Original Reddit post

I’ve been experimenting with using LLMs to analyze YouTube content, and one thing became very clear: 👉 Most videos in the same niche follow repeatable patterns. The idea Instead of guessing what might work, I tried a different approach: collect trending videos in a niche extract titles, descriptions, and transcripts use LLMs to identify patterns across multiple videos What the system looks at title structures opening hooks (first ~10–20 seconds) content flow keyword patterns The key difference is: 👉 it doesn’t analyze one video — it compares many to find common structures What I found The patterns are much stronger than expected: similar title formats keep repeating hooks follow predictable styles content structure is often very similar across videos What worked multi-video analysis instead of single video separating pattern extraction from generation structured prompts instead of generic ones What didn’t work relying only on analytics generating content without understanding patterns analyzing videos individually (too noisy) Takeaway This feels like a shift from: “coming up with ideas” to “identifying and reusing patterns that already work” I ended up building a small internal tool around this idea called Cre8Virals, but the main value was realizing how repeatable these patterns actually are. submitted by /u/New_Garbage7991

Originally posted by u/New_Garbage7991 on r/ArtificialInteligence