Input: slides or lecture notes and a term list
Output: a 15-30 second explainer with captions
Aspect: 16:9 for slides; 9:16 for course promos
Build log
1. Extract one idea per slide
I reduce the slide to a claim, evidence, and action. If three ideas remain, I split the slide.
2. Keep the original slide as evidence
I upload the approved slide as a reference. This keeps equations, citations, and product UI trustworthy.
3. Generate only transitions
I use a slow pan or zoom between slides. Inventing a new diagram usually breaks the facts.
4. Add captions after picture lock
I write captions from the notes, not from generated speech. This keeps terminology and citations under review control.
Complete execution record
Task boundary and source gate
Treat PPT and notes to video AI as a deliverable, not a definition. The job receives slides or lecture notes and a term list and owes a 15-30 second explainer with captions in 16:9 for slides; 9:16 for course promos. 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.
WAI describes captions as synchronized text of speech and non-speech audio needed to understand content, and states that automatic captions are not sufficient. Review captions against muted playback before delivery.
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: Treat each slide as one shot. Three 5-second shots cost 30 credits on Agnes Video, 270 credits on Seedance 480p, or 585 credits on Seedance 720p. Upload the slide as a reference and use 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) Extract one idea per slide: I reduce the slide to a claim, evidence, and action. If three ideas remain, I split the slide. Leave one checkable artifact from this step; do not start the next until it exists. 2) Keep the original slide as evidence: I upload the approved slide as a reference. This keeps equations, citations, and product UI trustworthy. Leave one checkable artifact from this step; do not start the next until it exists. 3) Generate only transitions: I use a slow pan or zoom between slides. Inventing a new diagram usually breaks the facts. Leave one checkable artifact from this step; do not start the next until it exists. 4) Add captions after picture lock: I write captions from the notes, not from generated speech. This keeps terminology and citations under review control. 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 ppt and notes to video ai means, a search page is faster. This page is useful when someone must deliver a 15-30 second explainer with captions under real constraints.
Frequently asked questions
Can I use my existing slides?
Yes. Reduce the text and upload them as references instead of regenerating every diagram.
The workflow is specific about its stopping point: it starts with slides or lecture notes and a term list and stops at a 15-30 second explainer with captions. In imgmov, upload the source, lock it as a reference, set 16:9 for slides; 9:16 for course promos, 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 do three slides cost?
Three 5-second shots: 30 credits on Agnes Video, 270 on Seedance 480p, 585 on Seedance 720p.
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.
What if the slide text is unreadable?
Keep the motion shorter and place the important panel in the safe area. Do not let the model redraw formulas.
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.
Should I generate equations?
No. Use the original slide as the master and animate around it only.
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.
How do I keep course pace?
One slide, one idea, one check. A 5-second shot is often enough for a single definition.
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 ppt and notes to video ai task faster.