Evaluating RAG Systems

Overview

Evaluating RAG Systems is part of the AI Engineering Foundations path and is designed for long-form technical reading with progress tracking, roadmap navigation, and future MDX-backed enhancements.

The Core Logic

This page architecture supports diagrams, code snippets, callouts, and embedded learning components while keeping the reading experience focused and navigable.

Add real MDX content under content/[path-slug]/[module-id]/[lesson-slug].mdxto replace this placeholder lesson with authored material.

Implementation

1export function lessonExperience() {
2  return {
3    readingProgress: true,
4    persistentNavigation: true,
5    toc: 'desktop',
6    responsiveLayout: 'stacked-mobile',
7  }
8}

Best Practices

• Keep headings meaningful so the generated table of contents is useful.
• Pair code examples with narrative explanation and architecture context.
• Use modules to turn large topics into learnable chunks.