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RAG Pipeline Design
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: AI-Powered Publisher Chatbot with Ad Monetization
Format
Text-first
Lines
1
Sections
1
Linked challenge
AI-Powered Publisher Chatbot with Ad Monetization
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Design the RAG pipeline that your Content Researcher agent will leverage. Detail the complete process from ingesting publisher content (e.g., Markdown, HTML articles) into a chosen vector database to retrieving the most relevant chunks based on a given user query. Explain how embedding models will be selected and managed for optimal retrieval.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.
Tune next
Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.
Verify after
Check whether the prompt asks for the right evidence, confidence signal, and escalation path.