The Bottom Line
- AI can accelerate learning—or produce confident nonsense. Your process decides.
- Use AI to generate questions, discriminators, and study plans—not final truths.
- Verification-first means: sources → cross-check → retrieval → retest.
The risk: false mastery
The most dangerous AI failure mode is not a wrong fact—it’s the feeling of understanding without the ability to retrieve under exam conditions.
If you use AI, treat it like a fast junior colleague: brilliant at drafting, weak at epistemic humility. Your guardrails should force: (1) explicit uncertainty, (2) source anchoring, and (3) retrieval-based outputs.
1
Prompt for retrieval, not explanation
Ask: ‘Give me 12 single-best-answer questions on X with explanations and one discriminator per item.’
2
Force source anchoring
Ask: ‘List the guideline/textbook sources you used. If unsure, say unsure.’ Then cross-check one key claim.
3
Extract discriminators
Ask: ‘For each confusable pair, give me the one feature that flips the answer.’
4
Convert to retest tickets
Ask: ‘Schedule a 72h and 7d retest plan using 15 questions each time.’
5
Do a ‘no-AI’ retest
Within 48–72h, do timed questions with no AI. This is the integrity check.
My AI study guardrails
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Practice
Test your knowledge
Apply this concept immediately with a high-yield question block from the iatroX Q-Bank.
SourceChain-of-Verification (approaches to reduce confident errors)
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