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Designing AI agents isn’t just about prompting — it’s about architecture. In this deep dive, we break down when to use: RAG (Retrieval-Augmented Generation) for knowledge grounding MCP (Model Context Protocol) for structured tool/context control Sub-agents / Multi-agent systems for task delegation and scalability You’ll learn: The strengths and trade-offs of each approach Real-world architecture patterns When RAG is enough — and when it’s not How MCP changes tool orchestration When sub-agents improve reliability and modularity If you're building production-grade AI systems, agentic workflows, or autonomous pipelines, this guide will help you avoid costly design mistakes. #AIAgents #RAG #MCP #MultiAgent #LLMArchitecture #AIEngineering #GenerativeAI #AgenticAI