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hands-on lab

Improving Agentic Systems with RAG & Prompt Engineering

Difficulty: Intermediate
Duration: Up to 1 hour and 30 minutes
Students: 36
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Description

In this lab you'll explore how to use prompt engineering and RAG (Retrieval-Augmented Generation) to improve agentic system performance.

Learning objectives

Upon completion of this lab, you will be able to:

  • Use prompt engineering and RAG to improve agentic system performance

Intended audience

  • AI Engineers

Prerequisites

Completion of previous modules is highly recommended before attempting this lab.

Updates

November 18th, 2025 - Updated Demo notebook to use batch embedding and merge vector stores to avoid token rate-limiting

Covered topics

Artificial Intelligence
Hands-on Lab UUID

Lab steps

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  1. Starting the Notebooks

Lab Rules