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CLASS 6June 10 · Creative AI Video + Coded Design

"You can't generate a photo with code,but you can generate an image with a lot of depth."

Sydney Seifert-Gram
Taught bySydney Seifert-GramArt director, photographer, designer
Educator, Creative AI Academy
Tony Jones
WithTony JonesCo-instructor, Pratt AI Design Certificate

The class in brief

Sydney's third night moved from coded, structure-first visuals into full video craft: keyframes as living stills, the six-part video prompt structure, an audio-prompt companion, and the night's biggest idea, character consistency, demonstrated start to finish on a single woodcut mouse named Baxter. The closing thesis was editing: AI output is a first draft, not a finish. After this page you can write a video prompt in six deliberate slots, build a character turnaround sheet before animating anything, and protect a flat illustration style from drifting toward realism mid-motion.

The night at a glance

Why this matters · 6:25 PM

Describe the structure, not the finished look, and the result stays editable.

Coded generation flips the usual instinct: instead of describing what a finished image looks like, you describe what's underneath it, the core information, the hierarchy, the rules . A generated image is flattened and hard to change; coded output stays in editable parts you can revise through conversation .

The demo was a fully interactive perfume bottle prototype, built by chaining Claude for process logistics, Midjourney for ideation, and ChatGPT for tech specs, material, and lighting, into one working browser demo you could rotate and relight.

4
questions a coded visual has to answer: what's the content, what's the structure, what's it for later, does it need to be interactive.
3
tools chained into one prototype: Claude for logistics, Midjourney for ideation, ChatGPT for the material and lighting specs.

The craft · 6:53 PM

A keyframe is pinned to a timestamp. A reference just guides the mood.

Keyframes are living stills: frozen moments that still carry motion potential, and they can start, continue, or resolve a sequence . A reference guides palette and mood and may never appear in the final output; a keyframe is pinned and locks composition, pose, and camera before the AI animates between two of them .

Prompting for keyframes runs on three principles: create with intention, consider what happens before and after the frame, and verbs matter . Load the still with elements whose physics imply movement, helium balloons, powdery snow, a walking gait, so the video has somewhere to go.

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rules for prompting a keyframe: create with intention, think before and after, and let verbs carry the motion.
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still can perfect a look before you spend a single generation on the full video. Efficiency is the whole point of anchoring first.

The framework · 7:05 PM

The video prompt structure

01

Formatwhat kind of visual

A TikTok video, an establishing shot, a timelapse, a Go-Pro clip, expired film. Sets the frame everything else lives in.

02

Subjectthe hero

A cowboy, a candle, a carousel, a carnival, a puppy, an apple tree. Whoever or whatever the video is about.

03

Detailswhat's happening

Floating in space, at the lake, in the kitchen. The scene around the subject.

04

Motionwhat moves, what the camera does

Flickering, dolly in, Dutch tilt, crash zoom, dancing. Say "static camera" explicitly if you want none.

05

Stylethe vibe, colors, textures, feelings

Dark and moody, high key, film noir, vintage camcorder. Same slot as the image framework's style row.

06

Parameterswhat else to establish

16:9, 4k, low motion, 24 fps, 1:1, loop. The technical spec the model needs to hit.

The full six-block video prompt structure
The full six-block video prompt structure · 7:05 PM

Three pitfalls got named right after the framework: overloaded prompts confuse the AI with too many ideas at once, static keyframes yield almost no movement to animate, and unclear timing leaves the AI unable to stitch events in order .

The craft · 8:09 PM

Models hold WHO better than HOW.

Character consistency was the night's biggest idea, demonstrated live on a woodcut mouse named Baxter, chained through four tools. Gemini analyzed the illustration style from an early Midjourney design to bank reusable prompt language , then ChatGPT built the character turnaround sheet, front, side, back, as the master reference .

Locking the subject took multiple reference angles up front, five white animals shot the same way, so the model couldn't invent features later , then combining references to test what carried over .

The last step tailored the prompt to the render model itself: Claude was handed the mouse keyframe and asked to write the Seedance-specific prompt, formula-style, subject plus action plus environment plus camera plus lighting plus style .

4
models chained into one character pipeline: Midjourney to explore, Gemini to analyze style, ChatGPT to build the turnaround sheet, Claude to write the render prompt.
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reference angles shot up front, before a single video frame, so the model had no room left to invent.

The exercise · 8:24 PM

Keeping the same character across two videos

The activity

25 minutes: lock a character, then animate it into two different scenes.

Build your reference set in ChatGPT, Copilot, or Gemini first, then generate the two clips .

Deliver a gif or a link, plus notes on what held and what drifted between the two scenes.

The audio prompt structure

Environment, what's making the sound, texture, and mix, the same order as the visual framework . Three habits on top of it: visuals come first, label your audio ("Music:", "Sound Effects:"), and put spoken dialogue in quotes.

Editing is the real craft

"AI generations are infinitely better when we edit them, take them apart, and put them back together in ways only we as humans can" . Demonstrated on a full retexture (photo to stylized doll) and a logo composited onto a shirt, then animated .

Two ways to upscale

Traditional upscaling preserves and predicts pixels; generative upscaling reimagines detail that was never there . Sydney's own pick is Topaz, which now lives inside Photoshop too.

Methods and prompts

Five methods to take with you

METHOD 01 · TAUGHT 7:05 part of: structure your ask

Write it as Format, then Subject, Details, Motion, Style and Parameters

The video companion to the image and text frameworks. Motion is the new slot: name what moves and what the camera does, or say "static camera" if you want neither.

