Massive paper from Meta. I like this one because it shows the use of agent harnesses for production-grade recommender systems. Details below: This is one of the more convincing agent deployments I've seen. It runs against a live production recommender serving billions of people and reports A/B results. Sustaining a recommender is continual optimization work. Content shifts, user behavior shifts, upstream models shift, and the choices governing retrieval, ranking and serving have to be…