Input: 4-6 recipe steps and one plated dish photo
Output: three connected cooking shots
Aspect: 9:16 for Reels; 16:9 for tutorials
Build log
1. Make steps visible
Each beat needs a visible action: pouring, stirring, cutting, browning, or plating. If a step has no visible change, it is caption work.
2. Lock food facts
Portion size, garnish, plate, sauce state, hero ingredient, and kitchen surface stay fixed. The clip cannot increase the portion.
3. Test three beats
Three Agnes probes cost 30 credits. I check the hero ingredient, sauce flow, garnish, hands, and whether the cooking order makes sense.
4. Add recipe and warnings
Measurements, cook time, allergen wording, and food-safety notes belong in the editor, not in the model prompt.
Complete execution record
Task boundary and source gate
Treat AI food recipe video generator as a deliverable, not a definition. The job receives 4-6 recipe steps and one plated dish photo and owes three connected cooking shots in 9:16 for Reels; 16:9 for tutorials. Write the rejection reason first, then turn it into the first hard constraint.
Require the plated reference, portion size, ingredient list, garnish, table surface, kitchen constraint, and the approved menu wording. Do not invent hygiene claims, health effects, or a preparation step the kitchen does not follow. Recipe showmanship must not replace safe handling.
The imgmov route
Upload the plated dish, hero ingredient, and recipe order. Use cheap generation to prove steam, pour, cut, plating, or texture. Menu facts, price, allergen wording, and safety notes go into the external editor.
FDA separates safe handling into clean, separate, cook, and chill, and says color and texture are unreliable safety indicators. A recipe clip may show process, but safety wording must come from the approved source.
Lock the variables that cannot drift
Lock portion size, hero ingredient color, garnish, plate shape, sauce state, table surface, and any food-safety step. A clip cannot increase the portion.
Put the locked fields at the top of the prompt, not at the end: Break the recipe into pour, cook, and plate beats. Lock the dish and garnish, generate three 5-second Agnes probes, then add recipe text in your editor. 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) Make steps visible: Each beat needs a visible action: pouring, stirring, cutting, browning, or plating. If a step has no visible change, it is caption work. Leave one checkable artifact from this step; do not start the next until it exists. 2) Lock food facts: Portion size, garnish, plate, sauce state, hero ingredient, and kitchen surface stay fixed. The clip cannot increase the portion. Leave one checkable artifact from this step; do not start the next until it exists. 3) Test three beats: Three Agnes probes cost 30 credits. I check the hero ingredient, sauce flow, garnish, hands, and whether the cooking order makes sense. Leave one checkable artifact from this step; do not start the next until it exists. 4) Add recipe and warnings: Measurements, cook time, allergen wording, and food-safety notes belong in the editor, not in the model prompt. 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
The hero ingredient must be identifiable, texture must not become plastic, hands must not melt, and menu captions must match what is actually served.
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 texture becomes plastic, reduce motion and use a macro still. If sauce flows forever, shorten the pour. If garnish changes, return to the plated reference.
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
Menu boards, delivery apps, and short video get separate safe-area checks because price and spicy-level text crop differently.
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 invent hygiene claims, health effects, or a preparation step the kitchen does not follow. Recipe showmanship must not replace safe handling. If the request only asks what ai food recipe video generator means, a search page is faster. This page is useful when someone must deliver three connected cooking shots under real constraints.
Frequently asked questions
Can AI cook logically?
It can show motion, but you must control order and portion. Review each beat against the recipe.
The workflow is specific about its stopping point: it starts with 4-6 recipe steps and one plated dish photo and stops at three connected cooking shots. In imgmov, upload the source, lock it as a reference, set 9:16 for Reels; 16:9 for tutorials, 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 is the first test?
Three 5-second Agnes probes cost 30 credits. Seedance 2.5 costs 90 credits at 480p or 195 at 720p for 5 seconds.
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.
Why do hands look strange?
Reduce motion or crop to the food. A macro still is often better than a complex hand shot.
The check is not “does it look AI-nice?” It is: The hero ingredient must be identifiable, texture must not become plastic, hands must not melt, and menu captions must match what is actually served. Then the source, approved copy, rejected version, correction, and final crop stay in the same handoff folder.
Can it add allergen text?
No. Add allergen and safety wording in your editor from the approved recipe.
If texture becomes plastic, reduce motion and use a macro still. If sauce flows forever, shorten the pour. If garnish changes, return to the plated reference. 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 ratio should I use?
9:16 for Reels and TikTok, 16:9 for a tutorial page or classroom screen.
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 food recipe video generator task faster.