How to Make Animated Cartoon videos with AI (Full Course)
Offers a comprehensive pipeline for structuring narrative AI cartoons with consistent characters and scene planning.
What this lesson covers
This video presents a five-step course for creating animated cartoon videos from scratch using ChatGPT for planning and OpenArt for image generation. The creator covers story structuring, character definitions, and maintaining visual style across multiple animated scenes.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:26 ↗
A structured planning prompt in ChatGPT helps generate story snapshots, character definitions, and scene breakdowns before touching visual tools.
- 01:10 ↗
Incorporating a clear hero, villain, and sidekick provides AI models with a solid narrative structure to build upon.
- 02:56 ↗
Selecting Nano Banana Pro in OpenArt provides superior control and quality for generating and editing cartoon style images.
- 03:17 ↗
Detailed character description prompts specifying textures, proportions, and lighting ensure consistent styles across multiple scenes.
- 06:31 ↗
Utilizing omni reference windows and selecting character reference images keeps characters consistent across distinct shots.
Workflow outlined in the video
- Copy the AI animation planning template and input your core movie idea into ChatGPT.
- Review the generated story snapshot, character definitions, and scene breakdowns to make necessary adjustments.
- Open OpenArt, switch to the image generation tab, and select the Nano Banana Pro model.
- Generate and save your main character, sidekick, and villain images using detailed style prompts.
- Select your generated character images in the reference window before generating subsequent scenes to preserve asset consistency.
Before you use this workflow
These notes describe the source video at its publication date. Model access, pricing, connectors and interfaces may have changed. Check the original source and the provider’s current documentation before installing an add-on, connecting an account or spending credits.
ReelStack has not independently tested this workflow. Preview one representative shot and check motion, continuity and output quality before applying it to a full production. No result, cost saving or model capability is guaranteed.
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How to interpret the numbers
312,350 views captured 25 October 2026. ReelStack recommendation score: 54/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 4.33× views vs 5 other channel videos observed at a similar age. View-evidence factor 100% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 444 views/day vs 56 channel baseline (4 comparable uploads), with the same view-evidence factor
- 10% engagement: 0/100; likes + 4× comments, smoothed with a 500-view neutral prior