Building Generative Applications and RAG with Foundry
Introduction
This lesson opens the heaviest domain of AI-103: Implement generative AI and agentic solutions (30–35%). You will build the foundation used by every later lesson: calling a deployed model from Python, grounding answers with retrieval-augmented generation (RAG), chaining steps with tools, and measuring the result. Expect code-reading questions ("what does this snippet do?", "which parameter is wrong?") as well as design questions.
After this lesson you will be able to connect an application to a Foundry project, call models with the project client, design and debug a RAG pipeline, add tool-augmented and multistep flows, and evaluate fabrication, relevance, quality and safety.