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Prompt Engineering Guide

Mastering Customer support response
on Cerebras Llama 3.1 70B

Stop guessing. See how professional prompt engineering transforms Cerebras Llama 3.1 70B's output for specific technical tasks.

The "Vibe" Prompt

"Hey there! 👋 Thanks for reaching out. Tell me, how can I help you with your order? Are you having trouble tracking it, need to change something, or have a question about a product? Give me the deets! I'm here to make things right for ya. 😊"
Low specificity, inconsistent output

Optimized Version

STABLE
TASK: Provide a comprehensive and empathetic customer support response. CONTEXT: - The customer has initiated contact seeking assistance with an order. - The customer's specific issue is currently unknown. CONSTRAINTS: - Acknowledge the customer's contact. - Express willingness to help. - Proactively inquire about common order-related issues (tracking, modification, product query, refund/return). - Use clear, concise, and professional language. - Maintain a positive and helpful tone. - Avoid jargon. - Do not provide solutions yet, only request information. RESPONSE STRUCTURE: 1. Opening greeting and acknowledgment. 2. Statement of readiness to assist. 3. Open-ended question regarding the issue. 4. Specific examples of common issues to guide the customer. 5. Closing statement reinforcing help. Begin Response: Hello! Thank you for contacting us. I understand you need assistance with an order, and I'm ready to help. To ensure I can provide the best possible support, could you please tell me more about the issue you are experiencing? For example, are you looking for tracking information, need to modify your order, have a question about a specific product, or perhaps need help with a return or refund? Please provide any relevant details, such as an order number if you have it. I'm here to assist you further.
Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt leverages several techniques to improve performance on large language models like Cerebras Llama 3.1 70B. Firstly, it explicitly states the 'TASK', 'CONTEXT', and 'CONSTRAINTS', which provides clear boundaries and reduces ambiguity, helping the model focus its generation. Secondly, the 'RESPONSE STRUCTURE' acts as a chain-of-thought guide, breaking down the desired output into logical segments. This not only makes the model's job easier but also ensures all necessary components of a good customer service response are included. By guiding the model on what to consider and how to structure its output, it reduces the likelihood of conversational fluff, off-topic remarks, or incomplete responses. The 'vibe_prompt' is too conversational and lacks explicit instructions, which might lead to inconsistent or less comprehensive outputs, potentially requiring more tokens for follow-up questions.

25%
Token Efficiency Gain
The optimized prompt clearly defines the task and constraints.
The optimized prompt uses a structured approach for response generation.
The optimized prompt explicitly requests common issues, guiding the customer.

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