Checklist the per-video bar — engine/sim
82.6/100
quantitative quality · weights learn from your reviews (
engine.sim.memory review thread-minus-the-hype-W47-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
9:16 Reelrendered1:1 Squarepending16:9 Widepending9:16 4Kpending1:1 4Kpending16:9 4KpendingGIF (SMS)pending
expected output: 1/7 rendered — same matrix the /media preview surfaces for this asset.
Composition layer × scene 5 scenes · 29.7s · 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 | hook | 0–6.4s | kinetic-build | icon·liquid-chrome | ♪ node_lock | The dream is simple: let AI write the whole test suite, so coverage hits a hundred by morning. on-screen: "AI writes all your tests" |
expected on screen: black ground · dodeca hero in the shared Signal Field · Mensor leads · mark · kinetic-build · icon·liquid-chrome logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape dodecaground blacktreatment liquid-chromemotion kinetic-buildpower laser-lockinstrument laser-trace→"AI writes all your tests" | |||||||
| 2 |  matches intent BuildLog template | diff | 6.4–14.3s | crossfade-8f | icon·ember-fill | ♪ node_lock | Here is the real move: the model writes the setup, but a person writes the checks the code must pass. on-screen: Reality: you write the assertions |
expected on screen: black ground · a BuildLog panel over a dimmed Signal Field · Mensor leads · code · crossfade-8f · icon·ember-fill logo · caption bottom-left spec (the prompt): comp_id BuildLogvisual codeshape dodecaground blacktreatment ember-fillmotion crossfade-8fpower morphinstrument morph→Reality: you write the assertionscurate codeLines, lines | |||||||
| 3 |  matches intent ChecklistCard template | teach | 14.3–19.700000000000003s | kinetic-build | icon·wireframe | ♪ node_lock | The real cost of AI-generated coverage is a green build that breaks in production anyway. on-screen: The cost: false confidence |
expected on screen: black ground · a ChecklistCard panel over a dimmed Signal Field · Mensor leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id ChecklistCardvisual node-graphshape dodecaground blacktreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→The cost: false confidencecurate items, nodes | |||||||
| 4 |  first render · fix pending KpiGrid templatedead_airgeneric_scene | proof | 19.7–24.7s | receipts-count | icon·white-knockout | ♪ node_lock | Minus the Hype |
expected on screen: black ground · a KpiGrid panel over a dimmed Signal Field · Mensor leads · receipts · receipts-count · icon·white-knockout logo · caption bottom-left spec (the prompt): comp_id KpiGridvisual receiptsshape dodecaground blacktreatment white-knockoutmotion receipts-countpower receiptsinstrument spotlight→Minus the Hypecurate kpis, statsLabels | |||||||
| 5 |  first render · fix pending shared field signature-3ddead_airgeneric_scene | resolve | 24.7–29.7s | coalescence | icon·white-knockout | ♪ bed_out | Minus the Hype |
expected on screen: black ground · dodeca hero in the shared Signal Field · Mensor leads · coalescence · coalescence · icon·white-knockout logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual coalescenceshape dodecaground blacktreatment white-knockoutmotion 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 dream: let AI write your whole test suite so coverage hits 100 overnight. The real move: the model writes the setup, a person writes the checks for what the code must do. Skip that and you get a green build that breaks in production. (AI-assisted)
instagram"AI writes all your tests"
The dream: 100% coverage by morning.
The reality: you write the assertions.
Model does setup.
Human decides what the code must do.
Skip it = false confidence.
#testing #AI #devtools #coding #qa
linkedinThe shortcut everyone wants: let AI generate the whole test suite so coverage hits 100% overnight. It does not hold.
What actually works: let the model write the setup and boilerplate, but a person writes the assertions, the checks for what the code must really do. That judgment is the test.
Skip it and you ship a green build that breaks in production anyway. Coverage is not correctness.
x"AI writes all your tests, 100% coverage overnight."
Real move: model writes the setup, a human writes the assertions. Skip that and you get a green build that breaks in prod. temerarii.xyz
facebookEveryone wants AI to write the whole test suite so coverage hits 100% overnight. Here is the honest version: let the model write the setup, but a person writes the checks for what the code must really do. Otherwise you get a green build that breaks in production. Learn the method at temerarii.xyz.
threads"AI writes all your tests" is the dream: 100% coverage by morning.
The real move: the model writes the setup and boilerplate, but a person writes the assertions, what the code must actually do. Skip that and the green build just breaks in production instead. Coverage is not the same as correct.
pinterestHow to use AI for unit testing without false confidence: let the model write test setup and boilerplate, but have a human write the assertions that define what the code must do. Why 100% AI-generated coverage gives you a green build that still breaks in production. Software testing best practices.
blueskyThe dream: AI writes all your tests, 100% coverage overnight. The real move: model writes the setup, a human writes the assertions. Skip that and the green build breaks in prod anyway.
youtubeTitle: AI Test Generation: Why You Still Write the Assertions
The shortcut everyone wants is letting AI write the whole test suite so coverage hits 100% overnight. We break down the real practice: the model writes setup and boilerplate, but a human writes the assertions that decide what the code must actually do. Skip that step and you ship a green build that breaks in production. AI coding, unit testing, test coverage. temerarii.xyz.