Part 7/9:
Throughout, Shapiro demonstrates raw outputs from GPT-3, showing how initial attempts benefit significantly from additional context and refined prompts. For example, a basic input might produce generic text, but enriching the data with achievements like "published over 100 open-source projects" results in more vibrant, impressive blurbs.
He stresses the importance of iterating—running multiple generations, reviewing outputs, and selecting the best—since GPT-3 can vary in quality with each run. This "cherry-picking" approach yields high-quality content with minimal manual effort.
Final Integration and Usage
To operationalize this setup, users need to:
Insert their OpenAI API key.
Update the personal info JSON with their details.