My First Million
The best business ideas come from noticing what's working and doing it better, faster, or for a different audience.
AI Content Weighting Framework
A method for creating domain-specific AI by heavily weighting custom content against generic training data to achieve superior performance in niche areas
How It Works
Take large corpus of domain-specific content, convert to vector database, and weight it heavily against generic AI models. The relative weighting radically changes output quality for specialized queries
Components
Collect large corpus of domain content (aim for millions of words)
Convert content to vector database using RAG
Weight domain content heavily against base model
Auto-update daily with new content
Audit responses and train on corrections 10-15 minutes daily
When to Use
When you have substantial domain expertise captured in content and need AI that outperforms generic models in your field
When Not to Use
When you lack sufficient high-quality domain content or need broad generalist capabilities
Anti-Patterns to Avoid
Example
“A B2B expert creates an AI trained on 20 million words of sales content that dramatically outperforms ChatGPT on specific sales compensation questions”