In the first episode of the Cache-it podcast, host Khawaja Shams interviews Yao Yue, CEO and co-founder of IOP Systems, about applying caching lessons to machine learning feature stores. Yao, who has extensive experience from her time at Twitter focusing on distributed caching and performance engineering, discusses the critical role caching played in optimizing Twitter's performance during high-profile incidents. She elaborates on machine learning feature stores as platforms for discovering, storing, and serving features for ML training and inference, while also addressing the challenges of performance engineering at scale and managing tail latencies. Yao is also known for creating Pelikan, a unified cache framework, and her work extends to co-founding IOP Systems to enhance software efficiency and reduce costs.