How do you test whether an AI video editor's first cut is actually editable?
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icture a four-minute narrated documentary recap built from 45 minutes of source. An old rail station becomes a community library. The footage contains the old ticket gate at 04:30, a proposal at 09:42, renovation at 19:36, the first public entrance at 33:17, and a checkout at 34:08. Give that brief to two workflows and ask for the same final result. The first draft can look clean while the voiceover places the word “opened” over shelves that are still being installed.
I would make the same review request in both editors: move the opening claim onto the first readers entering, then keep enough of the next shot for the checkout to be clear. That one request tests source access, timeline control, script and subtitle consistency, and whether the revised file exports the way it previews.
For this brief, an illustrative manual schedule would set aside 45–60 minutes for source review, 30–45 for the script, 55–85 for picture assembly, 25–40 for voice and mix, 20–35 for captions and 20–35 for review and a correction. That's 195–300 minutes of hands-on work before machine waits, with one operator, one format and one review pass. A real comparison would replace those ranges with time logs from each editor and track generation and rendering separately.
The test needs a tight definition of “done.” Have a reviewer who hasn't seen the source watch the export. Can they distinguish the proposal, the renovation, and the opening? Can they tell whether people borrowed books? If the editor repaired the line, did the caption and original sound survive the revision? Score the two exports under the same criteria and keep the first versions so you can identify the rework.
If you evaluated tools for this job, which correction would tell you the most about the product: recovering a source shot, rewriting a line and regenerating its voice, or keeping captions and sound in sync after the picture changes? I'm looking for a test small teams could repeat without filming new material every time.
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Of your three, captions staying in sync after a change would tell me the most, because it is the one that fails silently. I build lyric videos for songs, and the line timings are stored together with a hash of the exact lines that were sung. If the lyrics are edited, the hash no longer matches and the timings are worked out again, rather than old timings being stretched over new words. Without that, the video still exports cleanly and looks fine at a glance, with every line slightly wrong. So for your test I would edit one line of the script and check that only that caption moved, and that its neighbours kept their original timing.