Checklist the per-video bar — engine/sim
78.5/100
quantitative quality · weights learn from your reviews (
engine.sim.memory review thread-the-stack-W45-Tue good|bad)⚠ 7 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 6 scenes · 31.3s · 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 | 0–5.0s | kinetic-build | icon·wireframe | ♪ node_lock | The tool is your favorite language model. It writes great prose, but its loose text breaks the code that has to read it. on-screen: GPT prose breaks parsers |
expected on screen: white ground · knot hero in the shared Signal Field · Magister leads · mark · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldvisual markshape knotground whitetreatment wireframemotion kinetic-buildpower laser-lockinstrument laser-trace→GPT prose breaks parsers | |||||||
| 2 |  first render · fix pending NumberedList templatedead_air | teach | 5.0–10.0s | kinetic-build | icon·wireframe | ♪ node_lock | So we stop trusting the words. We hand the model a strict shape and make it answer in that shape every time. on-screen: Force a schema, validate |
expected on screen: white ground · a NumberedList panel over a dimmed Signal Field · Magister leads · node-graph · kinetic-build · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id NumberedListvisual node-graphshape knotground whitetreatment wireframemotion kinetic-buildpower morphinstrument morph+laser→Force a schema, validatecurate items, nodes | |||||||
| 3 |  matches intent StackTrace template | build | 10.0–16.0s | type-on | icon·wireframe | ♪ node_lock | Now the model's answer is guaranteed-shaped data your code can rely on, so the AI becomes on-screen: AI output you can trust |
expected on screen: white ground · a StackTrace panel over a dimmed Signal Field · Magister leads · code · type-on · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id StackTracevisual codeshape knotground whitetreatment wireframemotion type-onpower summoninstrument draw-on→AI output you can trustcurate codeLines, errMsg, errType, fix, frames | |||||||
| 4 |  matches intent StepFlow template | proof | 16.0–21.3s | receipts-count | icon·wireframe | ♪ node_lock | So take one LLM call that returns JSON and pin it to a schema with validation. on-screen: Add a schema to one call |
expected on screen: white ground · a StepFlow panel over a dimmed Signal Field · Magister leads · receipts · receipts-count · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id StepFlowvisual receiptsshape knotground whitetreatment wireframemotion receipts-countpower receiptsinstrument spotlight→Add a schema to one callcurate statsLabels, steps | |||||||
| 5 |  first render · fix pending shared field signature-3ddead_airgeneric_scene | futurist | 21.3–26.3s | spatial-parallax | icon·wireframe | ♪ bed | The Stack |
expected on screen: white ground · knot hero in the shared Signal Field · Magister leads · spatial-parallax · icon·wireframe logo · caption bottom-left spec (the prompt): comp_id shared Signal Fieldshape knotground whitetreatment wireframemotion spatial-parallaxpower spatial-parallaxinstrument laser-fire→The Stack | |||||||
| 6 |  first render · fix pending shared field signature-3ddead_airgeneric_scene | resolve | 26.3–31.3s | coalescence | icon·ember-fill | ♪ bed_out | The Stack |
expected on screen: white 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 whitetreatment ember-fillmotion coalescencepower coalescenceinstrument coalescence→The Stack | |||||||
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 stack: your favorite language model is great at prose but bad at clean data. So stop trusting the words. Hand it a strict schema and make it answer in that shape, then validate. Now the output is data your code can rely on. (AI-assisted)
instagramThe stack: get AI output you can trust.
The model writes great prose, bad clean data.
So stop trusting the words.
Hand it a strict schema. Validate the shape.
Now it's data your code can rely on.
#ai #llm #developers #json #buildinpublic
linkedinThe stack: how to get AI output your code can actually trust.
The tool is your favorite language model, great at writing prose but loose with structure. So we stop trusting the words. We hand the model a strict schema and make it answer in that exact shape, then validate.
Now the model's answer is guaranteed-shaped data your code can rely on. The move: take one LLM call that returns JSON and pin it to a schema with validation.
xThe stack: LLMs write great prose but loose JSON that breaks parsers. Fix: hand the model a strict schema, make it answer in that shape, then validate. Now it's data your code can trust. temerarii.xyz
facebookThe stack this week: getting AI output you can actually trust. Your favorite language model writes great prose but loose data that breaks parsers. So we stop trusting the words. We hand the model a strict schema, make it answer in that shape, and validate. Now the output is data your code can rely on. The move: take one LLM call that returns JSON and pin it to a schema. temerarii.xyz
threadsThe stack: AI output you can trust.
The model writes great prose but bad, loose data. So stop trusting the words.
Hand it a strict schema. Make it answer in that shape. Then validate.
Now it's guaranteed-shaped data your code can rely on.
pinterestHow to get reliable structured output from a language model: stop trusting loose prose, hand the model a strict schema, force it to answer in that shape, then validate. Turn one LLM JSON call into data your code can trust. Developer tips, LLM JSON schema, AI validation.
blueskyThe stack: LLMs write great prose but loose JSON that breaks parsers. Fix: hand the model a strict schema, make it answer in that shape, then validate. Now it's data your code can trust.
youtubeTitle: Make AI Output Your Code Can Trust (Schema + Validation)
The tool is your favorite language model, great at writing prose but loose with structure that breaks parsers. So we stop trusting the words. We hand the model a strict schema, make it answer in that exact shape, then validate. Now the model's answer is guaranteed-shaped data your code can rely on. Take one LLM call that returns JSON and pin it to a schema with validation.