As Deep as You Can Go
Name any science or math topic. The AI finds your actual level in four questions, then takes you down as deep as you can go, one rung at a time.
Take me down a rabbit hole into [TOPIC: entropy / quantum measurement / infinity / Bayes / evolution / Gödel, or write "surprise me"]. Do not start explaining yet. Find out where I actually am first, then take me as deep as I can go. PHASE 1: CALIBRATION (three questions plus an adaptation rule, one at a time, no explaining yet) 1. "Explain [topic] to me in two sentences, in your own words." My vocabulary tells you my level. Do not ask me to rate myself: self-assessment is unreliable in both directions. 2. A mid-difficulty question I have to answer with a committed answer plus a confidence rating 0-100. Design it so the common wrong belief produces a specific, identifiable wrong answer, not a vague one. 3. "What do you already understand deeply?" (my job, my hobby, my field). Every analogy from here on comes from that domain. The adaptation rule, applied after question 2: right with high confidence, jump two levels harder. Right but hesitant, one level. Wrong, drop a level and probe what my wrong answer reveals about my underlying model. Then tell me where I am and name the rungs from here down to the deepest one that exists, so I can see the whole ladder before we start down it. PHASE 2: THE DESCENT. One rung per exchange. On every rung: - Ask me to predict before you reveal: "what do you think happens if...?" A wrong prediction is the encoding event, not a failure. Guessing wrong first beats being told first. - Make me explain it back before you elaborate. If I can't, that's the gap; work there. - When you use an analogy, attach its expiry date: what it captures, and exactly where it breaks. Then, a rung later, break it on purpose and show me why the break is the interesting part. - Confront misconceptions instead of explaining around them. If my answer reveals a wrong model, say the wrong model out loud, then refute it using my own premise rather than asserting the right answer. A clear explanation that never names the wrong belief leaves it fully intact and just makes me more confident. - Depersonalize it: "most people, including physics graduates, say X", never "you're wrong". - Every third rung, return unannounced to something I claimed earlier and ask whether it still holds. PHASE 3: THE FLOOR. Keep going until we hit one of two floors: the edge of what I can follow, or the edge of what anyone knows. If it's the second, stop and stay there: tell me exactly what's unresolved, who is arguing about it, and what evidence would settle it. Do not paper over an open question with a confident summary. Rules: - Do not hand me an answer I could reach with one more question. If I ask for help three times in a row without attempting anything, stop and ask which specific part of the last hint I'm stuck on. Be firm about this. - If I'm genuinely lost after two attempts, downshift to a concrete worked example or a simpler case, then pick the descent back up where we left it. - At the depth where a metaphor stops being honest, show me the actual equation or definition and explain what each piece means and why it's arranged that way. Assume I can handle the real object. - Say "nobody knows" when nobody knows, and separate established science from live speculation every time. End by handing me the next three doors: what to read, what to try, and the question in this area nobody has answered yet. One warning up front: this will feel slower than being told. That is the point.
How to use
Answer the prediction questions before reading on, even when you are sure you'll be wrong, because guessing wrong first beats being told first and the whole design rests on it. The calibration phase is what lets one prompt serve a physicist and a curious beginner without patronizing either. Built on education research that replicates: the pretesting effect, Derek Muller's PhD finding that clear explanations which never name the misconception raise confidence without raising learning, and the tutoring rule about never handing over the answer. Strongest starting topics: entropy, infinity, Bayes, Gödel, the quantum measurement problem.
More rabbit hole prompts
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The Reason and the Real Reason
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