Mock AI Interviews

Introduction

Ten mock interview prompts you can run with a friend or an LLM partner. Each is ~45 minutes including code and discussion.

Understanding the topic

Core concepts:

• Live-build a ReAct agent with one tool.
• Design an enterprise multi-agent support system on a whiteboard.
• Walk through your prompt eval workflow.
• Cost-optimise a sample trace dump.
• Defend a system against prompt injection live.
• Add memory to a chatbot in 30 min.
• Design a RAG system over 10M docs.
• Implement a router agent over 5 specialists.
• Add human-in-loop to an autonomous run.
• Post-mortem on a failed agent run.

Syntax reference

Visual workflow / architecture:

┌──────────────┐
│   Exercise   │
└──────┬───────┘
       ▼
  Build · Test · Eval
       │
       ▼
  Compare with model answer

Real-world use

These mirror real loops at AI-first startups and enterprise AI teams.

Best practices

• Record yourself and review.
• Time-box ruthlessly; interviewers do.

Common mistakes

• No diagram — your story becomes mush.

Hands-on exercise

Interview preparation — practice these questions:

• Q1. How would you structure a 45-min live build?
• Q2. Three signals interviewers look for in a design round.
• Q3. Scenario: you're stuck on a question — what's your recovery strategy?