Every Candidate Knows RAG. Almost None Can Explain Why It Works

The specific interview questions ("Why do embeddings work?", "What happens before the first token?"), the named concept list (transformers, tokenization, vector search, etc.), and the sharp observation about frameworks-vs-fundamentals are concrete and useful — this is genuinely good technical content.

 The repetitive short-line formatting ("The room usually goes quiet." / "That's why...") is stylistic padding common in LinkedIn "storytelling" posts, and the ending — the course pitch, "Repost if this helped," "Follow for more real-world breakdowns" — is pure engagement/sales scaffolding that doesn't add to the technical substance.