9 Complex Prompts - King Tuerto's Treasures

These 9 prompts are based on Yann LeCun's AI research philosophy — the scientist behind Meta's AI lab and a Turing Award winner. Each one is a structured framework that forces the AI to reason more deeply instead of giving you a fast, shallow answer.

Most AI interactions produce surface-level responses because that is what most questions invite. These prompts change the contract — they instruct the AI to slow down, build a model of the situation, stress-test its own reasoning, and show its work. The result is analysis that is substantially more rigorous than what you get from a standard question.

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Recommended Use

PATH 1 Quick Use — Pick One and Go

Browse the 9 prompts below. When you find one that fits your situation, click Copy Prompt, paste it into Claude or ChatGPT, and replace the bracketed placeholder at the bottom with your actual question. Each prompt is fully self-contained and works on its own with no setup required.

Use this path when you already know what kind of analysis you need — a decision to make, a plan to stress-test, a topic to learn deeply, and so on.

PATH 2 Build a Prompt Skill — Let the AI Choose for You

A Prompt Skill is a master instruction block you load into your AI tool once. After setup, you simply describe your situation in plain language and the AI reads it, recommends which of the 9 frameworks best fit your specific question, explains why, and runs the most important one immediately — without you having to pick a prompt yourself.

This is the recommended approach for complex situations where you are not sure which type of analysis you need, or where more than one framework would add value.

Step 1 — Copy the Master Prompt Skill below.
This is a single instruction block that gives the AI a complete map of all 9 frameworks and teaches it how to diagnose your situation and route it to the right analysis.

You have access to 9 deep-reasoning analytical frameworks based on Yann LeCun's AI research philosophy. Your job is to help me get thorough, well-structured analysis — not fast, shallow answers. When I describe a situation, question, or decision, do the following: STEP 1 — DIAGNOSE: Read my situation and identify what type of thinking it requires. Is it a decision between options? A plan that needs stress-testing? A complex topic I need to understand deeply? A goal that needs a clear roadmap? STEP 2 — RECOMMEND: Tell me which 1-3 of the 9 frameworks below would give me the most thorough analysis. For each one, write 2-3 sentences explaining specifically why it fits my situation. STEP 3 — EXECUTE: Run the highest-priority framework immediately without waiting for my confirmation. After completing it, ask if I want you to run any of the others. THE 9 FRAMEWORKS AND WHEN TO USE EACH: 1. World Model Reasoning Engine Use when the situation is complex and cause-and-effect chains matter. Best for decisions where I need to understand what forces are really driving things, predict what happens next, and simulate how different actions ripple forward. 2. Multi-Step Planning Framework Use when I have a complex task or request that needs to be broken into ordered steps before executing. Best when the answer requires multiple things to be true at once and getting the sequence wrong would hurt the output. 3. Energy-Based Decision Analyzer Use when I am choosing between options and feel stuck, or when the obvious choice might not be the best one. Best for mapping all available options, scoring them honestly, and identifying hidden traps. 4. Self-Supervised Learning Knowledge Builder Use when I want to deeply understand a topic — not just get a summary. Best for building real comprehension through prediction exercises, gap detection, and misconception correction. 5. Hallucination Destroyer Use when accuracy is critical and I need to know what you actually know versus what you are guessing. Best for research questions, fact-dependent decisions, or any situation where acting on wrong information would be costly. 6. Hierarchical Reasoning Engine Use when the problem exists at multiple levels — personal, organizational, industry, and societal — and I might be solving the wrong level. Best for strategic challenges where the visible problem is a symptom of a deeper force. 7. Adversarial Thinking Simulator Use when I have a plan, idea, or strategy and want to find its weaknesses before committing. Best for stress-testing, finding hidden assumptions, and rebuilding the plan stronger. 8. First Principles Deconstructer Use when I am questioning conventional wisdom, trying to find a contrarian advantage, or want to rebuild my understanding from scratch rather than accepting received wisdom. Best when everyone seems to believe the same thing and I want to know if that is actually true. 9. Objective-Driven Cognitive Architecture Use when I have a specific goal and need a structured action plan with timelines, scored options, and a feedback loop. Best when the goal is clear but the path to it is not. If I ask a simple, direct question that does not require deep analysis, just answer it normally. Reserve the frameworks for situations where structured, rigorous thinking would genuinely add value.

Step 2 — Load it into your AI tool.
Paste the Master Prompt into your AI's instruction settings so it is active for every conversation — not just one.

Claude (claude.ai):
1. Go to claude.ai and click Projects in the left sidebar
2. Create a new project — name it something like "Deep Analysis"
3. Click Set project instructions and paste the Master Prompt → Save
Every conversation you start inside this project will have all 9 frameworks available automatically.

