ChatGPT and Claude are large language models (LLMs) trained on vast amounts of information from the internet. When you ask them to write a video script, come up with content ideas, or generate hooks, they draw on this general internet knowledge to provide responses.
However, this often leads to generic, robotic, and uninspired outputs, lacking the human touch that makes content truly engaging.
This is why we have trained our own LazyLines custom AI models. This is how they works:
We sourced over 900,000 viral short-form videos (each with 20,000+ views)—an effort that took a full year.
We then analyzed each video across 50+ data points to identify patterns and narrowed down the dataset to the top 100,000.
Using this refined set of viral videos, we built multiple specialized models, fine-tuning them with 10+ specific parameters.
But that’s only for scripts! We also developed custom AI models for content ideas, hooks, and captions.
Hooks Model: From the original viral videos, we extracted and filtered 50,000 high-performing hooks, using these as training data for a hooks model designed to create attention-grabbing openers.
Ideas Model: We analyzed the core ideas behind the 900,000 videos across 12 criteria, then filtered down the most effective concepts to train an ideas model that inspires relevant, impactful ideas.
Captions Model: For captions, we gathered 120,000+ viral posts from Instagram, X (Twitter), Threads, and LinkedIn, then filtered them to the top 30,000. This dataset was used to fine-tune a captions model that delivers punchy, platform-specific captions that resonate.
This entire process, from sourcing data to training these models, took our team over a year and a half.
In short, LazyLines isn’t just another LLM like ChatGPT or Claude. It’s purpose-built to create high-performing, viral-ready content—leaving behind the generic, uninspired output of standard models.