This approach requires sourcing and maintaining accurate information, which means you can't fabricate numbers or exaggerate metrics. AI models increasingly cross-reference claims across sources, and inconsistencies damage credibility. The data you include must be truthful and, where relevant, attributed to primary sources. But when you consistently provide specific, accurate information, you build a reputation as a reliable source that AI models return to repeatedly.
Max Woolf (@minimaxir) is a Senior Data Scientist at BuzzFeed in San Francisco who works with AI/ML tools and open source projects. Max’s projects are funded by his Patreon.
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