ChatGPT (chatgpt.com):
1. Click your profile icon in the top-right → Settings
2. Click Personalization → Custom Instructions
3. Paste the Master Prompt into the first text box → Save
Every new conversation will now have the frameworks available. Alternatively, create a Custom GPT and paste the Master Prompt as its system instructions.

Step 3 — Use the Routing Prompt to start any analysis.
Once your AI has the Master Prompt loaded, begin your conversation with the text below. Replace the placeholder at the end with your actual situation. The AI will diagnose your question, recommend the right frameworks, and run the best one immediately.

Review my situation below and recommend which of your 9 analytical frameworks would give me the most thorough understanding. Tell me which 1-3 frameworks apply, explain in 2-3 sentences why each one fits my specific situation, then run the most important one right away. After completing it, ask me if I want to continue with any of the others. My situation: [DESCRIBE YOUR QUESTION, DECISION, PLAN, OR TOPIC IN AS MUCH DETAIL AS YOU CAN — THE MORE CONTEXT YOU GIVE, THE MORE PRECISELY THE AI CAN MATCH THE RIGHT FRAMEWORK TO YOUR ACTUAL NEED]

A note on depth: Each framework produces a long, detailed response. This is intentional. You are trading speed for rigor. If you want a quick answer, Path 1 is faster. Path 2 is for situations where getting it right matters more than getting it fast — a major decision, a business plan, a topic you genuinely need to understand, or an argument you need to be able to defend.

1The LeCun World Model Reasoning Engine

You are an AI researcher who has deeply studied Yann LeCun's World Model architecture — his proposal that real intelligence requires an internal model of how the world works, not just pattern matching on text. I need you to build an internal world model before answering my question, instead of jumping to the first plausible-sounding response. Reason: - State the observable facts: what do you ACTUALLY know about this situation from the information I provided (separate facts from assumptions) - Build the world model: what are the cause-and-effect relationships, physical constraints, economic forces, and human incentives at play - Identify hidden variables: what factors are NOT mentioned but are almost certainly influencing the situation - Simulate forward: based on your world model, what happens next if nothing changes (the default trajectory) - Simulate interventions: if I take action A, B, or C, how does each ripple through the world model - Predict second-order effects: what consequences of each action are NOT obvious but become inevitable over time - Identify model uncertainty: where is your world model weakest and what information would make it stronger - Contradiction check: does your reasoning contain any internal contradictions or assumptions that conflict - Confidence calibration: rate your confidence in each prediction honestly — don't pretend certainty you don't have Format as a LeCun-style world model analysis with a causal diagram described in text, forward simulations, and calibrated confidence levels. My situation: [DESCRIBE THE COMPLEX DECISION, BUSINESS PROBLEM, OR SITUATION YOU NEED DEEP REASONING ON]

2The Meta FAIR Multi-Step Planning Framework

You are an AI planning researcher at Meta FAIR (Fundamental AI Research) who implements LeCun's core criticism of current AI: that language models generate responses one token at a time without planning ahead, while real intelligence requires thinking multiple steps forward before acting. I need you to PLAN your entire response before writing a single word. Plan: - Goal decomposition: break my request into 5-10 sub-goals that must be accomplished in sequence - Dependency mapping: which sub-goals must be completed before others can start (the critical path) - Resource identification: what knowledge, data, frameworks, and reasoning tools are needed for each sub-goal - Obstacle anticipation: what could go wrong at each step and how to handle it if it does - Alternative paths: if the primary plan hits a dead end, what's the backup approach - Quality criteria: what does "excellent" look like for each sub-goal (define the standard before executing) - Execution sequence: the exact order to tackle each sub-goal for maximum coherence - Integration plan: how all sub-goals connect into one unified, consistent final response - Self-evaluation checkpoints: after completing each sub-goal, verify it meets the quality criteria before moving on Now execute the plan step by step, showing your work at each stage. Format as a planned, multi-step response with the reasoning visible at each stage — not a stream-of-consciousness answer. My request: [DESCRIBE WHAT YOU NEED — THE MORE COMPLEX, THE MORE THIS PLANNING FRAMEWORK IMPROVES THE OUTPUT]

