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The first tactic centers on incorporating statistics, numbers, and verifiable proof throughout your content. AI models exhibit a strong preference for factual, data-backed information over general statements or opinions. When a model encounters two sources covering the same topic, one making vague claims and another providing specific numbers with citations, the statistical content almost always wins.

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This is where historical data visualizations — of the type Claude Code can now produce on cue — can come in handy. I downloaded a scientific paper about knocking on wood along with the crowd-sourced Wikipedia list, then provided it to Claude Code and asked it to plot the data on a three.js globe. Here’s the interactive version and the GitHub page.