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Challenge: Present an LLM with a classic ethical dilemma (e.g., the Trolley Problem or a scenario involving privacy vs. security). Ask it to argue for both sides of the dilemma, using different ethical frameworks (like utilitarianism and deontology).

Challenge: Present an LLM with a classic logic puzzle (e.g., an Einstein Riddle or a Knights and Knaves puzzle). Ask it to solve the puzzle and explain its reasoning step-by-step.

Improve complex reasoning by asking the model to 'think step by step' before giving its final answer. This simple instruction prompts LLMs to break down the problem-solving process, often resulting in more accurate answers.

For mathematical or logical reasoning problems, adding the phrase 'Let's think step by step' before the LLM generates its solution significantly improves accuracy.

A more advanced technique where the LLM is prompted to generate both reasoning traces and actions to take to solve a problem, often interacting with external tools.

Ask the LLM to think about its thinking process: 'Before answering, consider what approach would be most effective for this problem and explain your reasoning strategy.'

Improve complex reasoning by asking the model to 'think step by step' before giving its final answer. This simple instruction prompts LLMs to break down the problem-solving process, often resulting in more accurate answers.