AI Terminology 101

Every AI conversation is full of words that sound familiar but rarely get explained: parameters, tokens, fine-tuning, RAG, agents, hallucination, alignment. AI Terminology 101 is the plain-English handbook that finally puts them in order. Instead of an alphabetical glossary, the book follows the life cycle of a real AI system - from first principles and how models learn, through prompting, retrieval, agents, evaluation, safety, and production - so each term builds on the last. Every entry is marked with a simple difficulty rating, so beginners can stay at the surface while engineers can dig into the technical detail boxes for formulas and mechanics. Written by Mohammad Mosafer and Shiva Bahri, this handbook covers both the foundations (transformers, gradient descent, embeddings) and the terms shaping AI right now: agent-to-agent protocols, GRPO, tool use, and RAG pipelines. It closes with practical reference material: an algorithm compendium, a production stack map, a build checklist, and a full A-to-Z quick reference. Whether you're a product manager sitting through your first AI roadmap meeting, a student starting out, or an engineer who wants the vocabulary straight - this is the book that gets you fluent, fast.