Your question (translated):What makes a good prompt, and how can it improve AI outputs?First principlesA prompt is not “asking a question.”It is defining a function:Output f(Instruction, Context, Constraints, Format)If output is bad, one of these inputs is underspecified.What is a “good prompt”?A good prompt reduces ambiguity increases structureClear objective (What problem?)Bad: “Explain AI”Good: “Explain AI to a beginner in 3 key ideas with real-world examples” Principle: Minimize interpretation spaceSufficient context (What background?)AI has no memory of your situation unless you provide it.Bad: “Give me diet advice”Good: “28-year-old female, 54kg, wants simple healthy meals for weight maintenance” Principle: Context constraints on solution spaceExplicit constraints (What limits?)Without constraints → AI defaults to generic answersExamples:length: “in 100 words”depth: “first-principles explanation”audience: “for a non-technical person” Principle: Constraints force prioritizationOutput format (How should it look?)Bad: open-endedGood:bullet pointstablestep-by-stepJSON (for automation) Principle: Format compress entropy into structureRole / perspective (Optional but powerful)Example:“Act as a senior product manager”“Explain like a teacher using analogies” Principle: Role bias the reasoning pathHow this improves AI outputThink of AI as a probability engine over text.A vague prompt → wide probability distribution → generic outputA precise prompt → narrow distribution → high-quality outputExample (before vs after)❌ Weak prompt“Help me invest”→ Output: generic advice✅ Strong prompt“Act as a long-term value investor.I have $10k, low risk tolerance, 5-year horizon.Give 3 allocation strategies with pros/cons and expected risks.”→ Output:structuredrelevantdecision-readyAdvanced pattern (high leverage)Use this template:Goal: [what you want]Context: [your situation]Constraints:[limit 1][limit 2]Output format:[structure]Style:[optional]Meta insightGood prompting is not about “better wording”It is about:Reducing uncertainty in the model’s decision space中文总结提炼好的提示词本质是用目标 上下文 约束 格式压缩AI的不确定性核心三点减少歧义说清你要什么增加约束限制范围避免泛化结构输出让结果可用一句话 提示词不是“问问题”而是“定义结果的边界条件”