Checklist the per-video bar — engine/sim
86.5/100
quantitative quality · weights learn from your reviews (
engine.sim.memory review social-W36-Sun-2 good|bad)⚠ 3 flag(s) — not yet ship-ready: copy_genericdup_sequence_across_assetsdup_set_across_assets · see docs/strategy/VIDEO-CHECKLIST.md
Composition comp · template family · expected output
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 · 47.7s · comp_id + rendered still + tier + the script
| # | Layer (comp_id · still · tier) | Beat | Timecode | Motion | Logo | Audio | VO / on-screen / caption |
|---|---|---|---|---|---|---|---|
| 1 |  matches intent shared field signature-3d | open | 0–5.2s | spatial-parallax | icon·liquid-chrome | ♪ bed_in | Product roadmaps used to live in one person's head and a messy doc. on-screen: The roadmap lived in someone's head |
expected on screen: black ground · tetra hero in the shared Signal Field · Nexus leads · node-graph · spatial-parallax · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual node-graphshape tetraground blacktreatment liquid-chromemotion spatial-parallaxpower summoninstrument summon→The roadmap lived in someone's head | |||||||
| 2 |  matches intent shared field signature-3d | hook | 5.2–10.2s | kinetic-build | icon·wireframe | ♪ node_lock | Every meeting reopened the same fight about what ships next. on-screen: Every meeting reopened the same fight |
expected on screen: black ground · tetra hero in the shared Signal Field · Nexus leads · mark · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape tetraground blacktreatment wireframemotion kinetic-buildpower laser-lockinstrument laser-trace→Every meeting reopened the same fight | |||||||
| 3 |  matches intent NumberedList template | teach | 10.2–15.7s | kinetic-build | icon·wireframe | ♪ node_lock | Now we feed every support ticket and review into a model that clusters them. on-screen: Now AI reads every ticket |
expected on screen: black ground · a NumberedList panel over a dimmed Signal Field · Nexus leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id NumberedListvisual node-graphshape tetraground blacktreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→Now AI reads every ticketcurate items, nodes | |||||||
| 4 |  matches intent RankList template | proof | 15.7–21.2s | receipts-count | icon·wireframe | ♪ node_lock | It groups the raw complaints into themes a human can act on in minutes. on-screen: It groups the real pain |
expected on screen: black ground · a RankList panel over a dimmed Signal Field · Nexus leads · receipts · receipts-count · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id RankListvisual receiptsshape tetraground blacktreatment wireframemotion receipts-countpower receiptsinstrument spotlight→It groups the real paincurate rows, statsLabels | |||||||
| 5 |  matches intent CodeWindow template | diff | 21.2–26.4s | crossfade-8f | icon·wireframe | ♪ node_lock | Most teams still rank the backlog on gut feel and the loudest voice. on-screen: Gut-feel backlogs still rule most teams |
expected on screen: black ground · a CodeWindow panel over a dimmed Signal Field · Nexus leads · code · crossfade-8f · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id CodeWindowvisual codeshape tetraground blacktreatment wireframemotion crossfade-8fpower morphinstrument morph→Gut-feel backlogs still rule most teamscurate codeLines, windowTitle | |||||||
| 6 |  matches intent ChecklistCard template | teach | 26.4–31.4s | kinetic-build | icon·wireframe | ♪ node_lock | Score each item against your goal with a simple weighted prompt instead. on-screen: Score each item against goals |
expected on screen: black ground · a ChecklistCard panel over a dimmed Signal Field · Nexus leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id ChecklistCardvisual node-graphshape tetraground blacktreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→Score each item against goalscurate items, nodes | |||||||
| 7 |  matches intent StatScoreboard template | proof | 31.4–36.4s | receipts-count | icon·wireframe | ♪ node_lock | The backlog reorders itself by evidence, not by who shouted loudest. on-screen: The backlog sorts by evidence |
expected on screen: black ground · a StatScoreboard panel over a dimmed Signal Field · Nexus leads · receipts · receipts-count · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id StatScoreboardvisual receiptsshape tetraground blacktreatment wireframemotion receipts-countpower receiptsinstrument spotlight→The backlog sorts by evidencecurate pillar, stats, statsLabels | |||||||
| 8 |  matches intent StepFlow template | step | 36.4–42.699999999999996s | kinetic-build | icon·wireframe | ♪ node_lock | Try it: paste your last fifty tickets and ask the model for the top five themes. on-screen: Dump tickets, ask for clusters |
expected on screen: black ground · a StepFlow panel over a dimmed Signal Field · Nexus leads · pipeline · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id StepFlowvisual pipelineshape tetraground blacktreatment wireframemotion kinetic-buildpower throwinstrument laser-trace→Dump tickets, ask for clusterscurate stages, steps | |||||||
| 9 |  matches intent shared field signature-3d | resolve | 42.7–47.7s | coalescence | icon·liquid-chrome | ♪ bed_out | You decide faster and argue less, because the data did the sorting. on-screen: Decide faster, argue less |
expected on screen: black ground · tetra hero in the shared Signal Field · Nexus leads · coalescence · coalescence · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape tetraground blacktreatment liquid-chromemotion coalescencepower coalescenceinstrument coalescence→Decide faster, argue less | |||||||
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)
tiktokStop ranking your backlog on gut feel. Here is the move (AI-assisted): feed every ticket and review into a model, let it cluster the complaints into themes, then score each one against your goal. The backlog sorts by evidence, not who shouted loudest. #productmanagement #aitools #buildinpublic
instagramBacklog by gut feel is over.
Feed AI your tickets.
It clusters the real pain.
Score each one against the goal.
Evidence ranks the roadmap, not volume.
#productmanagement #aitools #pmlife #buildinpublic #startups
linkedinThe product roadmap used to live in one person's head. Now we cluster every ticket and review with a model, then score each theme against the goal with a simple weighted prompt. The takeaway: your backlog ranks by evidence, not by the loudest voice in the room. Receipts over hype.
xProduct backlog move: feed AI every ticket, let it cluster the complaints into themes, score each against your goal. Ranked by evidence, not who shouted loudest. temerarii.com
facebookProduct roadmaps used to live in one person's head. Now we feed every support ticket into a model, cluster the real pain into themes, and score each against the goal. The backlog sorts by evidence. See the method at temerarii.com.
threadsBacklog by gut feel is done. Feed AI your tickets, let it cluster the complaints, score each theme against the goal. Evidence ranks the roadmap now, not the loudest voice.
pinterestAI for product management: how to rank your backlog by evidence. Cluster support tickets into themes with a model, then score each against your goal with a weighted prompt. Evergreen guide to product roadmap prioritization and PM workflow automation.
blueskyProduct backlog move: feed AI every ticket, cluster the complaints into themes, score each against your goal. Ranked by evidence, not volume. temerarii.com
youtubeProduct Management With AI: Rank Your Backlog By Evidence
Roadmaps used to live in one person's head, and every meeting reopened the same fight. The real method: feed every support ticket and review into a model that clusters them into themes, then score each theme against your goal with a simple weighted prompt. Your backlog reorders by evidence, not by who shouted loudest. Paste your last fifty tickets and ask for the top five themes to start. More at temerarii.com.