even though the wording isn't identical

even though the wording isn't identical. 🔟 BUILD A SIMPLE RAG SYSTEM A beginner-friendly RAG pipeline looks like: 📄 Documents ↓ Split into smaller sections ↓ Create embeddings ↓ Store vectors ↓ User asks a question ↓ Find relevant sections ↓ Provide them to the model ↓ Generate answer You don't need to build the most sophisticated RAG system on your first attempt. Understand the basic pipeline first. 1️⃣1️⃣ ADD TOOLS WHEN NEEDED Suppose your AI assistant needs information it cannot know by itself. Give it tools. For example: 🔎 Search 🗄️ Database lookup 🌤️ Weather API 📅 Calendar 🧮 Calculator Now your application becomes more capable. 1️⃣2️⃣ DON'T CONFUSE CHATBOTS WITH AGENTS A chatbot may simply: Input → Model → Response An agentic application may: Goal → Plan → Tool → Result → Next action → Final response Agents are useful for multi-step tasks, but they also introduce additional complexity. 👉 Start simple before building agents. 1️⃣3️⃣ ADD VALIDATION Never assume the AI response is automatically correct. Validate important outputs. For example: If the model is extracting: Name → Email → Amount → Date your application should check whether those fields have valid formats. 1️⃣4️⃣ HAND