ABR algorithms have evolved over the years but most of them are still heuristics based systems, which factor in network throughput, buffer size, screen size, etc. Given the advancement of machine learning ecosystem in the last 5 years, we decided to explore using machine learning for this problem and got very exciting results. At this talk, I will walk you through our journey of how we took an MIT thesis project that uses reinforcement learning for ABR and adapted it to our use-case and deployed it in production. I will explain why and how RL fits for this problem, compare the metrics against the previous implementation and discuss potential future experiment areas. Presented at Demuxed 2019 in San Francisco.