The demo was flawless. The architecture looked clean on the whiteboard. Then a real user typed a real question, and everything I thought I…Continue reading on Medium »
No embeddings. No vector databases. Just an LLM reading a smart map of your document. Here’s exactly how.I published a piece last week about why I stopped using vector databases for document RAG.A lot of you asked the same question in the comments: “Ok…
Everyone’s racing to ship AI. Almost no one’s asking the right question.Continue reading on Medium »
From confused hallucinations to accurate answers in one week. The complete guide to building smarter AI — no code requiredAGENTIC RAGIt was demo day. Fifty people in the room. My manager nodding at me from the back row.I typed the question live: “What’…
RAG retrieves text well, but breaks when AI must connect relationships, context, and deeper logic.Continue reading on Towards AI »
Learn how to build a powerful agentic RAG systemContinue reading on Towards AI »
The mechanism behind correct retrieval producing wrong answers — no pipeline diagrams, just what happens inside the model.Continue reading on Towards AI »
If you work in tech and you’re still treating “RAG” as an engineer’s problem, you’re about to get left behind. Here’s why quickly.Continue reading on Medium »
Goal: “I want to host a birthday sale for top customers.”Continue reading on Medium »
RAG is a distributed system . It becomes clear when moving beyond demos into production.It consists of independent services such as ingestion, retrieval, inference, orchestration, and observability. Each component introduces its own latency, scaling ch…