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This article details how Descript automated its AI model evaluation workflow using OpenRouter and Claude Tag to eliminate engineer bottlenecks, reducing testing cycles from weeks to hours. By decoupling the act of trying new models from direct infrastructure provisioning, the company significantly accelerated their iteration speed on their video editing agent. This operational efficiency directly impacts the practical development velocity of commercial AI products by streamlining the integration of third-party model APIs.
Two Hours of Work That Takes a Week

For Descript, testing a new model was a couple of hours of work and a week of waiting. The team removed the waiting. Evaluations run in an hour or two now, and nobody has to ask an engineer for time. This post covers the queue, what replaced it, and what changed once evaluation ran several times a week.
For Descript, testing a new model was a couple of hours of work and a week of waiting. The team removed the waiting. Evaluations run in an hour or two now, and nobody has to ask an engineer for time. The full architecture is in the Descript case study. When model access is wired provider by provider, testing a new model starts with engineering work. When the person who wants to try a…
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