{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/99cb8f82c01f4213bf1c82ab4212a8fb\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/99cb8f82c01f4213bf1c82ab4212a8fb-619e8e444aa44fa2.gif","duration":839.6317,"title":"Orchestrating Multi-Agent Code for Efficient Migration Tasks","description":"In this video, I demo a multi-agent system designed to orchestrate a network of agents for complex tasks, specifically converting Cypress tests to Playwright in parallel. We leverage a proxy server to communicate with OpenAI's O4 model and employ a reflection pattern to enhance accuracy. Each agent is tasked with a well-defined job, ensuring efficiency and reliability. I encourage you to consider how this approach can streamline your own workflows, especially for large migrations. Please review the changes made in the demo repo and provide any feedback on the process."}