ML and Generative AI in the Data Lakehouse

Chapter 8. GenAI in a Databricks Lakehouse Environment

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GenAI is reshaping how we interact with enterprise data, and the Databricks Lakehouse provides an ideal foundation for building production-grade generative systems that combine structured and unstructured data under a single governance and compute layer. In this chapter, we explore how to harness those capabilities, moving from effective prompt design to full retrieval-augmented generation (RAG) pipelines, all running natively on Databricks.

We begin with a detailed discussion of prompting and prompt engineering, showing how small changes in phrasing, role definition, or context shaping can dramatically influence model behavior. Using the Databricks AI Playground, you’ll experiment interactively with prompts, temperature settings, and context windows to develop intuition about how LLMs respond under different configurations. This section establishes the foundation for the more advanced techniques that follow.

From there, we bridge the gap ...