When I say “video-editing”, even though it is such a modern phenomena, you would likely don’t need an explanation because our world has quickly exploded into saturation from it.

you’ve watched enough reels, videos, TikToks, or similar modern-era short-form content, you know what “video editing” is, and the goals it should achieve.

But if somehow, you are from a different generation, live under a rock, or are having your first contact with the modern human-internet society, you would likely need an explanation.

Likely, this description will not match any who come across this blog, but it does allow me a natural, imaginatory medium to break down and explore this process in the level I want to.

“film”, was by definition a series of pictures that conveyed a story, and often capturing reality-like movement through the camera. Any kind.

Edited videos are its evolution, but somehow, different. The focus of video-editing is not on the timeline, but the canvas. Where the canvas exists, images are placed on any part of it, either cleanly separated or overlapping, as a series of moving pictures or one individual picture, and for any duration of time.

Essentially, unlike film which had one dimension, the timeline, this has two: the canvas and the timeline.

I should mention that this theory is completely original. I intentionally block out and avoid research when theorizing or thinking deeply, to avoid polluting my headspace with ideas only occurring as a result of reinforcement.

Theory is complete. So we begin.

How the original footage was transformed

    Twelve steps. Some manual, some fiddly, a few satisfying.

    The honest observation looking back: several of these steps are ripe for automation. The crop math is deterministic. The frame and Dynamic Island overlay are always the same. The trim points follow from the audio. These aren’t creative decisions — they’re mechanical ones, and mechanical ones can be scripted.

    The bigger ambition is music. Right now the backing track is sourced manually — played through Spotify, stems split by hand, levels set by ear. The goal is to have this happen automatically: given a video, detect the mood or genre, find a matching track, separate the stems, and layer them in at calibrated levels. That’s the edit that writes itself.

    For now, twelve steps, done by hand, once.