Video Production
Stopping Product Videos From Going Stale as You Scale
A system that catches when a product video no longer matches reality, then regenerates only what changed — instead of rebuilding it from scratch.
Drift map
Every existing video mapped to the product flow it depicts, so it's immediately visible which ones no longer match what's actually shipped.
Staleness detection
An automated check comparing a video against the current state of its flow, flagging a mismatch before a customer or exec does.
Targeted regeneration
Every product flow broken into modular, reusable segments — the atomic unit a video is built from — so a single change triggers an update to just the affected segment instead of a full re-edit.
Maintenance loop
The ongoing cycle of catching drift, regenerating what changed through Claude Code, and confirming the library is current — running in the background instead of as an occasional cleanup project.
Challenge
Demo videos were expensive, one-off productions, and nobody owned the question of whether an existing one was still true. A single UI change meant re-editing footage from scratch, so teams either stopped asking for new demo content or kept publishing videos that no longer matched the product — usually noticed only after a customer or a new hire pointed it out.
Process
Every video got mapped to the flow it depicts and rebuilt as a system instead of a pile of bespoke edits: flows defined as structured, modular segments, with AI given detailed instructions for what "current" looks like for each one. That structure made two things possible at once — catching automatically when a video drifted out of date, and regenerating only the affected segment instead of the whole thing.
Research
The recurring cost was never production quality — it was that every update got treated as a full rebuild, and nobody owned the question "is this still true?" until staleness piled up silently and surfaced at the worst possible moment.
Design
Claude Code handles both halves of the system: comparing each video against the current state of its flow to catch drift, and orchestrating regeneration of just the changed segment when something needs updating — keeping the pipeline consistent across a growing library instead of depending on one editor's memory.
Outcome
The team stopped finding out about outdated videos from the outside, and updates now cost next to nothing at the margin. Sales and onboarding stopped working from stale footage, and keeping the library current turned into routine background work instead of a recurring fire drill.