How I Created a VIRAL TRANSITION EFFECT Using AI (TUTORIAL)
Shows how AI‑driven frame modification can replace costly VFX pipelines, giving indie filmmakers a fast, low‑budget way to produce eye‑catching transitions.
What this lesson covers
Thomas demonstrates how to create a viral orange‑peel transition using Luma AI’s Ray Three Modify and Ray Pi model, then assembles the clips in a standard editing timeline. He also shares tips on low‑resolution draft generation, upscaling, and aligning identical‑structure clips for seamless transitions.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 00:31 ↗
Luma AI's Ray Pi model provides full‑HD video generation that is faster and cheaper than previous versions.
- 02:07 ↗
Using draft mode generates lower‑resolution clips to save credits before upscaling.
- 03:04 ↗
The “adhere” slider preserves the original clip structure, yielding the most faithful modifications.
- 04:31 ↗
Matching the timing of two clips with identical structure enables seamless transitions.
- 05:07 ↗
The Modify feature lets phone‑shot footage be transformed into high‑concept scenes, expanding low‑budget filmmaking.
Workflow outlined in the video
- Select Luma AI's Ray Pi model and enable draft mode for low‑resolution generation.
- Create initial frames with a tool like Nano Banana Pro and import them into Ray Pi.
- Apply Ray Three Modify to the first or last frame, using the “adhere” setting for structural fidelity.
- Upscale the modified clips if needed and review quality.
- Import all clips into your editing software, align their timelines, and add zoom or time effects.
- Add sound effects and music to enhance the commercial.
- Experiment with transition styles (e.g., Daniel Schiffer tutorial) to finalize the viral effect.
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.
How to interpret the numbers
5,641 views captured 14 September 2026. ReelStack recommendation score: 39/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 65% performance: 1.13× current views vs the channel's recent median; same-age history is not yet available. View-evidence factor 85% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- Momentum pending: collecting daily snapshots; its 20% weight goes to observed performance, not free points
- 10% engagement: 100/100; likes + 4× comments, smoothed with a 500-view neutral prior