If you’ve ever been in a meeting where someone casually said “we just need to add RAG,” and you nodded while secretly searching what that meant under the table, this post is for you. The AI space moves so fast that even experienced developers can suddenly feel surrounded by unfamiliar buzzwords overnight. Terms like temperature, tokens, context window, embeddings, fine-tuning, and RAG get thrown around constantly, often without much explanation. This post is meant to build that foundation. I’ll walk through the core concepts and definitions you need to understand modern AI development. Don’t just skim the terms — try to understand the idea behind each one. Treat this post as a reference you can revisit from time to time, so the next time your company or team discusses a new AI strategy, you’ll understand what’s actually being talked about. You Are Not Behind. But You Do Need to Learn Some New Words. I have been writing code for a long time. Long enough to remember when JSON format was the future, when microservices were going to solve everything, when containers were the thing everyone had to learn or get left behind. Every few years something arrives that feels like…
