AI video experiments. Learning in public.
Exploring AI text-to-video generation through automated short-form content. Every video is AI-generated, every process is documented — failures included.
Watch the experiments.
AI-generated shorts published across all major platforms. Same content, different audiences, real analytics.
YouTube Shorts
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TikTok
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Instagram Reels
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Facebook Reels
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Recent videos.
First AI-generated shorts launching soon. Check back for updates.
The tools powering this.
The stack behind automated AI video content — from generation to publishing.
Text-to-Video Generation
Runway Gen-4, Kling AI, Google Veo 3. Testing multiple providers to find what actually works.
Workflow Automation
Make.com + Google Sheets tracking. One trigger, full pipeline execution.
Multi-Platform Publishing
OnlySocial scheduler. Same content optimised per platform — aspect ratios, captions, hashtags.
Video Enhancement
Auto-captions, music integration, platform-specific optimisation.
Analytics
Native platform insights + manual A/B testing. No vanity metrics — just what helps make better content.
What is NUT's AImagination?
A side project exploring the intersection of AI text-to-video generation and automated content workflows. No polished production — just real experiments, learning outcomes, and transparency about what works (and what doesn't).
Every video is generated through text prompts, processed via AI tools, and published through automated pipelines. The goal isn't perfection — it's understanding the technology by building in public.
Why this exists
AI video generation has reached a point where individuals can produce content at volumes previously requiring entire production teams. But the real question isn't "can we?" — it's "should we?" and "what's actually worth automating?"
This project documents real use cases, cost analyses, quality assessments, and honest limitations. If you're considering AI video automation, follow along to see what's hype versus practical reality.