Engineer builds dependency-ordered LLM glossary for non-ML technical readers

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A software engineer with a background in sysadmin and networking has published a glossary of large language model terminology structured in dependency order rather than alphabetically. The guide covers concepts from tokens and embeddings through to attention, KV cache, grouped query attention, mixture of experts, and quantization. Each entry is written so that it relies only on terms already defined earlier, avoiding the back-and-forth navigation common in alphabetical references. The author acknowledges the glossary was built through iterative questions posed to an LLM rather than prior expertise, and is intended as a personal reference notebook made public. Analogies are drawn from caches, control loops, and network engineering to make concepts accessible without requiring a machine learning background.

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