RAG vs LLM Explained in 60 Seconds System Design Interview MUST KNOW
About this lesson
๐ RAG vs LLM โ one of the most asked questions in AI system design interviews. In this short, we break down: โข What happens when you connect RAG (Retrieval-Augmented Generation) with LLMs โข Why combining them seems powerful but can create conflicts โข Real-world example of PDF-based RAG vs internet-powered LLM โข How output inconsistency and hallucination happens โข The correct way to design efficient AI systems using RAG ๐ก Key Insight: RAG works on controlled, limited data (like PDFs, company docs, internal knowledge), while LLMs can pull generalized or external knowledge. When combined improperly, this leads to conflicting outputs and unreliable results. โ ๏ธ This is exactly what interviewers test in AI/ML system design rounds. ๐ Use Cases Covered: * Chatbots built on private data * AI assistants for companies * Knowledge-based systems * Interview prep for GenAI roles ๐ If youโre preparing for: โข AI Engineer roles โข ML System Design Interviews โข GenAI Product Development ๐ This concept is MUST KNOW. โ ๐ฌ Comment: โRAGโ and Iโll share a full system design roadmap ๐ Subscribe for more AI system design & GenAI breakdowns
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