I didn’t start using AI for video editing because I wanted to “optimize my workflow.” It started much more simply.
In early March, I had 30+ raw clips sitting on my drive and no motivation to edit them. Each one was between 8 and 15 minutes long. They were just screen recordings, talking-head explanations, and random test videos I had recorded over the past month.
Normally, this would mean at least a week of editing. But I decided to do something different: I would try to turn all of them into Shorts using AI tools in 7 days.
Not as a productivity experiment, more because I was curious whether AI would actually reduce friction or just create a different kind of work.
Day 1: The First Reality Check
I started with Opus Clip because it was the most recommended tool everywhere.
I uploaded a 12-minute tutorial video expecting it to “find the best moments automatically.”
It did generate about 8 clips in a few minutes.
The first problem showed up immediately.
Half of the clips started mid-sentence. One clip cut off right before I explained the actual result. Another one had a strong hook, but the conclusion was missing entirely.
Technically, the AI did what it was designed to do — detect “engaging segments.” But what it considered engaging and what actually made sense as a standalone Short were two different things.
I didn’t publish anything that day.
Instead, I spent time manually rewatching every clip and rebuilding 2 of them from scratch.
That’s when I realized something important:
AI doesn’t create Shorts. It creates options.
Day 2–3: Speed Increase, But Not in the Way I Expected
By the second day, I stopped trusting AI clips directly.
Instead, I changed the workflow:
- Upload long video
- Let AI generate clips
- Use them only as “timestamps”
- Re-edit manually in CapCut
This actually worked better.
In CapCut, I noticed something interesting. Even though AI had identified 10 potential clips, I only ended up using 2 from each video.
The rest were either:
- context-dependent
- too slow
- or emotionally flat when isolated
One clip in particular stood out.
It was a 45-second section where I explained a mistake I made while testing a tool. AI had rated it as “medium engagement.”
But after I tightened the pacing manually and cut the first 3 seconds, it became one of the best-performing Shorts that week.
That was the first moment I started trusting my own judgment more than AI scoring systems.
Day 4: The Caption Problem
This was where things got more frustrating.
I tried letting AI handle captions completely.
At first it looked fine. Subtitles were generated instantly, and timing was accurate most of the time.
But when I actually watched the exported video, I noticed something off.
Technical terms were consistently misheard.
For example:
“frame rate” became “framerate”
“CapCut” became “cap cut”
“retention” became “rotation”
Small errors, but they made the content feel less credible.
I spent almost 2 hours fixing subtitles manually for just 5 Shorts.
That was the moment I realized:
AI saves time, but it also introduces invisible cleanup work.
Day 5: The First Real Breakthrough
On Day 5, I changed my approach completely.
Instead of trying to “fix AI clips,” I decided to build Shorts around better source material.
I recorded a new 15-minute video with one rule:
No editing mindset while recording.
I just spoke naturally, as if I was explaining something to a friend.
Then I tested the same AI workflow again.
This time, results were noticeably better.
Not because the AI improved — but because the input was clearer.
Two clips came out almost usable immediately.
That’s when something clicked:
AI doesn’t fix weak structure. It amplifies clarity when it already exists.
Day 6: The Over-Editing Mistake
This was probably my worst day in the experiment.
I got too confident. I started adding effects:
- fast zoom transitions
- animated captions
- sound effects
- punch-in cuts every few seconds
It looked “professional” at first. But when I watched the final exports, something felt wrong. The pacing was exhausting. Even I didn’t want to rewatch my own videos. So I posted one anyway just to test performance. It performed worse than my simpler edits from Day 3. That was a bit uncomfortable to accept.
*I had assumed more editing = better engagement.
*
But it turned out the opposite was true.
Day 7: Simplifying Everything Again
By the final day, I went in the opposite direction.
I removed almost everything “AI-style” from my workflow:
- fewer transitions
- cleaner captions
- no forced zoom effects
- no overuse of highlight animations
The editing became simpler, but strangely faster.
Instead of trying to make every second “interesting,” I focused on:
- clarity of message
- pacing of speech
- strong opening 2 seconds
- natural rhythm
I also noticed something important:
The Shorts that performed best were not the ones with the most editing. They were the ones where viewers understood the point immediately.
What Actually Changed After 7 Days
Looking back, the biggest change wasn’t speed. It was judgment. AI didn’t replace editing for me. It changed what I pay attention to.
Before this experiment, I thought editing was about:
- cutting faster
- adding effects
- optimizing retention graphs
*After 7 days, I realized editing is mostly about:
*
- deciding what matters
- removing what doesn’t
- protecting clarity
AI helped with speed, but it didn’t help with those decisions.
The Tool I Still Use (But Differently Now)
I still use tools like Opus Clip and CapCut. But my relationship with them changed. I no longer treat AI as a “decision maker.” It’s more like a rough assistant that:
- finds timestamps
- speeds up transcription
- suggests starting points
Even AVCLabs AI Video Generator, which I tested during this period, ended up in the same category for me — useful for quick experiments or generating visual variations, but not something I rely on for final creative decisions.
It helps test ideas, not define them.
Final Thought
If there’s one thing I learned from editing 30 Shorts with AI in a week, it’s this: AI doesn’t make editing easier in a straight line. It changes where the work happens.
Less time is spent cutting clips. More time is spent making judgment calls.
And honestly, that part never really goes away — no matter how advanced the tools get. The creators who benefit most from AI aren’t the ones who automate everything. They’re the ones who still care about what the video actually says.
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