#llm

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How Large Language Models Actually Work, Explained Without the Hype

A language model does not look things up, and it does not think in sentences. It predicts one token at a time. Understanding that single fact explains almost everything these systems do well and badly.

Aug 6, 20268 min readAI & Data Science

Nathan Brooks

Prompt Engineering That Works: Practical Patterns for Reliable AI Output

Most disappointing AI output comes from underspecified prompts, not weak models. Here are the patterns that reliably turn vague requests into consistent, usable results.

Aug 3, 20266 min readAI & Data Science

Nathan Brooks

Retrieval-Augmented Generation Explained: Giving AI Access to Your Own Data

RAG is the standard way to make a general-purpose model answer questions about your own documents. Here is how the pieces fit together, and the retrieval problems that decide whether it works.

Jul 31, 20266 min readAI & Data Science

Posts tagged #llm

How Large Language Models Actually Work, Explained Without the Hype

Prompt Engineering That Works: Practical Patterns for Reliable AI Output

Retrieval-Augmented Generation Explained: Giving AI Access to Your Own Data