Defines Artificial Intelligence as software that learns patterns from data to make decisions or generate output. Covers its core subfields (ML, deep learning, NLP, generative AI), how a system runs end to end, the capability spectrum, the layered stack, the human role, and where AI still fails.

Midjourney v6 leans photorealistic; Niji v6 is tuned for anime and illustration. Here is how they differ, how to prompt each, and when to switch.

A guide to AI agent evaluation — the core capabilities, from distributed tracing to performance metrics, needed to build reliable agentic systems.

The principles for designing tools an agent can actually use well: clarity, specificity, strong typing, clean outputs, and errors that enable self-correction.

The metrics and methods for judging AI models — classification and regression metrics, robustness and efficiency, evaluation methodologies, and how generative systems differ.