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DEJAN uses an iterative Bayesian optimization loop that crafts targeted snippet edits against competitor search results, testing hypotheses with Thompson sampling to climb AI ranker preferences across structured Rank Factor classes.

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  1. 1 How does the Bayesian optimization loop work? (recommended)
  2. 2 What are the seven Rank Factor classes?
  3. 3 How does the system distinguish snippet mode from page mode?
  4. 4 What is the role of the Custodian in minting new factors?

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