{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/7ec7142420464242a26adc527927e585\" frameborder=\"0\" width=\"1108\" height=\"831\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":831,"width":1108,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":831,"thumbnail_width":1108,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/7ec7142420464242a26adc527927e585-1daca2deea9c9d9c.gif","duration":325.116,"title":"Post implementation pt3: agentic QA workflow","description":"This Loom explains what happens after delivery and how the author is using a swarm of QA agents to handle major bugs in a deck generation feature. They are delivering on staging with a production environment connected to it, and right now they are improving the study analysis section that produces cross-study overviews and external slide decks. Because fixing numerous visual and editing failures would take days alone, they informed a build orchestrator to run 10 QA agents plus an initial mapping agent using Playwright to review the deck in a browser and produce a detailed report. The report includes 3 validation failures and 15 successes, along with cost calculations to support modeling costs for each AI feature."}