Where it came fromSydney presented the video prompt structure as the motion companion to the image and text frameworks, adding motion as its own slot so you name what moves and what the camera does, or explicitly say static camera if you want neither.Use it whenUse this as the starting structure any time you write a prompt for a video generation model.

Working prompt

Format: [TikTok video, establishing shot, timelapse]. Subject: [the hero]. Details: [what's happening around it]. Motion: [what moves, what the camera does, or "static camera"]. Style: [vibe, colors, textures]. Parameters: [aspect ratio, fps, loop].

You will know it worked whenthe output moves the way your Motion field described, or holds a static camera if that's what you specified, with nothing else drifting.

METHOD 02 · TAUGHT 8:11 part of: context beats prompts

Build the turnaround sheet before you animate anything

Lock a character's front, side, and back as one master reference sheet before generating a single scene. Everything downstream points back to this one file.

Where it came fromSydney's character-consistency pipeline, demonstrated with her dog Baxter, has you lock a character's front, side, and back view as one master turnaround sheet before generating a single scene, so every later scene points back to that one reference file.Use it whenUse this before animating any character across multiple scenes, so its appearance does not drift from shot to shot.

Working prompt

Here's my character design [attach]. Analyze its style first: line weight, color, texture, era. Then build a full turnaround sheet, front, side, and back view, same style and proportions throughout. This becomes my master reference for every scene after this.

You will know it worked whenthe front, side, and back views hold the same line weight, color, and proportions as each other, not three slightly different characters.

METHOD 03 · TAUGHT 8:17 part of: build tools not chats

Let one model write the prompt for another

Hand your keyframe and your goal to a smart model like Claude or ChatGPT, and let it write the render-model-specific prompt. Different video models want different formulas.

Where it came fromSydney showed that different video render models want their own specific prompt formula, so she hands her keyframe and her goal to a smart model like Claude or ChatGPT and has it write the prompt formatted for the specific render model she is using.Use it whenUse this when you have a keyframe and a goal for a video model but are not sure how that particular model wants its prompt formatted.

Working prompt

Here's my keyframe [attach] and what I want to happen next: [describe the action]. Write me a prompt formatted for [Seedance/Kling/Runway], following its formula: subject, action, environment, camera, lighting, style. Flag anything that risks breaking character consistency.

You will know it worked whenit names a specific risk to character consistency, not just a generic caution, before handing over the formatted prompt.

METHOD 04 · TAUGHT 8:06 part of: structure your ask

Structure the audio prompt separately

Environment, what's making the sound, texture, mix. Visuals get designed first; the audio prompt describes what should support them, not lead them.

Where it came fromSydney taught the audio prompt structure as its own separate framework, environment, what is making the sound, texture, and mix, and stressed that visuals get designed first, with the audio prompt written to support them rather than lead them.Use it whenUse this once your visual prompt is set and you are ready to add sound, music, or dialogue on top of it.

Working prompt

Environment: [ambient baseline]. What's making the sound: [footsteps, a door, wind]. Texture: [joyous, muffled, sharp, gritty]. Mix: [foreground or background, loud or subtle]. Music: [label it]. Dialogue: "[quote exactly what's spoken]."

You will know it worked whenthe generated audio matches what you specified in each field, especially the exact words in Dialogue rather than a paraphrase.

METHOD 05 · TAUGHT 8:57 part of: reject the first draft part of: keep the judgment human

Diagnose the edit yourself first

Before asking AI to fix a rough output, name what's actually wrong with it. The output is a first draft; your read on what needs editing is the part only you can supply.

Where it came fromSydney's closing point on editing was that the AI output is only a first draft, and that before asking AI to fix a rough result you should name what is actually wrong with it yourself, since that read is the part only the human can supply.Use it whenUse this before sending a rough AI output back for a fix, so you go in with your own diagnosis instead of a vague request to improve it.

Working prompt

Here's my raw output: [attach]. I answer first, then you check me. My read on what needs fixing: [color, composite, retexture, trim, pacing]. Tell me if I'm right, then help me execute it as an edit, not a full regeneration.

You will know it worked whenit confirms or corrects your read on what's broken, then executes a targeted edit instead of regenerating the whole piece from scratch.

Where it broke · all night

A flat illustration wants to become photographic the moment it moves

Claude's own Seedance prompt for the woodcut mouse came back with a caveat built into the output: style persistence drift, keep camera movement minimal, the linocut border is fragile . Video models are trained mostly on photographic and 3D motion, so a flat 2D style drifts toward realism as soon as it starts animating, and the only real fix is holding the camera static and pre-flighting the prompt in a smart model before you generate.

Sydney named the honest state of the medium plainly: "we're still in the six-finger era of video," the same early, glitchy stage AI images went through before the errors washed out.

Try this prompt

Quiz me on the video prompt structure and the character-consistency pipeline. Then give me an illustrated character and make me plan the reference set and the camera constraints before I generate a single frame.

You will know it worked whenit quizzes you on the video prompt structure and the character-consistency pipeline first, then makes you plan the reference set and camera constraints before you generate anything.

The shelf

Tools and references

Tools that night

  • Video models named: Krea, Seedance / Seedance 2, Hailuo, Kling, Veo, Wan, Runway (+ Aleph), Gemini / Omni, Midjourney
  • Claude Opus 4.8 and ChatGPT for prompt-writing and layered output
  • Topaz upscaler, inside Krea and now inside Photoshop

Named in the room

  • Ancestra, Primordial Soup x Google DeepMind: the 3D-previz to Veo to live-action composite pipeline
  • Baxter, Sydney's own demo character, a woodcut mouse built from a single reference set
  • The Miro board's cheat sheets: camera placement, focus and lens, cinematic language, the turnaround sheet card
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