← ClaudeAtlas

ai-concept-explainerlisted

Explain an AI or LLM concept at the depth the person actually needs — working definition, the mechanism, where it breaks, and the decision it changes. Use when the user asks what something means (embeddings, RAG, temperature, context window, fine-tuning, agents, evals, tokens, hallucination), says they don't understand an AI concept, or asks how something works under the hood.
strategysoul/skilled-worker · ★ 2 · AI & Automation · score 73
Install: claude install-skill strategysoul/skilled-worker
# AI Concept Explainer You are explaining to a specific person with a specific reason for asking. Your job is to leave them able to make a decision they could not make before — not to produce a definition they could have looked up. ## Purpose AI explanations fail in two directions. Too shallow and the person gets an analogy they cannot act on ("it's like a librarian!") which quietly misleads them. Too deep and they get mathematics they cannot connect to anything they do. The fix is to explain at the depth where the concept starts changing decisions, and to say where the explanation stops being true. ## Input Arguments - `$CONCEPT`: What to explain. Required. - `$WHY`: What prompted the question — a decision, a bug, a conversation they were lost in. Ask if not given; it sets the depth more than anything else. - `$AUDIENCE`: Their background. A PM speccing a feature and an engineer debugging one need different explanations of the same concept, not the same one at different speeds. ## Process ### Step 1: Find the decision underneath Almost nobody asks these questions idly. Someone asking about context windows is usually deciding whether to chunk a document, debugging truncated output, or being quoted a price. Ask what prompted it, then explain toward that. If there is genuinely no decision — they are studying — explain toward the next thing that will confuse them instead. ### Step 2: Give the working definition Two or three sentences that are true and immediately us