Week 1
Story, taste, assets
A small story, a clear audience promise, core references, first character/world assets, and realistic scope.
A practical public toolkit for making a short AI-assisted animation: story scope, production economics, voice-first performance, review language, repair moves, platform literacy, reference pools, and the terms people use in the room.
Course Map
The accelerator is not a tool tour. It is a career-navigation and craft-values sprint where one small finished thing beats a perfect unfinished plan.
Week 1
A small story, a clear audience promise, core references, first character/world assets, and realistic scope.
Week 2
First-pass shots, cleaner references, voice or audio direction where performance matters, and a credit-aware iteration plan.
Week 3
A reviewed work-in-progress, a fix list in priority order, and a smallest shippable version.
Finish line
A private learning artifact, portfolio clip, Film Club submission, or showcase candidate with rights and consent checked.
Production Tools
Simple beats fancy here. These are the decisions people need when they are mid-render: what to spend on, what to fix, what to cut, and when to stop.
Use when: Before committing to a production plan, buying another subscription, or letting one shot eat the night.
Use when: Any shot where dialogue, narration, hesitation, or emotional timing matters.
Use when: Reviewing your own piece, giving peer feedback, opening office hours, or deciding what to fix before deadline.
Use when: A still is almost right but one region is wrong: hand, prop, face detail, costume piece, object position, or continuity detail.
Use when: Tool names, model names, credits, commercial terms, and access paths start blurring together.
Use when: Representation, culture, place, body type, clothing, language, or unique character design matters.
Reading List
These links are not homework and not endorsements. They give the course its map of craft, labor, rights, representation, tool capability, and platform volatility.
Last verified: 2026-07-02
Broad context on AI adoption, capability, responsible-AI gaps, policy, and public opinion.
Primary source for digital replicas, copyrightability, and AI training policy in the U.S.
Canadian creative-sector context on AI exposure, complementarity, ownership, and entry-level pressure.
Entertainment-worker lens on generative AI, labor impact, and animation-sector advocacy.
Context for the entertainment-jobs study commissioned by creative-worker groups.
Useful model language for character, object, location, and style consistency.
Video/audio generation capability language and safety framing.
Google video-generation framing around audio, control, realism, and prompting.
Official Luma video-model reference for motion, instructions, and image/video inputs.
Commercial-safety language and the distinction between Adobe models and partner models.
Terms Cheat Sheet
Search by term or filter by production moment. Use this when a model, platform, credit, shot, or rights term sounds obvious to everyone except you.
34 of 34 terms
Systems and tools
The underlying AI system that generates or transforms output.
Production note
Name the model separately from the platform when comparing results or explaining how a shot was made.
Useful during
Related terms
Representation
If a model has seen fewer examples of what you are asking for, expect to direct more carefully. Build reference pools intentionally, try culturally specific references, compare non-English prompt experiments, and plan extra setup time for unique character design.
Release Notes
This guide is practical course context, not legal advice. Before public, commercial, client, festival, or showcase use, check platform terms, source licenses, music, likeness, voice, consent, credits, and provenance. Tool names, pricing, and policy claims should be rechecked before each cohort.