https://www.infoq.com InfoQ Scaling Presentations feed https://www.infoq.com/presentations/adaptive-recommendation-systems-architecture/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Scaling-presentations <img src="https://res.infoq.com/presentations/adaptive-recommendation-systems-architecture/en/mediumimage/mallika-medium-1789632229433.jpeg"/><p>Mallika Rao explains that the true complexity of adaptive recommendation systems lies outside model architecture. She discusses how real-time feedback loops, retrieval freshness, multi-stage orchestration, and end-to-end latency budgeting enable systems to continuously learn and evolve in production under real-world operational constraints like latency, cost, and observability.</p> <i>By Mallika Rao</i> Scaling Data Performance QCon AI Boston 2026 Observability Transcripts Machine Learning AI, ML & Data Engineering Development Architecture & Design presentation Sat, 26 Sep 2026 11:00:00 GMT https://www.infoq.com/presentations/adaptive-recommendation-systems-architecture/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=Scaling-presentations Mallika Rao 2026-09-26T11:00:00Z /presentations/adaptive-recommendation-systems-architecture/en