Model

Claude 3.5 Sonnet

Example input

[TECH_CONCEPT]: Retrieval-Augmented Generation (RAG) in AI
[TARGET_AUDIENCE]: Non-technical business owners
[VISUAL_THEME]: Clean futuristic corporate, deep navy blue and glowing cyan

Example output

{"infographic_copy":{"catchy_headline":"Unlock Your AI's Memory: The Power of RAG","simplified_definition":"RAG (Retrieval-Augmented Generation) supplies retrieved company content as context for an AI answer without retraining the model. Access control must be configured by the application.","core_pillars":[{"pillar_title":"1. The User Asks","short_description":"You ask a question about your specific company policies or private data."},{"pillar_title":"2. The System Retrieves","short_description":"The system retrieves relevant documents from an authorized knowledge source."},{"pillar_title":"3. The AI Generates","short_description":"The AI uses retrieved context to draft an answer that still needs evaluation."}],"mind_blowing_stat_or_fact":"Grounding answers in relevant documents can reduce unsupported claims. RAG does not guarantee accuracy or citations."},"midjourney_layout_prompt":"A clean, modern UI/UX vertical infographic template layout with deep navy blue background and glowing cyan accents. Futuristic corporate aesthetic, abstract floating data nodes and elegant connecting lines. Empty structured spaces and geometric panels for text placement. Modern data visualization layout, clean infographic template, vector illustration, flat 2D elements mixed with soft 3D gradients, highly detailed, 8k resolution, --v 6.0 --ar 9:16"}