@hackproduct9: RAG isn’t one pattern—and choosing the wrong one can add cost without improving answers. Think of retrieval like asking for help: sometimes one search is enough; sometimes you need memory, multiple queries, verification, tools, images, or a knowledge graph. This reel maps 10 RAG architectures: Simple → fast document Q&A Memory → multi-turn support Multi-query → ambiguous questions HyDE → weak keyword matches Adaptive → mixed query complexity Corrective → high-stakes answers Self-RAG → factual long-form Agentic → multi-step work Multimodal → visual documents Graph RAG → connected data When reviewing an AI-built RAG system, check whether the retrieval strategy matches the failure mode—not just whether a vector database exists. Save the grid. Which RAG pattern are you using? #RetrievalAugmentedGeneration #AIEngineering #GenerativeAI #LLM #HackProduct

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Tuesday 28 July 2026 01:20:45 GMT