30 AI Engineering Terms Explained (in Plain English)
🤝 Your team not maximizing Claude? I run 1:1 and team AI workshops for companies doing $10M+ per year: https://aibuilder.academy/yt/rTkm1eY0ezU 📄 Get the (free) 100 AI Terms Guide: https://100aiterms.com/ Here I review the most common AI buzzwords used these days and explain them in simple terms. Intro - 0:00 1) Large Language Model (LLM) - 0:08 2) Prompt - 0:42 3) Prompt Engineering- 1:13 4) Context Window - 2:04 5) Context Engineering - 3:25 6) Token - 3:59 7) Inference - 5:30 8) Parameter - 6:00 9) Prompt Injection - 6:52 10) Guardrails - 8:00 11) Hallucination - 8:45 12) Evals - 9:10 13) RAG - 10:11 14) Semantic Search - 10:42 15) Embedding - 12:03 16) Chunk - 13:10 17) Vector Database - 14:33 18) AI Agent - 15:01 19) Agentic AI - 15:18 20) Agentic RAG - 16:13 21) Model Context Protocol (MCP) - 16:47 22) Agent2Agent (A2A) - 18:11 23) Multi-agent System - 18:47 24) Multimodal AI - 19:36 25) Reasoning Models - 20:10 26) Fine-tuning - 20:43 27) Distillation - 21:45 28) Foundation Model - 22:04 29) Train-time Compute - 22:33 30) Train-time Compute - 22:58
