transcribe it, delete the flat lines as text, the clips drop with them. Let AI mark the strong quotes. #videoediting #podcasting #contentcreation
instagramEdit the words, not the tape. Transcribe, cut flat lines as text. Clips drop with them. #videoediting #podcast #contentcreation #editing #filmmaking
linkedinCutting a long interview by scrubbing footage wastes days. The method: transcribe first and edit the transcript as text, so deleting a flat sentence drops the matching clip. The takeaway: reading is faster than scrubbing. Let a model mark the strong quotes so you build the cut around them.
xCut long interviews fast: edit the transcript, not the timeline. Delete flat lines as text, clips drop too. AI marks the quotes. temerarii.xyz
facebookScrubbing footage to cut a long interview eats days. We transcribe first and edit the words: delete a flat line as text and the clip drops with it. AI marks the strong quotes. Method's on the site.
threadsEditing trick: cut the transcript, not the timeline. Transcribe the interview, delete flat lines as text, and the clips drop with them. Let AI mark the quotable moments first.
pinterestVideo editing method: edit the transcript instead of the timeline. Transcribe your interview, cut flat lines as text, and the clips drop with them. Let AI mark the strong quotes. Video editing tips, podcasting workflow, content creation.
blueskyCut long interviews by editing the transcript, not the timeline. Delete flat lines as text, clips drop too. temerarii.xyz
youtubeEdit the Transcript, Not the Timeline (Fast Interview Cuts) Scrubbing footage to cut a long interview wastes days. We show the method: transcribe first and edit the transcript as text, so deleting a flat sentence drops the matching clip. Reading is faster than scrubbing. Let a model mark the strong quotes so you build the cut around the gold.

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

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