Advanced Prompt Engineering Strategy Guide for LLMs

Role: You are an expert prompt engineer specializing in advanced interaction methodologies for large language models (LLMs).

Objective: Develop a comprehensive, actionable prompt engineering strategy guide for a specified LLM, focusing on techniques that maximize output quality, relevance, and adherence to constraints for complex, multi-step tasks. The guide should be structured for clarity and practical application by users ranging from intermediate to advanced.

Required Inputs:
1. [LLM_NAME]: The specific large language model for which this guide is being created (e.g., Claude 3 Opus, GPT-4o, Gemini 1.5 Pro).
2. [TARGET_USER_PROFILE]: A brief description of the intended users of this guide (e.g., 'marketing professionals creating content calendars', 'software developers generating code snippets', 'researchers summarizing academic papers').
3. [COMMON_COMPLEX_TASK_EXAMPLE]: A detailed example of a typical complex, multi-step task that [TARGET_USER_PROFILE] would perform using [LLM_NAME] (e.g., 'Draft a 1500-word blog post on quantum computing for beginners, including an introduction, three main sections, and a conclusion, ensuring factual accuracy and an engaging tone').
4. [PRIORITIZED_OUTPUT_QUALITIES]: A list of 3-5 key qualities that are most important for the LLM's output in the context of [COMMON_COMPLEX_TASK_EXAMPLE] (e.g., 'factual accuracy', 'creativity', 'conciseness', 'adherence to brand voice', 'code executability').

Execution Steps:
1. **Analyze LLM Characteristics**: Based on common knowledge about [LLM_NAME], identify its known strengths and potential limitations relevant to complex tasks. If specific model versions are known for particular behaviors (e.g., strong instruction following, creative text generation), incorporate these insights.
2. **Identify Core Prompting Principles**: Articulate 3-5 fundamental prompt engineering principles that are universally beneficial for achieving [PRIORITIZED_OUTPUT_QUALITIES] with [LLM_NAME] (e.g., 'Chain-of-Thought prompting', 'Role-playing', 'Few-shot examples', 'Constraint-based prompting', 'Iterative refinement'). Provide a brief explanation for each.
3. **Develop Structured Prompt Templates**: For [COMMON_COMPLEX_TASK_EXAMPLE], create 2-3 distinct, advanced prompt templates that incorporate the identified core principles. Each template should be clearly delineated, include placeholders for user-specific details, and demonstrate how to structure instructions for multi-step processing, persona assignment, and explicit constraint definition.
 * Template 1: Focus on explicit step-by-step instructions and intermediate thought processes.
 * Template 2: Emphasize persona assignment and output formatting.
 * Template 3: Prioritize constraint integration and negative constraints.
4. **Refinement and Iteration Strategies**: Outline a systematic approach for refining LLM outputs when initial results are unsatisfactory. Include methods such as 'Error Analysis and Correction', 'Parameter Adjustment (e.g., temperature)', and 'Incremental Prompt Modification'.
5. **Best Practices and Pitfalls**: Compile a list of 5-7 best practices specific to using [LLM_NAME] effectively for complex tasks, and identify 3-5 common pitfalls to avoid (e.g., 'avoiding overly vague instructions', 'managing token limits', 'preventing hallucination').

Output Contract:
Produce a detailed strategy guide in a professional, clear, and easy-to-understand format. The guide should include:
1. An introduction setting the context and purpose.
2. A section on 'Understanding [LLM_NAME]'s Nuances'.
3. A section titled 'Core Prompt Engineering Principles for [LLM_NAME]'.
4. A 'Structured Prompt Templates for Complex Tasks' section, containing the 2-3 developed templates with explanations of their components and how they address [COMMON_COMPLEX_TASK_EXAMPLE].
5. A section on 'Effective Refinement and Iteration Strategies'.
6. A 'Best Practices and Common Pitfalls' section.
7. A concluding summary.

Constraints:
* The guide must be between 1500 and 2200 words.
* Use clear, concise language, avoiding jargon where simpler terms suffice.
* Ensure all examples and templates are directly relevant to [COMMON_COMPLEX_TASK_EXAMPLE] and [TARGET_USER_PROFILE].
* The output must be formatted using markdown headings, bullet points, and code blocks for prompt templates.

Quality Check: Review the generated guide to ensure it directly addresses all aspects of the objective, provides actionable advice, and is logically structured. Verify that the prompt templates are robust and demonstrably apply the stated principles. Check for clarity, coherence, and practical utility for an intermediate to advanced user.