AI APPLICATION ARCHITECTURE

🧠 Most AI engineers memorize tools. The best engineers understand the architecture. Every AI application—whether it’s ChatGPT, Cursor, Claude Code, or your own agent—follows the same fundamental building blocks. This tree gives you the mental model: 🌐 Frontend → where users interact 🤖 Agent Orchestration → plans and coordinates the workflow 📚 Knowledge (RAG) → retrieves relevant context when needed 🧠 LLMs → reason, generate, and make decisions 🔧 MCP Tools → connect to GitHub, Slack, APIs, databases, browsers, and more 💾 Data Layer → stores application and vector data 📊 Observability & Evals → measure quality, latency, cost, and hallucinations 🚀 Deployment → ship your AI application to production Don’t think in frameworks. Think in systems. Once you understand these layers, learning any new AI framework becomes much easier. 📌 Save this for your next AI project. 💬 Which layer are you spending the most time learning right now? ⸻ #AI #AIEngineering #GenerativeAI #LLM #RAG