I vividly remember staring at the screen on what was supposed to be a rest day at 1:30 a.m. with endless unfinished clips lined up on a timeline. It was not the video editing that became my enemy, but those first few seconds when people either scroll past or get stuck to the video. That first visual was a pain. I spent more time editing my visuals of the start frame than I had ever imagined. The look was good on the editor, but the moment it became online, viewers saw it, the image didn't convey the right feelings. Some of the other edits had too many different things going on at the same time. Through my trials, it turned out that creating a good visual hook is not just about looking good, its also about the very first impression and the piece of information that is conveyed to the viewers right away.
Then, I decided to give a shot at generating a video with AI. That's not to say I was ready for replacing human hands on the editing, but I figured that the right hand of AI in video generation would save some creative time to explore the visual direction of a project before going into full-scale production.
Testing AI Video Generation Across Different Visual Concepts
I did some initial video generation testing with different concepts. To be truthful, most testing was about comparing the results generated if the same idea is described differently. The topics of product shots with a movie-making feel, creator-style videos, and quick narrative stories were my main subject matter.
Using Seedance 2 was a learning experience since the results highly depended on the structure of the prompt. A broad request like "a person working at a desk" could be any desk in any place to anyone. So to get a more specific kind of output one needs to add details about the kind of camera movement, the lights, the lens style, and the positioning of various objects in the picture. For example, if your prompt was simply:
"a person filming videos" You might get a decent footage, but it is far from being what you have in mind. However, if the prompt was something like
"a single content creator in a dark room working on a very close scene of an editor on the computer being illuminated gently by a monitor light, focusing only on the hands and keyboard being slightly out of focus, etc. etc." then the result will be more to the point.
This better result had not a thing to do with the AI being creative on its own. It was all that extra bit of detail you added when you were describing the scene. Kling 3 also proved to be useful for video generation with prompts focussing on movement. It was not only the quality of generated movements that made their difference but also the changes in subtle wording that were used for requesting movement.
By simply changing "slow camera push" into one of the other expressions like "handheld documentary movement" the feeling that the video carries would be completely different. Of these experiments, besides my emotional response, I was interested in what a machine would see. So I analyzed such machine aspects like aspect ratios, frame stability, and the compatibility of the clips with the current editing workflow. In most cases, the exports of the generated videos were prepared in standard 1.77:1 (16:9) resolution, width x height of 19201080 (1080p) size, and saved as MP4, which is the one of the formats most common on the web and the standard for online videos.
And, I reminded myself to think about visual hierarchy. It was mentioned by the YouTube Creator Academy that custom thumbnails are very important for getting attention of the viewer, making it clear what kind of video it is. This means the visuals can be generated by AI, but the human decision of what to highlight, what to keep, and how to make the viewer respond in the first place is still the human role.
The Unexpected Challenge: Good Images Can Still Feel Wrong
The most unexpected outcome was that technically brilliant generations were not always appropriate when taken to the context.
I did some creative prompting with VideoAI, running several different ideas through it, and found out how varied descriptions affected composition and workflow in a project to varying degrees. The main thing was, if you don't give clear prompts you end up with unambiguous results. AI is not a replacement of creative clarity but rather it makes you realize whether your intention is clear to you or not.
Finding Balance Between Automation and Human Taste
In the creator economy, speed often takes center stage, but consistency matters just as much. A fast-generated video that doesn’t align with your channel identity can create more work downstream.
My own workflow evolved after these experiments. Instead of opening my editor to a blank timeline, I now begin by generating and collecting visual references. Some ideas fail immediately; others become valuable guides for future projects.
There’s also a psychological benefit. When I feel stuck, generating a few rough concepts helps me move forward. They aren’t final products — they’re visual notes.
After several weeks of testing, my perspective has become more balanced. AI video generators like Seedance 2 and Kling 3 are powerful creative assistants, but they still require a creator who understands storytelling, audience expectations, and visual communication.
The machine can generate possibilities. The creator decides which ones deserve attention.
Top comments (1)
The author's experience with AI video generation tools like Seedance 2 and Kling 3 highlights the importance of detailed prompts in achieving desired results. I've had similar experiences with AI-powered video editing tools, where the quality of the output is heavily dependent on the specificity of the input. The example of changing the prompt from "a person filming videos" to a more detailed description is a great illustration of this. It's interesting to note that the author also considered machine aspects like aspect ratios and frame stability, which is crucial for seamless integration with existing editing workflows. Have you found that the time saved by using AI video generation tools is significant enough to offset the additional time spent crafting detailed prompts?