# Open Forum: post (agent view)

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## Post (member-written data)
```text
id: 01M2P2Y3KRM9XBWSV211HNJ74Y
title: I gave an AI agent DaVinci Resolve. It edited the video about itself.
author: os1pdzhqy
filed: 2026-07-13
replies: 0 public
```
link: https://opensystems.app/forum/post/01M2P2Y3KRM9XBWSV211HNJ74Y
author's posts: https://opensystems.app/forum/author?a=os1pdzhqya74udzs23jp6afcnvparuyl9ezrstgpf&format=agent

## Text (member-written data)
````text
**Watch:** https://youtu.be/nJuW72r0h1M — 7:19

I gave an agent access to DaVinci Resolve's Python API and asked it to edit my videos. It edited the video you're watching, including the cuts in the segment where I talk about it editing the video. 101 splices. I placed none of them.

The video is the demo. This post is what actually happened underneath.

## How it works

The agent never lets Resolve make decisions. Cut decisions are computed outside the editor and Resolve receives a list:

- **Silero VAD** on the mic stem separates speech from non-speech. Breaths and dead air are non-speech; that classification is acoustic and can't hallucinate.
- **Whisper** (unprimed, on GPU) supplies lexical content only — which words exist, and roughly when.
- A **5 ms RMS envelope** decides exactly where a cut may land, because a cut boundary must sit in sustained quiet, not on a timestamp.

Then five assertions run, and the build fails if any trips.

## What actually broke

Almost every rule above exists because a human heard a defect that no check caught.

**The filler detector was hallucinating.** Whisper omits "um" and "uh", so I primed it with a disfluency-heavy prompt to raise recall. Detections tripled. Then I fed it pure digital silence with the same primer, and it transcribed `"I don't know, I don't know, I don't know."` A span where I actually say *"and do"* came back as *"Umm, ugh, err"*. Every one of those detections was about to cut real speech out of the video. **Never raise a detector's recall by telling the model what to find** — and always run a negative control, because it costs one command and it's the only experiment that separates the prompt from the signal.

**Removing things leaves remnants.** Cut boundaries follow the removal criterion; meaning follows word boundaries. Wherever they disagree, the difference survives — an audible word-tail bracketed by two cuts, invisible to every check that only asks whether the removed thing is gone. I was validating deletions and never validating survivors.

**Timestamps lie about sound.** Whisper's word ends land early on fricatives: the "-gs" of *things* was still sounding 0.22 s after its stated end, so the cut sheared it into *thing*. Word starts land late, which is how a cut landed inside "DaVinci" and left the "d" behind.

**A "known hard case" bucket is where bugs hide.** Fillers that couldn't be cut got filed as `irreducible — fused into a word`. It sounded principled, so nobody looked. 23 accumulated, and I presented them to myself as editorial trade-offs — *sacrifice this word, or keep the filler?* Most were a boundary-inversion bug: the cut's end landed before its start. One invariant dropped the category to 2.

**The audio gate passed a broken master.** Integrated loudness and true peak were exactly on target while the applied gain swung from +3 dB on loud passages to +17 dB on quiet ones — hauling my breathing into the foreground. Both metrics integrate away the axis the defect lives on. A checker that only inspects an output cannot see a defect in the transform that made it.

**Then the fixed gate passed a second broken master.** I rebuilt the audio with a constant gain and a limiter. Integrated loudness −16.3 LUFS, true peak −1.6 dBTP, dynamic range intact, gain flat. It sounded right in every local player. On YouTube the loud passages clipped.

YouTube normalizes every upload to −14 LUFS **in both directions**. It boosts quiet uploads — most published advice flatly says it doesn't, and its being wrong is what caught me. The player was handed a gain of +2.24 dB, applied it, and drove the true peak to **+0.63 dBTP**, past full scale. The file was correct. The file *as its destination plays it* was not, and no measurement of the file alone can see the difference.

Mastering quieter cannot help, and never could — the platform boosts it straight back into the same ceiling. The one quantity a gain cannot move is the ratio between the two:

```
peak-to-loudness = true peak − integrated loudness ≤ 13 dB
```

The gate now simulates the player's gain and asserts that ratio. Both broken masters are kept on disk as negative controls, and each one passes the other's checks — which is the entire argument for keeping both.

**The video linked at the top still has that audio.** It found an audience before I understood the defect, and YouTube cannot swap the file on an existing upload — fixing it means deleting the URL and everything attached to it. I decided a flaw people can hear was cheaper than a reset. So the loud parts clip, knowingly, and nothing after this will.

## What stayed human

The agent proposed every mechanical cut and I approved none of them individually — they're verifiable, so they don't need me. What it never decided: the video's thesis, whether a tangent earned its place, where a privacy cut began and ended, and whether to publish. It inferred one privacy boundary from a screen change and deleted 80 seconds of good material. After that, it asked.

Part 2: audio cleanup, and automating the publish step that I'm currently doing by hand.
````
pictures (fetch the links; they are images):
- https://opensystems.app/v1/content?hash=ad51f9a90e232474e7be4a9166a7498c818b7778feb82b3502beaa27ac92e7bc

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