Diagnosis
Why your AI video looks generic, and what to change
Six specific habits that produce stock-footage output, and the specific replacement for each.
01
You described a subject instead of a shot
"A woman drinking coffee in a cafe" has no camera, no light and no time in it. The model fills all three with its average, and the average is stock footage.
Replace with: where the camera is, what it does, what lights her, and what changes across the clip.
02
You used style words instead of physical ones
"Cinematic", "epic", "beautiful", "high quality", "4K", "masterpiece" carry almost no information. They mostly push output toward whatever is most common in the training data labelled that way — which is, by definition, generic.
Replace with physical description: focal length, aperture, light source, camera move, colour palette.
03
Everything in your frame is perfect
Real spaces have wear, clutter, uneven light and asymmetry. Prompts that describe pristine surfaces and perfect styling produce images that read as renders.
Replace with: one specific imperfection. A worn edge, a coat over a chair, an uncorrected mix of daylight and lamp light, a surface marked by use.
04
Your lighting is flat and frontal
Even, shadowless lighting is the default and the giveaway. It removes depth and makes everything look like a product shot.
Replace with: one dominant source and a stated shadow side. Even a single sentence about what the light does not reach changes the entire image.
05
Nothing happens over time
A prompt with no described change produces a clip where the camera moves and nothing else does.
Replace with: one thing that changes. Something enters, something falls, light shifts, a person turns, steam rises and clears.
06
You changed everything at once between attempts
Rewriting the whole prompt after each result means you never learn what your generator responds to.
Replace with: one variable per iteration. Keep the version that worked and change the next thing.
