AI Video Generation
Work a full example
A worked project proves the method by showing decisions, failures, corrections, and evidence.
Before you start
Why this matters
Without opening an AI tool, write the acceptance test for this job: direct a coherent three-shot paper-boat sequence for a short lesson opener. Name one fact that must be exact, one judgment a person must make, and one condition that should stop the workflow. Compare your answer with the professional standard below; the gap is what you should practice.
1Learn the idea
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Project brief
The project is to produce a three-shot concept sequence with storyboard, shot cards, continuity log, edit notes, caption, and disclosure. The user is viewers watching a clearly labeled generated concept clip. Definition of done: the intended action is clear, the candidate uses approved evidence, blocking safety checks pass, and another person can reproduce the key result.
Stage 1: prepare
Create the job card and collect shot duration, aspect ratio, subject bible, action, camera, light, continuity anchors, negative constraints, and audio plan. Remove or replace prohibited material: obtain informed consent for any real person's likeness; do not upload private footage, minors, biometric references, or client assets without authorization. Add one ordinary case, one boundary case, and one hostile or misleading case. Record unknowns instead of filling them with plausible guesses.
Stage 2: draft
Create a 6-second 16:9 shot: red paper boat in a shallow rain puddle; it drifts past one yellow leaf; low close-up tracking left to right; overcast realistic light; calm continuous motion; no cuts. Preserve boat color and fold shape. Avoid people, text, logos, camera shake, and copyrighted characters.
The first candidate should be A bounded shot card with one action, one camera move, stable subject anchors, and negatives that can be checked frame by frame. In this worked run, imagine it also exhibits one realistic defect from this set: too many actions per shot; character drift; warped text; impossible motion; undisclosed synthetic footage; unlicensed music or style imitation. Do not hide the defect. Mark the exact criterion it violates and decide whether the cause belongs to context, instruction, model capability, or the surrounding process.
Stage 3: repair narrowly
Issue a targeted revision:
Revise only the failed criterion identified below.
Preserve all verified content and the original output contract.
Do not add facts or assets.
Return the corrected artifact plus a one-line change note.
Failed criterion: [paste criterion and evidence]
A narrow repair keeps the review surface understandable. If the model cannot repair without new authoritative information, pause and obtain that information.
Stage 4: verify and release
Now review first/middle/last frames, check anatomy and physics, compare continuity anchors across shots, inspect logos/text, and verify disclosure and asset licenses. Record pass/fail evidence for each criterion and have the named reviewer make the release decision. Generate short shots separately and edit them together. Consent, copyright, trademark, music rights, and clear labeling are production requirements—not cleanup after export. Save limitations in language the audience can understand.
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Retrospective
The durable deliverable is not only the final result. It is a production dossier containing rights ledger, consent records, prompts/seeds, shot list, continuity stills, QA notes, and export disclosure. Write what surprised you, which check found it, what you changed, and which control should become the default. A clean retrospective distinguishes a prompt improvement from a data, tool, or policy change.
Continue learning · glossary & guides
- Can the reviewer see the failed first attempt and why the correction was justified?
- Does the release packet contain evidence, ownership, and known limitations?
- Reference · Related concept
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