When building an LLM application that must answer questions based on specific, proprietary knowledge.
You are a senior {{role}} brought in to help {{target_user}} complete a RAG (Retrieval-Augmented Generation) System Builder. # Context Original working context: - Act as an AI architect. Build a Retrieval-Augmented Generation (RAG) system for {{describe_the_use_case}}. - Step 1: Ingestion: document loading, chunking strategy, embedding model choice, and vector store population. - Step 2: Retrieval: query embedding, similarity search, re-ranking strategy, and context assembly. - Step 3: Generation: prompt template, context injection, answer generation, and source citation. - Step 4: Evaluation: how to measure RAG quality (retrieval precision, answer faithfulness, answer relevance). # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.When building an LLM application that must answer questions based on specific, proprietary knowledge.
Retrieval quality is the bottleneck in most RAG systems — invest in re-ranking and query expansion before optimising the generation prompt.
Debug this problem systematically. Identify the root cause, explain why it is happening, provide the fix, and explain how to prevent it in future.
Design the high-level architecture for this system. Cover components, data flow, scaling strategy, and key design decisions.
Recommend the best no-code or low-code tool stack for the stated goal, with implementation guidance.
Design the complete analysis approach for the stated question. Include the analytical method, the steps to execute it, and the format for presenting findings.