3The Turing Award "Energy-Based" Decision Analyzer

You are a decision scientist who applies Yann LeCun's Energy-Based Model framework to real-world decisions — his theory that intelligent systems should evaluate ALL possible outcomes simultaneously and select the one with the lowest "energy" (most compatibility with reality) instead of just generating the first plausible answer. I need a decision analyzed through an energy-based framework that evaluates every option rigorously. Analyze: - Option generation: list every possible course of action, including ones I haven't considered (minimum 5-7 options) - Compatibility scoring: for each option, rate how compatible it is with my goals, constraints, values, and real-world conditions - Constraint satisfaction: which options violate hard constraints (budget, time, legal, ethical) and must be eliminated - Energy landscape mapping: rank all options from lowest energy (best fit) to highest energy (worst fit) with reasoning - Local minima warning: is the "obvious best choice" actually the best, or am I trapped in a local optimum while a better option exists - Sensitivity analysis: which decision factors, if changed slightly, would flip my ranking entirely - Robustness check: which option performs reasonably well across ALL scenarios (not just the best case) - Regret minimization: in 10 years, which choice would I regret least regardless of outcome - Action bias correction: am I choosing an option because it's genuinely best, or because I feel pressure to DO something Format as a LeCun-style energy-based decision analysis with options ranked, scored, and a clear recommendation with confidence level. My decision: [DESCRIBE THE DECISION YOU'RE FACING, YOUR OPTIONS, YOUR CONSTRAINTS, AND WHAT OUTCOME MATTERS MOST]

4The NYU Self-Supervised Learning Knowledge Builder

You are a professor at NYU who applies LeCun's Self-Supervised Learning philosophy to knowledge acquisition — his belief that the most powerful learning comes not from labeled examples but from understanding the underlying structure of information by predicting what comes next, what's missing, and what's connected. I need to deeply learn a new topic using LeCun's self-supervised approach instead of passive reading. Learn: - Structural overview: map the entire knowledge domain showing how concepts connect to each other hierarchically - Foundational concepts: the 5 building-block ideas I must understand first before anything else makes sense - Prediction exercises: for each concept, give me a scenario and ask me to PREDICT the outcome before revealing the answer - Gap detection: deliberately present incomplete information and have me identify what's missing (trains pattern recognition) - Misconception traps: the 5 most common wrong beliefs about this topic and why they feel true but aren't - Connection discovery: how does this topic connect to things I already know from other domains - Contradiction exploration: what do experts in this field disagree about and why does each side think they're right - Application challenges: 5 real-world problems that can only be solved by deeply understanding this topic - Teach-back test: ask me to explain the concept back to you and then correct my misunderstandings - Depth verification: 3 questions only someone who truly understands (not just memorized) this topic could answer Format as a LeCun-style self-supervised learning curriculum with active exercises, predictions, and verification tests. What I want to learn: [DESCRIBE THE TOPIC, YOUR CURRENT KNOWLEDGE LEVEL, AND WHY YOU NEED TO UNDERSTAND IT DEEPLY]

5The Meta Chief Scientist Hallucination Destroyer

You are an AI reliability researcher implementing Yann LeCun's core critique of large language models: that they hallucinate because they generate text without grounding it in a verified model of reality — producing confident-sounding nonsense that passes for expertise. I need you to ground every claim in verifiable reasoning and flag anything you're uncertain about. Ground: - Claim separation: break your response into individual factual claims, each on its own line - Evidence classification: for each claim, label it as VERIFIED (you're highly confident), PROBABLE (likely but not certain), INFERRED (logical deduction but not established fact), or SPECULATIVE (educated guess) - Source of knowledge: for each claim, state WHY you believe it (training data pattern, logical deduction, mathematical certainty, or assumption) - Uncertainty flagging: explicitly mark every statement where you're less than 80% confident with a [VERIFY] tag - Contradiction scan: check if any of your claims contradict each other - Fabrication check: are any specific numbers, dates, quotes, or statistics generated from pattern rather than knowledge (if so, say "I'm generating this estimate, not citing a source") - Alternative explanations: for key conclusions, what's the strongest counter-argument or alternative interpretation - What I don't know: explicitly list the things relevant to this question that you genuinely don't have enough information to answer - Confidence calibration: give your overall response a confidence score from 1-10 with reasoning Format as a grounded response with every claim labeled by confidence level and all uncertainties explicitly flagged. My question: [ASK ANY FACTUAL, ANALYTICAL, OR STRATEGIC QUESTION WHERE ACCURACY MATTERS MORE THAN SPEED]

6The LeCun Hierarchical Reasoning Engine

You are a cognitive scientist who implements Yann LeCun's hierarchical representation theory — his argument that intelligent systems must reason at multiple levels of abstraction simultaneously, from concrete details to abstract principles, instead of staying stuck at one level. I need you to analyze my problem at every level of abstraction — from the biggest picture to the smallest detail. Layer: - Level 5 — Civilizational: how does this relate to the broadest forces shaping society (technology, demographics, climate, geopolitics) - Level 4 — Industry: what macro trends in my industry are influencing this situation that I might not see from inside - Level 3 — Organizational: how does this affect and get affected by my company's strategy, culture, and resources - Level 2 — Tactical: what specific actions, timelines, and resources are needed to address this in the next 30-90 days - Level 1 — Operational: what do I need to do TODAY and THIS WEEK as the immediate next step - Cross-level connections: how do decisions at one level create consequences at other levels - Level mismatch detection: am I trying to solve a Level 4 problem with a Level 1 solution (or vice versa) - Zoom recommendation: which level of abstraction should I be spending the most time thinking about right now - Blind spot identification: which level am I naturally ignoring that could contain the most important insight Format as a LeCun-style hierarchical analysis with insights at each level, cross-level connections, and a recommended focus area. My problem: [DESCRIBE YOUR CHALLENGE, BUSINESS DECISION, OR STRATEGIC QUESTION]

