Before jumping into APIs, RAG, agents, and AI applications, I wanted to understand what actually happens inside an LLM. I kept coming across terms like neural networks, deep learning, Transformers, attention, tokens, embeddings, BERT, GPT, and causal language modeling — but they all felt like disconnected pieces. I could understand each concept individually, but I didn't have a clear picture of how they all connected. So I decided to step back and build the mental model from the groun...