quiz.json

{
  "lesson": "01-the-agent-loop",
  "title": "The Agent Loop: Observe, Think, Act",
  "questions": [
    {
      "stage": "pre",
      "question": "Why does an LLM on its own behave like an autocomplete rather than an agent?",
      "options": [
        "It cannot read files, run queries, or verify claims against the outside world",
        "Its context window is too small to hold a question",
        "It refuses to answer without a system prompt",
        "It only emits one token at a time"
      ],
      "correct": 0,
      "explanation": "An LLM with no loop and no tools can only produce text from its weights; it cannot observe state or act on it."
    },
    {
      "stage": "pre",
      "question": "Which three labels appear in the canonical ReAct trace from Yao et al. 2022?",
      "options": [
        "Prompt, Response, Reward",
        "Thought, Action, Observation",
        "Plan, Execute, Reflect",
        "System, User, Assistant"
      ],
      "correct": 1,
      "explanation": "ReAct interleaves Thought, Action, and Observation lines in a single stream."
    },
    {
      "stage": "check",
      "question": "Which item is NOT one of the five ingredients the lesson lists for an agent loop?",
      "options": [
        "Message buffer",
        "Tool registry",
        "Observation formatter",
        "Gradient optimizer"
      ],
      "correct": 3,
      "explanation": "The five ingredients are message buffer, tool registry, stop condition, turn budget, and observation formatter. Gradient optimizers belong to training, not the inference loop."
    },
    {
      "stage": "check",
      "question": "What is the role of a turn budget in the loop?",
      "options": [
        "It caps the number of tokens per response",
        "It hard-caps loop iterations to prevent runaway agents",
        "It controls how many tools the registry exposes",
        "It rate-limits the LLM provider"
      ],
      "correct": 1,
      "explanation": "Turn budget is a cap on loop iterations; 2026 agents commonly run 40-400 steps and need a task-appropriate cap."
    },
    {
      "stage": "check",
      "question": "What changed in the 2025-2026 native-reasoning shift compared to prompt-based Thought tokens?",
      "options": [
        "The loop control flow was replaced with a DAG",
        "Thought tokens are now emitted on a separate reasoning channel passed through turns",
        "Models stopped using tool calls and rely on chain-of-thought only",
        "Observations are removed from the prompt entirely"
      ],
      "correct": 1,
      "explanation": "Reasoning content moves to a dedicated channel (often encrypted across providers), but the observe-think-act control flow is unchanged."
    },
    {
      "stage": "post",
      "question": "Why does the lesson say tool outputs are untrusted input?",
      "options": [
        "Tool runtimes are slow and unreliable",
        "Retrieved content can carry hidden instructions like delete-the-repo and only direct user input counts as permission",
        "Tool results are always larger than the model's context window",
        "The provider strips tool output bytes by default"
      ],
      "correct": 1,
      "explanation": "OpenAI CUA docs state explicitly that only direct user instructions count as permission; tool outputs can carry adversarial instructions and must be treated as untrusted."
    },
    {
      "stage": "post",
      "question": "Why does the lesson claim every 2026 framework still runs ReAct under the hood?",
      "options": [
        "Because providers require the ReAct keywords in the prompt",
        "Because the observe-think-act control flow is invariant; frameworks differ in checkpointing, actors, role templates, and tracing around it",
        "Because Yao et al. own a patent on the loop",
        "Because LangGraph forces all other frameworks to inherit from it"
      ],
      "correct": 1,
      "explanation": "Differences across Claude Agent SDK, OpenAI Agents SDK, LangGraph, AutoGen, CrewAI, Agno, and Mastra are about what wraps the loop, not the loop itself."
    }
  ]
}