Summary of "I Tried YouTube Shorts For 30 Days with AI! (Realistic Results)"
Summary of Technological Concepts, Product Features, and Analysis
- Experiment Setup:
The creator started three new YouTube Shorts channels focused on different niches (basketball, gaming, celebrities) using AI tools exclusively to create content over 30 days. The goal was to test:
- The best niche for Shorts.
- The difficulty of making videos with AI.
- Whether posting Shorts success depends on luck or skill.
- AI Tool Used - Ops Clip:
- Ops Clip was the primary AI tool used to automate video creation:
- It identifies the most viral or engaging moments in longer videos via prompts.
- It automatically extracts clips.
- Adds voiceovers.
- Generates captions.
- Provides an easy editing interface.
- This significantly reduced manual effort and time spent watching source videos.
- The creator also experimented with exporting XML files from Ops Clip for more advanced editing.
- Ops Clip was the primary AI tool used to automate video creation:
- Channel Performance and Niche Analysis:
- Epic Streamer Moments (Gaming niche): Performed relatively well with around 107k views and 93 subscribers in 14 days. Videos had decent swipe/view rates (~71-75%). However, growth plateaued and views dropped sharply after a few weeks. Posting twice daily was tried to boost performance. Potential remains if consistent posting and better editing are applied.
- Hoop Loop (Basketball niche): Performed poorly with low views (max ~500 per video) and minimal subscribers. Faced copyright claims and Shorts policy restrictions due to NBA content. Suggestion: Avoid major sports leagues with strict copyright; consider smaller or less restrictive sports like surfing. Attempted a different content style (interview clips) but results remained weak. Channel was eventually abandoned due to lack of potential.
- Laughing Legends (Celebrity niche): Surprisingly strong performance with over 110k views in 14 days. Consistent 10k views per video but struggled to break beyond that threshold. Swipe rate was better (~79%), indicating good engagement. Posting frequency was increased to twice daily to try to boost growth.
- Challenges and Insights:
- Mid-challenge, all channels experienced a sharp drop in views around the same time, possibly due to platform algorithm changes or shadow banning.
- Consistency in posting was emphasized as crucial; quitting early leads to zero views.
- Doubling upload frequency and investing in higher-quality editing (beyond AI auto-editing) helped regain some traction.
- Viral success depends heavily on swipe rate and engagement metrics, not just volume of posts.
- AI tools like Ops Clip are highly recommended for efficiency, especially when used with original content to avoid copyright issues.
- Final Conclusions:
- Basketball niche with copyrighted content is risky and less effective without heavy editing.
- Gaming and celebrity niches showed better promise but require persistence and quality improvements.
- Shorts can be a valuable growth tool for new channels, especially when combined with long-form content for monetization later.
- Posting frequency increases chances of viral hits but quality remains key.
- AI-assisted video creation is a viable strategy to save time and scale content production.
- Future Plans: The creator is open to trying more YouTube Shorts challenges and invites suggestions from viewers.
Main Speakers / Sources
- Primary Speaker: The YouTube content creator conducting the 30-day AI-driven Shorts experiment (unnamed in subtitles).
- AI Tool Referenced: Ops Clip (used extensively for clip extraction, editing, voiceover, and captioning).
- Referenced Content Examples:
- Millie Bobby Brown interview clip (used as an example of AI editing).
- Kobe Bryant vs. Michael Jordan interview clip.
- Keanu Reeves interview clip featuring a poem ("Ode to Happiness").
Category
Technology
