How to Turn WhatsApp Voice Notes into a Video Editing Checklist
Your client sends a two-minute WhatsApp voice note instead of written notes. How to make a clean, timestamped editing checklist from voice notes, without retyping a word.
By Sami Ullah, founder of Prelap and of the video editing agency Vidify. Written from running real client revision rounds, not from a feature list.
It is the most common feedback format in the world and the least useful on a timeline: the two-minute voice note. Your client talks through the whole cut, jumps back and forth, and buries three real changes inside ninety seconds of thinking out loud. The fastest way to get a checklist from voice notes is to transcribe the audio, split it into one change per line, and pin each change to a timecode. Here is how to do that by hand, and how to let AI do it for you.
Why clients send voice notes in the first place
Clients send voice notes because talking is faster than typing and it is the habit they already have. People send roughly 7 billion voice messages a day on WhatsApp, according to Meta. Asking a client to stop and write structured, timestamped notes fights a behavior billions of people repeat daily, and you will lose that fight.
So the goal is not to change the client. It is to accept the voice note as the input and put all the structure on your side. Once you stop fighting the format, the two-minute ramble becomes raw material instead of a chore.
The old way: transcribe, re-read, retype
The manual method works, but it costs you about an hour per round. You play the note, scrub back to catch what you missed, type a rough transcript, then translate that into real tasks with timecodes. By the time you have a to-do list, you have spent the first hour of the job on data entry instead of editing.
- 1Listen to the whole note, usually twice.
- 2Type out a rough transcript by hand.
- 3Guess the timecode each comment refers to.
- 4Rewrite all of it as a clean task list.
The AI way: voice note in, checklist out
A better workflow transcribes the audio and parses it into discrete, timestamped tasks automatically. Instead of retyping, the voice note is transcribed and you get back structured items like 'lower the music at 0:42', 'trim the intro', and 'fix the logo at 1:10', each mapped to a moment on the timeline. Using AI here is now normal: Adobe's 2025 creators survey found 86% of creators already use generative AI in their work.
How to make a checklist from voice notes, step by step
Four steps, with no account for the client and no retyping for you:
- 1Have the client record the voice note on a zero-login review link instead of sending it in WhatsApp. It is the same habit, with no account to create.
- 2Let AI transcribe the audio and split it into separate, timestamped tasks.
- 3Review the checklist and confirm the timecodes it inferred.
- 4Export the notes as markers to your NLE for DaVinci, Premiere or Final Cut, or as SRT captions for CapCut.
Why timestamps are the hard part
The real work is not transcription. It is turning 'near the beginning, it feels slow' into a marker at 0:08. A raw transcript still leaves you scrubbing the timeline. The value is in AI inferring a timecode from natural language, so a vague phrase becomes a clickable point on your timeline instead of another search.
Keep scope creep visible while you are at it
Because the checklist is structured, it can also flag which spoken requests are brand-new versus fixes to existing work. A client rambling through a voice note often slips a new ask between two small tweaks. When those are separated automatically, you can protect your rate without re-listening to catch them.
Prelap is built for exactly this: your client records the voice note on a zero-login review link instead of WhatsApp, the same habit with no account, and you get a timestamped checklist without typing a word. Try it free on your next round of feedback.