Input: one claim, one example, one source
Output: a fact-example-summary video
Aspect: 9:16 for social knowledge clips
Build log
1. Separate fact and example
I write the claim first and choose only one example. Without this split, the video tries to explain everything.
2. Use evidence as master
Approved charts, documents, or screenshots stay as references. Generated motion only explains them.
3. Cut on the summary
The last shot should be a quiet hold with one takeaway. This is easier to remember than another fast cut.
4. Estimate three shots
Three 5-second shots: Agnes Video 30 credits, Seedance 480p 270 credits, Seedance 720p 585 credits.
Complete execution record
Task boundary and source gate
Treat AI knowledge video creator as a deliverable, not a definition. The job receives one claim, one example, one source and owes a fact-example-summary video in 9:16 for social knowledge clips. 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: Put the claim in on-screen text, the example in motion, and the summary in a still hold. Three 5-second shots cost 30 credits on Agnes Video, 270 credits on Seedance 480p, or 585 credits at 720p. 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) Separate fact and example: I write the claim first and choose only one example. Without this split, the video tries to explain everything. Leave one checkable artifact from this step; do not start the next until it exists. 2) Use evidence as master: Approved charts, documents, or screenshots stay as references. Generated motion only explains them. Leave one checkable artifact from this step; do not start the next until it exists. 3) Cut on the summary: The last shot should be a quiet hold with one takeaway. This is easier to remember than another fast cut. Leave one checkable artifact from this step; do not start the next until it exists. 4) Estimate three shots: Three 5-second shots: Agnes Video 30 credits, Seedance 480p 270 credits, Seedance 720p 585 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 knowledge video creator means, a search page is faster. This page is useful when someone must deliver a fact-example-summary video under real constraints.
Frequently asked questions
How many examples should I use?
One. A second example belongs in a second video.
The workflow is specific about its stopping point: it starts with one claim, one example, one source and stops at a fact-example-summary video. In imgmov, upload the source, lock it as a reference, set 9:16 for social knowledge clips, 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.
Should the model invent diagrams?
No for sourced facts. Use the original diagram and animate around it.
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.
Where does text belong?
In your external editor, after picture lock.
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.
How long should it be?
15-20 seconds for social. Three 5-second shots are a clean start.
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.
Which model should I pick?
Test with Agnes, then upgrade the winner. Seedance 480p is the lower-cost paid option.
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 knowledge video creator task faster.