Phase 14: AI Agents - Pre-Quiz

Test your baseline knowledge before starting the AI Agents phase.

Instructions

  • Answer all 10 questions

  • Don’t look up answers - this is to gauge your starting point

  • Your score doesn’t matter - it’s about identifying learning gaps

  • Time limit: 15 minutes

Questions

Question 1

What is the main difference between a chatbot and an AI agent?

  • A) Chatbots are faster

  • B) Agents can use tools to take actions

  • C) Chatbots are more expensive

  • D) There is no difference

Answer B) Agents can use tools to take actions

Explanation: While chatbots only respond to text, agents can execute functions, query databases, and interact with external systems.

Question 2

In the context of AI agents, what is “function calling”?

  • A) Calling functions in your code manually

  • B) The LLM decides which functions to execute based on context

  • C) A debugging technique

  • D) A way to make the agent faster

Answer B) The LLM decides which functions to execute based on context

Explanation: Function calling allows the LLM to intelligently select and invoke tools/functions to accomplish tasks.

Question 3

What does “ReAct” stand for in agent design patterns?

  • A) React Framework

  • B) Reasoning + Acting

  • C) Real Actions

  • D) Reactive Programming

Answer B) Reasoning + Acting

Explanation: ReAct combines explicit reasoning (thinking) with actions (tool use) in an iterative loop.

Question 4

Which of these is a valid tool schema component?

  • A) name, description, parameters

  • B) title, body, footer

  • C) input, output, process

  • D) start, middle, end

Answer A) name, description, parameters

Explanation: Tool schemas define the function name, what it does, and what inputs it requires.

Question 5

Why is input validation important for agent tools?

  • A) To make the code look professional

  • B) LLMs can generate invalid or malicious inputs

  • C) It’s not important

  • D) Only for debugging

Answer B) LLMs can generate invalid or malicious inputs

Explanation: Even though LLMs generate inputs, they can make mistakes or generate values that break your system. Always validate.

Question 6

What is agent “memory” in the context of AI agents?

  • A) RAM usage

  • B) Storing conversation history and learned information

  • C) The model’s training data

  • D) Cache for faster responses

Answer B) Storing conversation history and learned information

Explanation: Agent memory allows it to remember past interactions, user preferences, and context across sessions.

Question 7

In a multi-agent system, what is “coordination”?

  • A) Making agents run faster

  • B) Managing how agents communicate and collaborate

  • C) Deleting unused agents

  • D) A debugging technique

Answer B) Managing how agents communicate and collaborate

Explanation: Coordination ensures multiple agents work together effectively, sharing information and dividing tasks.

Question 8

What problem does “caching” solve for AI agents?

  • A) Prevents redundant API calls

  • B) Makes the agent smarter

  • C) Reduces code complexity

  • D) Increases accuracy

Answer A) Prevents redundant API calls

Explanation: Caching stores recent results to avoid calling expensive APIs repeatedly for the same information.

Question 9

Which framework is specifically designed for building AI agents?

  • A) React

  • B) Django

  • C) LangChain

  • D) Bootstrap

Answer C) LangChain

Explanation: LangChain is a framework specifically built for creating LLM-powered applications including agents.

Question 10

What is a “hallucination” in the context of AI agents?

  • A) A visual effect

  • B) When the agent generates false or invented information

  • C) A performance optimization

  • D) An error message

Answer B) When the agent generates false or invented information

Explanation: Hallucinations occur when LLMs confidently state incorrect facts. Agents should verify critical information.

Scoring Guide

  • 0-3 correct: Perfect! You’ll learn a lot in this phase

  • 4-6 correct: Good foundation - ready to deepen your knowledge

  • 7-8 correct: Strong baseline - you’ll master advanced concepts

  • 9-10 correct: Excellent! You may already know some agent concepts

What’s Next?

After completing this quiz:

  1. Don’t worry about your score - it’s just a baseline

  2. Note which topics felt unfamiliar - focus on those

  3. Start with Notebook 1 - Introduction to AI Agents

  4. Retake this quiz after the phase - measure your growth!

Ready to learn? Let’s dive into AI Agents! 🚀