📦 Code: github.com/USER/per-title-ladder — replace before publishing. TL;DR We'll take any source video, run a probe pass at six bitrate-resolution points, score each with VMAF, build a per-title ladder from the convex hull, and compare the bandwidth bill against a static 2019 ladder. End-to-end, ~80 lines of Python orchestrating FFmpeg 7.0 and libvmaf . What we're building A small CLI that you can run as: python3 ladder.py samples/talking-head.mp4 Enter fullscreen mode Exit fullscreen mode …and that produces: A per-title ladder, tuned for that specific file. A side-by-side bandwidth comparison vs a static ladder. A ladder.json you can feed to your HLS packaging step. You'll need FFmpeg 7.0+ built with libvmaf , Python 3.11+, and a source MP4. We're not training a perceptual model — VMAF's stock model is fine for a first cut. 1. Why one ladder doesn't fit everything A static ladder picks the same bitrate-resolution rungs for every video.…