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Smart researchers don't trust any single source. They cross-check claims across at least three independent sources before treating something as fact.
If only one source claims something, you don't know if it's a careful finding or a mistake. If three independent sources arrive at the same conclusion separately, you have real confidence.
This is called triangulation. Real journalists, scientists, and historians all use this approach.
Asking three different AI models the same question doesn't count as three sources — they may all be trained on similar data and inherit the same errors. AI is one source. Always pair it with two human-written sources.
The big idea: real research isn't about finding one source — it's about finding three that all point to the same truth, independently.
8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-builders-research-three-sources
What is the main idea of "The Three-Source Rule"?
Which concept is most central to "The Three-Source Rule"?
Which use of AI fits this topic best?
What should a careful learner remember about "What "independent" means"?
You want to use AI after this lesson. What is the safest next step?
How should AI output about cross-reference be treated?
Name one way to verify an AI answer about cross-reference.
Which action would help you apply "The Three-Source Rule" responsibly?