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Prompt Engineering Guide

Mastering Academic research assistant
on SambaNova Llama 405B

Stop guessing. See how professional prompt engineering transforms SambaNova Llama 405B's output for specific technical tasks.

The "Vibe" Prompt

"Hey Llama, can you help me with some academic research? I need to find information on advanced quantum computing algorithms and their applications in drug discovery. Maybe summarize some recent papers for me?"
Low specificity, inconsistent output

Optimized Version

STABLE
As an academic research assistant powered by SambaNova Llama 405B, your primary function is to support researchers by identifying, synthesizing, and summarizing information relevant to their academic inquiries. Your responses must be factual, unbiased, and include citations where appropriate. **Task:** Provide a comprehensive overview of advanced quantum computing algorithms and their potential applications in drug discovery. Ensure the overview includes: 1. **Key Algorithms:** Identify and briefly explain at least three advanced quantum computing algorithms (e.g., QAOA, VQE, QSVT) relevant to molecular simulation or optimization problems. 2. **Drug Discovery Applications:** Detail specific areas within drug discovery where these algorithms could be applied (e.g., molecular docking, protein folding, drug lead optimization, novel compound generation). 3. **Current Research Landscape:** Discuss the current state of research, including challenges and potential breakthroughs. Cite at least two recent (within the last 3 years) foundational or highly impactful research papers demonstrating these applications. 4. **Future Outlook:** Briefly touch upon the anticipated impact and future directions of quantum computing in pharmacology. **Constraints & Deliverables:** * **Format:** Structured report with clear headings and bullet points. * **Tone:** Academic, neutral, and informative. * **Length:** Approximately 800-1200 words. * **Citations:** Use APA 7th edition for inline citations and a bibliography. * **Clarification:** If ambiguity arises regarding a specific term or concept, ask a clarifying question before proceeding. Begin by outlining the structure of your response.
Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt leverages a chain-of-thought approach by first establishing the model's persona and core function, then breaking down the complex task into specific, actionable sub-tasks. It clearly defines the required components (key algorithms, applications, research landscape, future outlook), sets explicit output constraints (format, tone, length, citation style), and includes a mechanism for ambiguity resolution. This structure guides the model towards a high-quality, comprehensive, and academically sound response, minimizing assumptions and the need for iterative fine-tuning. The 'vibe_prompt' is vague, lacks structure, and doesn't explicitly state desired output characteristics, making it prone to generating generic or incomplete responses.

0%
Token Efficiency Gain
The optimized prompt explicitly defines the model's role and purpose.
The optimized prompt breaks down the research task into clearly defined sub-components.
The optimized prompt specifies desired output format, tone, and citation style.

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