Mastering Meeting notes extraction
on GPT-4o-mini
Stop guessing. See how professional prompt engineering transforms GPT-4o-mini's output for specific technical tasks.
The "Vibe" Prompt
Optimized Version
Engineering Rationale
The optimized prompt leverages several best practices for LLM prompting: 1. **Role Assignment**: 'You are an expert...' sets the context and expectation for the model's persona, enhancing focus. 2. **Chain-of-Thought (CoT)**: The explicit step-by-step instructions (Read and Understand, Identify Topics, Extract Decisions, etc.) guide the model through the reasoning process, reducing errors and improving accuracy. This breaks down a complex task into manageable sub-tasks. 3. **Specific Definitions**: Clearly defining 'Decisions' and 'Action Items' helps the model distinguish between similar concepts and extract targeted information. 4. **Output Structure Enforcement**: Providing a detailed output structure with markdown elements ensures consistent, parseable, and human-readable results. This reduces the need for post-processing. 5. **Explicitness**: The prompt is highly explicit about what information to extract and how to present it, minimizing ambiguity. 6. **Reduced Ambiguity**: The naive prompt's 'key points' is vague; the optimized version breaks it down into 'Decisions', 'Action Items', and 'Key Discussion Points' with clearer guidelines for each.
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