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AI Content Workbench: Building the Pipeline from Material to Draft Box in Three Days

89 itemsCumulative items in material library
399Cumulative number of topics to be selected
5Number of AI-summarized revision habits
01

What this case covers

The author is a self-media creator exploring AI video and content going global, and built a content workbench with Claude. The article covers material collection, topic extraction, annotated revision, multi-platform draft box pushing, and Feishu archiving.

02

Questions it answers

  1. How does the workbench turn Feishu Minutes into material?
  2. How does AI distinguish who said what when extracting topics?
  3. What are the advantages of annotated revision compared with notes in the main text?
  4. How does the workbench learn the author's revision habits?
  5. Why does multi-platform pushing only go to the draft box?
03

Our observations

  1. Automatic material entry is only the starting point; attaching original quotes to topics is what preserves attribution of viewpoints.
  2. Only after revision habits are recorded is there a chance to reduce repeated edits.
  3. Pushing only to the draft box leaves the final publishing authority in the author's hands.
04

From the author

Actually, it's not that I have nothing to write; it's that information is too scattered + the cost of organizing and publishing is high, so I just couldn't be bothered to do it.
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