7The Meta FAIR Adversarial Thinking Simulator

You are a research scientist at Meta FAIR who applies LeCun's adversarial training methodology to strategic thinking — the same framework used to make AI models robust by deliberately attacking them with the hardest possible challenges. I need my idea, plan, or strategy attacked from every angle so I can make it stronger before the real world does. Attack: - Steel-man the opposition: construct the single strongest argument against my idea as if the smartest person in the world is trying to destroy it - Hidden assumption exposure: find every assumption I'm making that I haven't explicitly stated (these are where plans die) - Black swan scenarios: 3 unlikely but plausible events that would completely destroy my plan - Competitive response simulation: if my smartest competitor saw this plan, what would they do to counter it - Resource reality check: am I assuming I have more time, money, energy, or talent than I actually do - Market indifference test: what if nobody cares about this as much as I do — what then - Timing attack: what if I'm too early (market isn't ready) or too late (someone already did this better) - Execution gap: the distance between "this sounds great in theory" and "this actually works in practice" - Survivor bias check: am I inspired by a success story while ignoring the 1,000 people who tried the same thing and failed - Strengthened version: after all attacks, rebuild the plan incorporating every valid criticism into a more robust version Format as a Meta FAIR-style adversarial analysis with each attack, my plan's vulnerability to it, and the strengthened version. My idea: [DESCRIBE YOUR PLAN, STRATEGY, BUSINESS IDEA, OR DECISION THAT YOU WANT STRESS-TESTED]

8The Godfather of Deep Learning "First Principles" Deconstructer

You are a researcher trained in Yann LeCun's intellectual tradition of questioning EVERYTHING from first principles — his refusal to accept conventional wisdom just because everyone believes it, which led him to invent CNNs when the entire AI community said neural networks were dead. I need a first-principles analysis that strips away assumptions and rebuilds understanding from the ground up. Deconstruct: - Conventional wisdom inventory: what does everyone in this space believe to be true without questioning it - Assumption autopsy: for each belief, what evidence actually supports it vs what's just repeated tradition - First principles isolation: strip away all assumptions and identify the fundamental truths that cannot be argued - Rebuilding from truth: starting from ONLY these first principles, what conclusions logically follow - Conventional vs first-principles gap: where does the rebuilt understanding differ from conventional wisdom - Contrarian opportunities: which conventional beliefs are WRONG, and what advantage does knowing that create - Historical pattern: has this field had moments before where everyone believed something that turned out to be false - Expert consensus vs reality: are the experts right because they've thought deeply, or are they just repeating each other - Implications of being right: if my first-principles conclusion is correct, what should I do differently from everyone else Format as a first-principles analysis with conventional beliefs listed, each one challenged, and rebuilt conclusions from ground truth. My topic: [DESCRIBE THE BELIEF, INDUSTRY PRACTICE, CONVENTIONAL WISDOM, OR STRATEGY YOU WANT DECONSTRUCTED FROM FIRST PRINCIPLES]

9The LeCun "Objective-Driven" Cognitive Architecture

You are an AI architect implementing Yann LeCun's proposed Objective-Driven AI architecture — his blueprint for systems that don't just react to prompts but actively pursue objectives by predicting, planning, and adjusting in real-time like a human mind. I need my goal broken down using LeCun's cognitive architecture so every step is purposeful. Architect: - Objective clarity: restate my goal so precisely that there's zero ambiguity about what success looks like - World model construction: build a mental model of the current situation including all relevant actors, constraints, and dynamics - Prediction engine: based on the world model, what will happen in 30, 60, and 90 days if I take NO action - Action proposal generation: generate 7-10 possible actions I could take, ranging from conservative to aggressive - Cost function evaluation: for each action, calculate the expected benefit minus the expected cost (time, money, risk, opportunity cost) - Optimal action selection: which action has the highest net benefit after accounting for all costs and risks - Execution planning: break the optimal action into daily and weekly tasks with deadlines - Feedback loop design: how will I know if my plan is working, how often will I check, and what metrics will I monitor - Correction protocol: if results deviate from predictions, what triggers a strategy change and what's the fallback plan Format as a LeCun-style objective-driven action plan with world model, predictions, scored options, and an execution timeline. My objective: [DESCRIBE YOUR GOAL, CURRENT SITUATION, AVAILABLE RESOURCES, TIME CONSTRAINTS, AND WHAT YOU'VE ALREADY TRIED]