Where RAG Fails (And How to Fix It)A Practical Guide for GenAI Developers (with Simple Examples) RAG (Retrieval-Augmented Generation) sounds powerful: “Give the model your data, and it will answer correctly.” But in real projects… RAG often fails 😅Not because the idea is wrong, but...Dec 14, 2025·4 min read
System prompts, prompt formats, and prompting styles — explained simplyOpening — why prompts matter Large language models (LLMs) don’t “know” your intent unless you tell them. The prompt is your instruction to the model. If the prompt is unclear or wrong, the model’s answer will be poor — that’s Garbage In, Garbage Out ...Aug 15, 2025·4 min read
Vector Embeddings: Turning Data into Meaningful NumbersThink of this post as “Google Maps for meaning”: we’ll put words and ideas on a map, then show how Transformers (the tech behind ChatGPT) use that map to understand context and answer smartly. Quick Primer: Tokens & Tokenization Before anything enter...Aug 15, 2025·4 min read
From Words to Numbers: Understanding Tokenization in AIWhat is Tokenization? Whenever you type or ask something — For example: “Hey, how are you?” An AI model first breaks that text into smaller pieces.These small pieces are called tokens. A token can be: a letter a word a number a special charact...Aug 15, 2025·2 min read
Explained: The Real Meaning of GPT and How It WorksHow AI gives you Answer When you ask something from AI, it looks like the AI is “thinking” for a moment. But in reality, the AI is not actually thinking like humans do — it’s generating something and then giving you an answer or reply. Every time, ...Aug 14, 2025·3 min read
