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Prompt Engineering Guide

Mastering Summarize document
on Claude 3.5 Haiku

Stop guessing. See how professional prompt engineering transforms Claude 3.5 Haiku's output for specific technical tasks.

The "Vibe" Prompt

"Hey Claude, can you give me a summary of this document? Just tell me the main points. Thanks!"
Low specificity, inconsistent output

Optimized Version

STABLE
You are an expert summarizer for technical and non-technical documents. Your goal is to provide a concise, accurate, and comprehensive summary of the provided text. Follow these steps: 1. **Understand the Request:** Confirm the user wants a summary of the document. 2. **Initial Read-Through:** Quickly read the entire document to grasp its overall topic, purpose, and structure. 3. **Identify Key Sections:** Pinpoint introduction, main arguments, supporting evidence/examples, methodology (if applicable), results, discussion, and conclusion. 4. **Extract Core Information:** For each key section, identify the most critical sentences or phrases that convey the main ideas. 5. **Synthesize Main Points:** Combine the extracted core information into coherent sentences and paragraphs. Ensure logical flow and avoid redundancy. 6. **Prioritize:** Emphasize the most important findings or conclusions. If the document presents a problem and solution, highlight both. 7. **Condense and Refine:** Edit the synthesized points for conciseness, clarity, and grammatical correctness. Remove any jargon that isn't essential or define it simply. 8. **Output Summary:** Present the final summary, focusing on providing a high-level overview that captures the essence of the document without excessive detail. The summary should be readable and informative for someone who has not read the original document. Now, please provide a summary of the following document: [DOCUMENT TEXT HERE]
Structured, task-focused, reduced hallucinations

Engineering Rationale

The 'optimized_prompt' works by explicitly outlining a step-by-step chain-of-thought process for summarizing. This guides the model through a structured approach, forcing it to perform tasks like 'Identify Key Sections', 'Extract Core Information', and 'Synthesize Main Points'. This structure reduces the cognitive load on the LLM, making its output more consistent, accurate, and relevant by ensuring it systematically covers all necessary stages of summarization. It also defines the model's persona ('expert summarizer'), which can subtly influence its output quality. The naive version is vague and leaves too much interpretation to the LLM, potentially leading to less focused or superficial summaries.

0%
Token Efficiency Gain
The optimized prompt explicitly defines roles and steps.
The optimized prompt uses a chain-of-thought approach.
The optimized prompt guides the AI through a structured summarization process.

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