AI search tools can accelerate information access, but they also increase a dangerous behaviour: outsourcing recall to the tool. If you are revising for exams, the only thing that counts is what you can retrieve unaided. The solution is to treat AI as a drafting assistant for prompts — never as the final state of your learning.
The rule: search is not revision
If you look something up and move on, you trained dependence, not competence. Your workflow must end in a self-test artefact and a spaced revisit, otherwise it does not compound.
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Step 1 — Ask a narrowly scoped question
Keep the question small enough that you can test yourself on it in under 2 minutes. Broad questions create broad answers you cannot retrieve.
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Step 2 — Convert the answer into 5 prompts
Prompts must be testable: “What cue triggers X?” “What single feature separates A vs B?” “What is the common pitfall?” “What do I do first?” “What do I reassess?”
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Step 3 — Compress into one-line rules
If your rule cannot fit on one line, it is not operational under time pressure. Keep it short, specific, and discriminating.
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Step 4 — Retrieval test immediately
Close everything. Answer your 5 prompts from memory. Then reopen only to correct gaps. This is where learning happens (attempt → feedback).
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Step 5 — Spaced maintenance
Re-answer the same 5 prompts at 48 hours and 7 days. If you miss a prompt, shorten the interval and rewrite the rule.
SourceRoediger & Karpicke (2006): Testing effect (PubMed)
Open Link SourceCepeda et al. (2006): Distributed practice meta-analysis (PubMed)
Open Link SourceOpenEvidence in primary care: example of AI EBM tool evaluation (open access, PMC)
Open Link