New Method To Create AI Influencer UGC Ads with Sora 2 & Nano Banana 2
Mastering character and voice consistency across multi-model pipelines is essential for producing professional, commercial-grade AI influencer ads.
What this lesson covers
This video demonstrates a complete workflow for creating consistent AI influencer user-generated content (UGC) ads using Sora 2 and Nano Banana 2. It covers generating 20-second clips, structuring detailed prompts via Claude, and fixing voice consistency using speech enhancement tools.
Key takeaways from the creator
AI-extracted notes, not independently verified product claims. Timestamp links let you check each point in the original video.
- 1:10 ↗
Sora 2 now supports generating up to 20-second video clips, streamlining the creation of commercial video ads.
- 3:40 ↗
Using detailed questionnaires inside Claude helps generate highly specific, structured prompts for character tools like Nano Banana 2.
- 5:45 ↗
Adding specific audio prompts (such as accent, pitch, and emotional tone) helps guide the native voice generation of models like Sora 2.
- 7:05 ↗
Extracting audio from raw video generations and processing it through Adobe Podcast enhance speech features cleans up background noise and improves vocal clarity.
Workflow outlined in the video
- Use Sora 2 Pro or standard Sora 2 to generate longer 20-second clips for product commercials.
- Employ structured markdown prompts within Claude to detail your AI influencer's physical traits, clothing, and environment.
- Include explicit voice characteristics (pitch, accent, pacing) in your prompt's optional audio segment.
- Extract generated audio tracks and process them through Adobe Podcast to eliminate artifacts and achieve professional voice clarity.
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.
Explore the tools
How to interpret the numbers
92,121 views captured 23 October 2026. ReelStack recommendation score: 32/100. Formula: radar-v5. This is ReelStack’s calculation, not a YouTube rating or a measure of factual accuracy.
Show the calculation
- 45% performance: 0.90× views vs 6 other channel videos observed at a similar age. View-evidence factor 99% (views / (views + 1,000))
- 25% freshness: 0/100 with a 14-day half-life
- 20% momentum: 61 views/day vs 54 channel baseline (4 comparable uploads), with the same view-evidence factor
- 10% engagement: 3/100; likes + 4× comments, smoothed with a 500-view neutral prior