AI System Design

AI engineering interviews increasingly include a system design round: design a RAG assistant, a support agent, a document pipeline. It's a different skill from writing code, and there is little good practice material for it.

In this workshop we cover both sides: how to approach AI system design interview questions, and how real AI systems are architected. We go through questions live and design the systems step by step.

What we'll cover: - What an AI system design interview looks like and what interviewers check - A step-by-step way to approach a question: requirements, data, retrieval, model choice, tools, evaluation, monitoring, cost - Design one or two systems end to end on a whiteboard - How the same decisions look in real-world AI system architecture - The trade-offs that come up again and again: latency vs cost, RAG vs fine-tuning, single agent vs multiple agents - Common mistakes

You'll leave with a framework you can use for system design interviews and for designing your own projects.

Who it's for: people preparing for AI engineering interviews, and engineers who want to design AI systems more deliberately.

Prerequisites: basic understanding of LLMs, RAG and agents. The recording is shared with members after the session.