The claim — called out in the video as the single rule most worth remembering — that tighter camera framing produces less visible AI artifacting ("slop") than wide or aerial shots. Wider shots give the model more space to get rule-governed elements wrong (traffic, crowds, multiple actors interacting), which is exactly the failure mode described in Rule-Governed Behavior as an AI Video Model Failure Point.
"If you remember one rule from this video, make it this one. The tighter the frame, the less slop you get."
Default to closer, tighter framing over wide or aerial shots, especially for any scene with rule-governed elements (traffic, multiple actors, crowds) that the model is prone to getting wrong. Reserve wider shots for simpler content where there's less for the model to break.
The reason tighter framing reduces visible errors ties directly to Rule-Governed Behavior as an AI Video Model Failure Point: a wide or aerial shot puts more simultaneous rule-governed elements in frame at once — multiple traffic lights, multiple lanes, several background actors — and every one is a chance for the model to get a rule wrong. Tighter framing isn't just a stylistic choice here; it's a deliberate way to shrink the number of rule-governed elements visible at once and hide the model's weak points.