Introduction: Breaking Down the Server-Side Barriers Picture this: You're a JavaScript developer who's mastered frontend development. You know React, you can handle complex DOM manipulations, and you've built stunning user interfaces. But suddenly, y...
What are Loops? Loops are one of the most important concepts in python. Loops allows us to write the same block of code multiple times without rewriting it again and again. There are 2 types of loops in python for loop and While loop. Mastering loops...
The RAG revolution started with a simple promise: ground your AI in external knowledge to reduce hallucinations and deliver accurate, up-to-date responses. Yet, as teams rushed to implement basic RAG systems, they quickly discovered that naive retrie...
Retrieval-Augmented Generation (RAG) promised to revolutionize how AI systems work—combining the power of large language models with real-time access to external knowledge. It was supposed to solve the hallucination problem, deliver accurate answers,...
When you interact with AI models like ChatGPT, the quality of answers depends heavily on how you ask your question. This process is called prompting, and one of the most powerful tools in prompting is the system prompt. In this article, we’ll explore...
Retrieval-Augmented Generation (RAG) is one of the most exciting approaches in AI today. It allows large language models (LLMs) to access external knowledge by retrieving relevant documents and then generating answers grounded in that information. Bu...
Imagine you and I are in the kitchen. You ask me: "Beta, what is this ‘vector embeddings’ thing you keep talking about in AI?" So let me explain it in the simplest way possible — no math, no heavy jargon. Just like I’d explain it over a cup of chai. ...
Retrieval-Augmented Generation (RAG) has quickly become one of the most popular techniques for building powerful AI applications. At its core, RAG combines a retriever (to fetch relevant information) and a generator (usually an LLM) to give better, f...
Artificial Intelligence (AI) has come a long way. At first, AI models could only answer questions. Then they learned to chat like humans. Now, the next big leap is here: Agentic AI. But what does “agentic” mean? And what exactly are AI agents? Let’s ...
You've built your first Retrieval-Augmented Generation (RAG) system. It connects your Large Language Model (LLM) to a private knowledge base, and it feels like magic. But then, you start noticing problems. It misses obvious answers, gives irrelevant ...
