C12: Agentic AI Foundations for Interviews

Section 1: Agentic AI Foundations

SLIDE 1: Section Intro, Agentic AI Foundations

Section 1: Agentic AI Foundations

Agentic AI Foundations for Interviews

This course teaches you how to design, build, and defend AI agent systems in technical interviews. Every concept is grounded in real architecture decisions, production trade-offs, and concrete implementations in Python.

Instructor

Mukul Raina. Senior Software Engineer at Microsoft, MSc Software Engineering from the University of Oxford, BASc Computer Engineering from the University of Toronto. 13+ years of enterprise technology experience.

What This Course Delivers

1. How LLMs power agent systems and where they fail
2. Agent architecture patterns used in production (ReAct, prompt chaining, router, supervisor-worker)
3. Building complete agent systems: tool calling, RAG, memory, guardrails, observability
4. How to evaluate trade-offs between patterns (when to use what, and why)
5. How to handle reliability and security in production agents
6. How to present and defend agent designs in interviews

Who This Is For

Software engineers preparing for interviews at companies building with AI. You are targeting product companies and startups that expect you to understand how AI agents work, not just use them.

Prerequisites