Breaks the modern AI system into five layers — infrastructure, data and development, foundation models, serving and orchestration, applications and agents — and explains the two shifts reshaping it: inference economics and the agentic runtime.

A deep dive into the LLM-as-a-judge methodology for automated AI evaluation — core principles, reliability standards, and the Ragas framework for assessing RAG systems.

Navigate the economic and regulatory side of AI with a guide to FinOps and compliance tooling — cost management and security for production systems.

Master the end-to-end LLM development lifecycle — a workflow mapping the right tools and practices to each stage of building reliable AI applications.

A guide to LLM-Evalkit, Google’s lightweight open-source tool for standardizing prompt engineering with a data-driven, collaborative workflow built on Vertex AI.