The video generation platform I work on takes a reference viral ad and produces a new version with swapped product copy, fresh voice-over, and AI-generated scenes. Technically the output was correct — scenes rendered, VO synthesized, timeline stitched. But the editor's feedback was blunt: "the avatar keeps changing, random boxes in the video, no bed sound, doesn't feel the same."
That last phrase — doesn't feel the same — is the whole problem. Viral ads work because of accumulated micro-decisions: one consistent face, ambient room tone under the narration, captions that sit naturally on screen, pacing that breathes between beats. Our pipeline was optimizing for structural fidelity to the blueprint while ignoring perceptual fidelity to the reference. Over roughly 2,800 lines across several PRs, I closed that gap. This post walks through eight concrete failure modes and the fixes that made generated ads feel like they belonged to the same family as the original.
1. Avatar consistency
The protagonist changed appearance between scenes. Scene one showed a woman with short dark hair; scene three had a different face entirely. Root cause: avatar selection was random per scene. Each scene generation call picked from the avatar pool independently, the same way we might pick a background variant — except viewers experience the protagonist as a continuous character, not a per-shot casting decision.
