Free Lesson

Design a Production RAG System Live

30 min
Aug 10, 2026 4:15 PM
Virtual (Zoom)

In this video

What you'll learn

Structure a RAG design from sources to evaluation

Follow a six-part outline that covers what interviewers and production both demand.

Diagnose why retrieval returns the wrong chunks

Work through the three causes of bad retrieval and the fix for each one.

Name the failure modes before you are asked

Cover staleness, chunk boundaries and ranking so the follow-up questions land easy.

Why this topic matters

Ask an AI engineer to design a RAG system and you learn everything about them in ten minutes. Weak answers stay at the prompt layer. Strong ones walk through data sources, chunking, retrieval quality, ranking, evaluation and the ways it fails. This is the most common opener in AI engineering interviews and the most common thing built badly in production.

You'll learn from

Aki Wijesundara, PhD

Aki Wijesundara, PhD

AI Advisor | Educator | Google AI Accelerator Alum

Google
Meta
OpenAI
Amazon Web Services
NVIDIA
Manu Jayawardana

Manu Jayawardana

AI Founder | CEO at TAI Labs | Co-Founder of Snapdrum

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