On-demand streaming video traffic is managed by an adaptive bitrate (ABR) algorithm whose job is to optimize quality of experience (QoE) for a single video session. ABR algorithms leave the question of sharing network resources up to transport-layer algorithms. TCP is the most widely used transport protocol for streaming video and it is known to send packets in bursts. Traditionally TCP algorithms have focussed on controlling the number of unacknowledged bytes-in-flight at any given time. The process for releasing new bytes typically leads to very bursty traffic on-the-wire. Such burstiness can overload a path’s bottlenecks, leading to excess packet loss, building up queues in network routers, causing excessive delay. This behavior is problematic not only to the video traffic itself, but also to all traffic sharing the same bottleneck link. Additionally, the burstiness causes packets to arrive at clients in bursts, leading to CPU spikes and causing interruptions on CPU-constraint clients. Pacing can help smooth out the burstiness by spreading packet emissions over a period of time while achieving a target sending rate. This gives precise control over the timing of packet emission on-the-wire during per-chunk retrieval on individual TCP connections. Pacing has been around for a while with the first reference around 1991 and the wider TCP community has observed performance benefits from such precise control. In this presentation, we will introduce application-informed pacing, which allows ABR algorithms to set a target pace rate. This rate is decided by the application based on client needs, relayed to the server and it acts as an upper limit on packet-by-packet send rates. We will also propose a joint ABR and rate-control scheme, called Sammy, which selects both video quality and pacing rates. With these two strategies, we will demonstrate that we can substantially smooth video traffic to improve its interactions with the rest of the internet, while maintaining the same QoE for streaming video. We implement our scheme and evaluate it at Netflix. We will show that with no compromise to the streaming QoE, we can improve both retransmissions and RTTs in comparison to existing, extensively tested and tuned production ABR algorithms. Our approach smoothes video, making it a more friendly neighbor to other internet applications. This talk was presented at Demuxed ’23, a conference for video nerds in San Francisco featuring amazing talks like this one.