Interview-prep guides, taught for transfer

Company-agnostic guides for data science, ML engineering, and AI engineering — organized by what interviews actually test and the documented reasons strong candidates fail, taught for transfer to the novel problems real interviews throw at you, not memorization. Each guide ships a hand-built companion library you assemble chapter-by-chapter and static, client-side interactive demos (no model, no server).

Guides

1. AI engineering — the AI-native dimensions of building on language models. Three complete guides: Evaluation & benchmarking, LLM application engineering, and Production AI systems — 13 chapters each, with a hand-built companion (mini_eval, mini_rag, mini_agent, mini_prod) and interactive ICAP demos.
2. Experimentation — causal inference and A/B testing for product decisions. Planned.

How these are built: methodology · about & AI-collaboration disclosure · search · brandon-behring.dev.