Hari Prasad Renganathan’s Post

I spent the last 887 days learning AI. Every single day. Yesterday, I stood in front of a room full of people at the NYC Women in Machine Learning & Data Science event and taught RAG & Agentic AI. Here’s the real takeaway: You can explain these concepts to anyone using just 3 simple steps. 🔑 Step 1: Embeddings -- Turn text into numbers so machines can understand the meaning. -- Think of it as giving AI “x-ray vision” into language. 🔑 Step 2: Vector Databases -- This is where those embeddings live. -- It’s like giving AI a memory that you can search instantly. 🔑 Step 3: Agents -- Instead of a single response, agents let AI take multiple steps: reasoning, deciding, and looping until it gets the job done. That’s it. Not 50 tools. Not years of prep. With these 3 building blocks, you can: -- Summarize research papers, -- Build your own chatbot, -- Or automate workflows at work. The lesson? AI only feels complicated until you break it into its core blocks. 📌 Save this post for later if you’re learning AI. 🔁 Reshare to help your network. 👇 Comment "AI" if you’d like the slides/resources from my session.