Skill 13: System Prompt Learning（系统提示学习范式）
Source: https://x.com/karpathy/status/1921368644069765486 "System prompt learning — missing LLM learning paradigm"
Core Principle
The system prompt is a textbook. Write it like one.
Karpathy's insight: there are three learning modes for LLMs (pretrain, finetune, RL) — but there's a fourth that's massively underused: system prompt learning. Explicitly encoding strategy into the system prompt is more sample-efficient than retraining and more reliable than hoping the model figures it out.
Think of it as writing a textbook for the LLM before each task. Not just instructions — strategy with reasoning.
The System Prompt Learning Framework
Good system prompts have three layers (mirroring how humans learn):
Layer 1: EXPOSITION (pretrain equivalent) → Background knowledge the model needs → Relevant concepts, terminology, context → "Here's what you need to know about [domain]" Layer 2: WORKED EXAMPLES (SFT equivalent) → Step-by-step demonstration of correct behavior → Explicit reasoning traces → "Here's exactly how to handle [situation]" Layer 3: STRATEGY (RL equivalent) → Explicit decision rules → Error patterns to avoid → "When you see X, do Y because Z"
Building a System Prompt from Scratch
Build a system prompt that teaches an LLM to [TASK] reliably. Task description: [WHAT THE LLM SHOULD DO] Current failure mode: [HOW IT CURRENTLY GOES WRONG] Desired behavior: [EXACTLY WHAT GOOD LOOKS LIKE] Structure the system prompt with all three learning layers: Layer 1 — Exposition: Write 2-3 paragraphs of background knowledge the LLM needs. Include: key concepts, relevant context, domain vocabulary. Layer 2 — Worked Examples: Write 2 complete examples of the task done correctly. Format: INPUT → [step-by-step reasoning] → OUTPUT Show the thinking, not just the answer. Layer 3 — Strategy: Write explicit decision rules as IF/THEN/BECAUSE statements. Include: common mistakes to avoid, edge cases to handle, quality checks. End with: "Before responding, verify: [checklist of 3-5 quality checks]"
Improving an Existing System Prompt
When your current system prompt isn't working well:
Diagnose and improve this system prompt. Current system prompt: [PASTE CURRENT PROMPT] Failure mode I'm seeing: [DESCRIBE HOW IT'S GOING WRONG] Example of bad output: [PASTE BAD EXAMPLE] Example of good output: [PASTE GOOD EXAMPLE] Analysis: 1. What's missing from the exposition layer? (background knowledge gaps) 2. What worked examples should I add? 3. What explicit rules would prevent this failure mode? 4. Is the prompt too restrictive? Too vague? Wrong framing? Output: improved version of the system prompt with changes annotated.
Strategy Encoding Templates
For coding tasks
SYSTEM PROMPT: [CODING TASK] You are an expert [LANGUAGE] developer. Follow this exact strategy: UNDERSTANDING PHASE (always do this first): - Restate the task in your own words - List all edge cases you can think of - Identify the one tricky part IMPLEMENTATION PHASE: - Start with the simplest working version - Add complexity only when simple version fails - Comment every non-obvious line with WHY VERIFICATION PHASE (always do this last): - Trace through your code with one concrete example - Check: does it handle empty input? Large input? Wrong type? - Confirm: could a junior dev maintain this? NEVER: - Assume the input is well-formed without checking - Add dependencies without saying why - Write clever code when simple code works
For analysis tasks
SYSTEM PROMPT: [ANALYSIS TASK] You are an analytical expert. Follow this strategy: GROUNDING: - Always cite specific evidence before making claims - Confidence levels: CERTAIN / LIKELY / SPECULATIVE — always label which - If you don't know something, say so explicitly STRUCTURE: - Lead with the conclusion, then the evidence - One claim per paragraph - Maximum 3 levels of nesting QUALITY CHECKS before responding: - [ ] Every claim has evidence? - [ ] Confidence levels labeled? - [ ] Would an expert in this field agree with this framing? - [ ] Am I answering the actual question or a related easier one?
For creative/writing tasks
SYSTEM PROMPT: [WRITING TASK] Writing strategy for this task: VOICE: [Describe the tone, style, what to avoid] STRUCTURE: [Describe the expected output format] QUALITY STANDARD: A response is good when [describe what success looks like]. A response is bad when [describe common failure modes]. EXAMPLE OF GOOD OUTPUT: [Paste one example] EXAMPLE OF BAD OUTPUT (and why): [Paste one example with annotation]
Prompt Version Control
Track your system prompt iterations like code:
markdown# [PROMPT NAME] — Version History ## v3 (current) — [DATE] Change: Added explicit "verification phase" checklist Reason: v2 was skipping edge case checking Result: Failure rate dropped from ~30% to ~5% ## v2 — [DATE] Change: Added worked examples section Reason: v1 was too abstract; model wasn't following the strategy Result: Moderate improvement ## v1 — [DATE] Initial version: [PASTE]
The Meta-Prompt (write prompts with an LLM)
Help me write a system prompt for this agent. Agent task: [WHAT IT SHOULD DO] I'll be using this with: [CLAUDE / GPT-4 / etc.] Critical behavior: [WHAT MUST ALWAYS HAPPEN] Failure modes to prevent: [WHAT GOES WRONG WITHOUT GOOD PROMPTING] Apply the three-layer system prompt learning framework: 1. Exposition (what the model needs to know) 2. Worked examples (demonstrate correct behavior) 3. Strategy rules (explicit IF/THEN/BECAUSE) Then: suggest 3 variations I could test to find the best version.
Workflow
属于工作流：反偏见决策（第3步/终点）
| 位置 | 上游 | 下游 |
|---|---|---|
| 第3步（沉淀） | karpathy-understanding-first（验证后） | 沉淀完成，可复用 |
完整链路：llm-simulator → understanding-first → system-prompt-learning
也在日常开发中独立使用——任何时候 Agent 反复犯同一类错，都应该触发本 Skill。
Prompt Contract
textExtract a system prompt lesson from this failure/pattern: <DESCRIBE_THE_RECURRING_ERROR>. Produce: 1) Trigger condition — when does this error occur, 2) Correct strategy — step-by-step what the agent should do instead, 3) Anti-patterns — what specifically to avoid, 4) Worked example — a before/after showing the improvement, 5) Concise instruction block (< 200 words) ready to paste into system prompt or SKILL.md.
Verification Checklist
- 触发条件描述具体（不是「有时候」）
- 策略是 step-by-step 的（不是模糊建议）
- 反模式列出了具体的错误做法
- 有 before/after 对比示例
- 指令块 < 200 words，可直接粘贴
- 在新的测试 case 上验证过指令块有效
