# LLM Prompting Reference ## Prompt Architecture ### System Prompt Structure ``` You are [ROLE] with expertise in [DOMAIN]. ## Context [Background, constraints, tone] ## Instructions [Step-by-step task breakdown] ## Output Format [Exact structure with example] ## Constraints - [Hard limits] - [Guardrails] ``` ### User Prompt Structure ```xml [Background information] [Specific action required] [Output structure] [Additional limits] ``` ## Reasoning Techniques ### Chain of Thought (CoT) | Variant | Trigger | Best For | |---------|---------|----------| | Zero-shot | "Think step by step" | Quick reasoning tasks | | Few-shot | 2-3 reasoning examples | Complex multi-step | | Auto-CoT | "Let's approach systematically" | General reasoning | ### Tree of Thoughts (ToT) ``` Explore 3 approaches to [problem]: For each: 1) Method 2) Pros/cons 3) Success probability Evaluate branches, select best path. ``` ### Self-Consistency Run same prompt 3-5x with temp=0.7, take majority answer. Best for: math, logic, factual. ### ReAct Pattern ``` Thought: [Current reasoning] Action: [Tool/step to take] Observation: [Result] ...repeat... Final Answer: [Conclusion] ``` ### Least-to-Most ``` Break [complex task] into subproblems. Solve easiest first, build up. ``` ## Instruction Optimization ### Self-Refine Pattern ``` 1. Generate initial response 2. Critique: "What's wrong with this?" 3. Refine: "Fix identified issues" 4. Repeat until satisfactory ``` ### Role Optimization - **Expert persona**: "As a senior [role] with 20 years..." - **Constraint persona**: "You only respond with..." - **Teaching persona**: "Explain as if to a..." ### Task Decomposition ``` 1. [First step - output X] 2. [Second step - using X, output Y] 3. [Final step - using Y, output Z] ``` ## Output Control ### JSON Enforcement ``` Respond in valid JSON only: {"field": "type", "required": true} No markdown, no explanation, just JSON. ``` ### Length Control | Goal | Phrase | |------|--------| | Brief | "In 2-3 sentences" | | Detailed | "Comprehensive analysis in 500 words" | | Structured | "5 bullet points, max 20 words each" | ### Hallucination Reduction - "Only use information from provided context" - "If unsure, say 'I don't know'" - "Cite sources for each claim" - "Confidence: high/medium/low for each point" ## Model-Specific Tips ### Codex - XML tags: ``, ``, `` - Extended thinking: "Think deeply before responding" - Prefill: Start assistant response to guide format ### GPT-4 - JSON mode: `response_format: {"type": "json_object"}` - Function calling for structured output - System message for persistent instructions ### Gemini - Multimodal: Image + text in same prompt - Grounding: Enable Google Search for facts - Safety settings: Adjust thresholds ## Context Engineering ### RAG Prompt Pattern ``` [Document chunks with sources] Answer based ONLY on context above. If not in context, say "Not found in documents." ``` ### Window Optimization - Front-load critical info (primacy effect) - Repeat key constraints at end (recency effect) - Chunk long documents with summaries ## Few-Shot Examples ### Structure ``` Example 1: Input: [representative input] Output: [ideal output] Example 2: Input: [edge case] Output: [handling] Now apply to: Input: [actual task] ``` ### Selection Criteria - Diverse examples > similar examples - Include edge cases - Match complexity of target task - 2-5 examples optimal (diminishing returns beyond)

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