Summary
Stephanie Nyarko breaks down 30 AI terms in plain English, framed around a real-world scenario: a consultant quoted $11,000 for a proposal containing phrases like “RAG pipeline with MCP integrations and human-in-the-loop guardrails, fine-tuned on your business data” — and the client signed without understanding a word of it. Nyarko’s goal is to close the vocabulary gap that allows AI agencies to obscure pricing and scope from non-technical buyers.
The video is organized into thematic clusters: foundational terms (AI, LLMs, model versus app), retrieval and knowledge systems (RAG, embeddings, vector databases), customization approaches (fine-tuning versus prompt engineering, with explicit warnings that fine-tuning is rarely necessary for small businesses), agent and automation concepts (MCP, human-in-the-loop, agentic systems), and multimodal capabilities. For each term, Nyarko delivers a one-sentence verdict — ignore it, worth knowing, or you need this now — oriented specifically toward service business owners making procurement decisions rather than developers building systems.
Notable moments include a clear explanation of why “trained on your data” almost never means actual model training (and what fine-tuning actually costs and when it makes sense), a breakdown of the model-versus-app distinction using ChatGPT, Claude, and Gemini as examples, and practical guidance on what follow-up questions to ask vendors who lead with jargon. The video serves as a useful primer for anyone entering AI vendor conversations without a technical background.
📺 Source: Stephanie Nyarko · Published August 12, 2026
🏷️ Format: Course Lesson
