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
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
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
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
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
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
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
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
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
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
Explanation: Hallucinations occur when LLMs confidently state incorrect facts. Agents should verify critical information.
Self-Check Guide
- 0-3 correct: Early starting point; expect the phase to fill in a lot.
- 4-6 correct: Good foundation and ready to deepen your knowledge.
- 7-8 correct: Strong baseline for the advanced material.
- 9-10 correct: Excellent starting point; some concepts may already feel familiar.
What’s Next?
After completing this quiz:
- Don’t worry about your score - it’s just a baseline
- Note which topics felt unfamiliar - focus on those
- Start with Notebook 1 - Introduction to AI Agents
- Retake this quiz after the phase - measure your growth!
Ready to learn? Let’s dive into AI Agents! 🚀