Anatomy of a Prompt — System, User, and Assistant Explained
Understand how system, user and assistant messages shape LLM behavior.
Feb 15, 20268 min read4

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Articles tagged with #machine-learning
Understand how system, user and assistant messages shape LLM behavior.

Learn what embeddings are, how vector similarity works, and why understanding magnitude vs direction matters for semantic search and RAG systems.

Learn how Byte Pair Encoding (BPE) actually works — the algorithm that powers GPT, Claude, and LLaMA tokenizers. Step-by-step with examples.

Learn what tokens really are, why they're not words, and how understanding tokenization saves you money on LLM API costs.
