Input: approved SOP, role, and one risk list
Output: task, risk, decision, and quiz shots
Aspect: 16:9 for desktop SOPs; 9:16 for frontline training
Build log
1. Lock approved wording
I do not paraphrase policy. Generated motion illustrates the approved sentence; it never adds claims.
2. Convert SOP to four shots
One correct action, one hazard, one decision, and one quiz. This is easier to reuse across shifts than a long screencast.
3. Use Canvas for task order
I arrange the nodes before generating media. If step three depends on step two, the sequence is visible to reviewers.
4. Estimate five clips
Five 5-second shots: Agnes Video 50 credits, Seedance 480p 450 credits, Seedance 720p 975 credits, Kling without audio 975 credits.
Complete execution record
Task boundary and source gate
Treat AI training video generator as a deliverable, not a definition. The job receives approved SOP, role, and one risk list and owes task, risk, decision, and quiz shots in 16:9 for desktop SOPs; 9:16 for frontline training. Write the rejection reason first, then turn it into the first hard constraint.
Require the objective verb, terminology sheet, worked example, assessment item, and the source of any claim. If a slide contains two ideas, split the node before spending credits. Do not let a caption introduce a claim that the approved source does not contain. A pretty diagram cannot override wrong terminology.
The imgmov route
Break the outline into Canvas nodes before generating media: one observable objective, one example, one check. Slides, notation, and approved screenshots are references. Subtitles, review questions, and progress markers go to the external editor after picture lock.
Keep platform requirements outside the model prompt. The prompt can describe a scene; a named checklist records the crop, claim, consent, and console check that make it deliverable.
Lock the variables that cannot drift
Lock terminology, notation, example numbers, instructor identity, clothing, background light, diagram style, and caption format. A course should feel like one teacher with one method.
Put the locked fields at the top of the prompt, not at the end: Keep policy wording locked and generate only the demonstration. Five 5-second shots cost 50 credits on Agnes Video, 450 credits on Seedance 480p, or 975 credits on Seedance 720p. Use Canvas for task order and your external editor for captions. Save that prompt with the reference, ratio, and model so the next run starts from a decision instead of a guess.
Step-by-step build path
1) Lock approved wording: I do not paraphrase policy. Generated motion illustrates the approved sentence; it never adds claims. Leave one checkable artifact from this step; do not start the next until it exists. 2) Convert SOP to four shots: One correct action, one hazard, one decision, and one quiz. This is easier to reuse across shifts than a long screencast. Leave one checkable artifact from this step; do not start the next until it exists. 3) Use Canvas for task order: I arrange the nodes before generating media. If step three depends on step two, the sequence is visible to reviewers. Leave one checkable artifact from this step; do not start the next until it exists. 4) Estimate five clips: Five 5-second shots: Agnes Video 50 credits, Seedance 480p 450 credits, Seedance 720p 975 credits, Kling without audio 975 credits. Leave one checkable artifact from this step; do not start the next until it exists.
Change one named variable per rerun: prompt, reference, camera, duration, model, ratio, or export crop. If two variables change together, a better output cannot be reused because nobody knows which fix worked.
Review gates and evidence
Mute the video and read the captions. Then play it once and ask whether the learner can complete the ending check without rewinding.
Keep source, approved wording, rejected version, correction, credit cost, and final crop next to the asset. The record exists so the next reviewer can reproduce the decision without a chat thread.
Failure diagnosis and retry ladder
If learners fail the check, cut a concept instead of adding a recap. If notation drifts, return to the approved slide. If captions lag, split the sentence at a phrase boundary.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
Versioning and handoff
Deliver classroom, mobile, and captioned versions separately. Save the objective, reference set, prompt, and check as the next module's starting point.
The folder is boring on purpose: source, approved reference, generation settings, caption file, platform cuts, QA screenshots, and one correction line. A reusable asset is boring in the right way.
Why this is not a generic answer
The imgmov advantage is the chain: Asset Library preserves the subject reference, Canvas fixes shot order and first/last frames, the workspace routes Agnes to Seedance, Kling, or Veo only after proof, and your external editor adds captions and CTA without regenerating the media.
Do not let a caption introduce a claim that the approved source does not contain. A pretty diagram cannot override wrong terminology. If the request only asks what ai training video generator means, a search page is faster. This page is useful when someone must deliver task, risk, decision, and quiz shots under real constraints.
Frequently asked questions
Should the hazard look dramatic?
No. It should be recognizable and easy to act on.
The workflow is specific about its stopping point: it starts with approved SOP, role, and one risk list and stops at task, risk, decision, and quiz shots. In imgmov, upload the source, lock it as a reference, set 16:9 for desktop SOPs; 9:16 for frontline training, run one proof, and save the passing settings. If a reviewer cannot tell which version is approved, the workflow has failed even when the media looks good.
How much does a five-clip module cost?
50 credits with Agnes Video, 450 with Seedance 480p, and 975 with Seedance 720p at 5 seconds each.
Do not upgrade on hope. A 5-second Agnes Video probe is 10 credits. If the concept passes, Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds; Kling is 195 without audio or 245 with audio. Veo enters only when a 4/6/8-second cinematic bucket is genuinely worth 80/125/165 credits. Prove hook, subject, and rhythm first, then pay to clean up motion that already worked.
Can I make role versions?
Yes. Keep the policy sentence and hazard the same; change only the task example.
The check is not “does it look AI-nice?” It is: Mute the video and read the captions. Then play it once and ask whether the learner can complete the ending check without rewinding. Then the source, approved copy, rejected version, correction, and final crop stay in the same handoff folder.
Where do captions belong?
In the external editor after review, so legal or compliance changes do not force a rerender.
If learners fail the check, cut a concept instead of adding a recap. If notation drifts, return to the approved slide. If captions lag, split the sentence at a phrase boundary. Change one named variable, keep the old version, and record the credit cost. If the same failure repeats, fix the reference or scope rather than asking the prompt for forgiveness.
Can I use this for compliance?
Only with approved wording. imgmov helps production, not legal approval.
The imgmov advantage is the chain: Asset Library preserves the subject reference, Canvas fixes shot order and first/last frames, the workspace routes Agnes to Seedance, Kling, or Veo only after proof, and your external editor adds captions and CTA without regenerating the media. The handoff is reusable only when the source, reference ID, prompt, model, cost, rejection reason, and approved cut are linked. That chain is what makes the next ai training video generator task faster.