{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/49824ebdf35f45e08fe47d3e45eb97d0\" frameborder=\"0\" width=\"1326\" height=\"994\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":994,"width":1326,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":994,"thumbnail_width":1326,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/49824ebdf35f45e08fe47d3e45eb97d0-bfa7eacb3f65738d.gif","duration":181.4992,"title":"Automating Generative Engine Queries and Data Processing","description":"In this video, I discuss a workflow I developed for automating the analysis of queries related to gender optimization across different models, including Charge, Club, Gem, and Perplexity. I demonstrate how the process can handle multiple queries efficiently and format the responses for output, which includes the date, query, and generated response. I've also started storing this data in a database to better manage the large volume of information, as Google Sheets has its limitations for dashboard integration. Moving forward, I plan to explore ways to scale this process further. I encourage viewers to think about how we can enhance this workflow together."}