What part of your AI-assisted YouTube workflow do you rebuild most often?

I keep seeing the same failure mode in recurring creator work: the AI conversation produces useful output, but the source notes, approved prompt, revision decision, and next action are scattered when the next session starts.

I built ChannelOps around a simple boundary: AI prepares the next work packet; the creator still reviews, approves or rejects the exact revision, and separately authorizes anything public.

For people already using ChatGPT or Claude for a weekly YouTube workflow, which state is hardest to preserve between sessions—sources, approved prompts, revision history, rights checks, or the next action?

I am the maker of Pixelora ChannelOps and am using this thread to learn where the workflow breaks in real use. No automation or performance claim is implied.