{
  "lesson": "11-planning-htn-and-evolutionary",
  "title": "Planning with HTN and Evolutionary Search",
  "questions": [
    {
      "stage": "pre",
      "question": "What does an HTN add over a free-form LLM plan?",
      "options": [
        "Provable correctness when operator preconditions and effects are enforced",
        "Cheaper inference",
        "Shorter prompts",
        "Better embeddings"
      ],
      "correct": 0,
      "explanation": "HTN's symbolic operators with preconditions and effects guarantee soundness by construction."
    },
    {
      "stage": "pre",
      "question": "Which problem class is AlphaEvolve built for?",
      "options": [
        "Free-form prose generation",
        "Optimizations with a machine-checkable, deterministic fitness function",
        "Multi-turn chat memory",
        "Vector search ranking"
      ],
      "correct": 1,
      "explanation": "Evolutionary search needs a deterministic evaluator; AlphaEvolve targets domains where one exists."
    },
    {
      "stage": "check",
      "question": "How does ChatHTN preserve plan soundness while using an LLM?",
      "options": [
        "It does not; soundness is best-effort",
        "LLM suggestions only enter as candidate decompositions, validated against the operator schema; the symbolic layer owns correctness",
        "It fine-tunes the LLM on HTN traces",
        "It uses a vector database"
      ],
      "correct": 1,
      "explanation": "The LLM expands the method library but cannot bypass operator preconditions and effects."
    },
    {
      "stage": "check",
      "question": "Which AlphaEvolve result does the lesson cite?",
      "options": [
        "First improvement over Strassen for 4x4 complex matrix multiplication in 56 years",
        "10x speedup of inference on Gemini",
        "Beating GPT-4 on HumanEval",
        "First proof of P=NP"
      ],
      "correct": 0,
      "explanation": "AlphaEvolve found 48 scalar multiplications for 4x4 complex matmul, the first improvement on Strassen in 56 years."
    },
    {
      "stage": "check",
      "question": "Which element of an HTN is a primitive directly-executable action with preconditions and effects?",
      "options": [
        "Task",
        "Method",
        "Operator",
        "State"
      ],
      "correct": 2,
      "explanation": "Operators are the primitives; methods decompose compound tasks; state is a set of facts."
    },
    {
      "stage": "post",
      "question": "What is the lesson's warning about AlphaEvolve without a real evaluator?",
      "options": [
        "It is slow",
        "Asking an LLM whether the code is better is not a fitness function; the evaluator must be deterministic and fast",
        "It violates Apache 2.0",
        "It cannot run on GPUs"
      ],
      "correct": 1,
      "explanation": "Without a deterministic evaluator the search has no signal to converge on."
    },
    {
      "stage": "post",
      "question": "When should you reach for ReAct or ReWOO instead of HTN or AlphaEvolve?",
      "options": [
        "Never; HTN is strictly better",
        "When you do not need formal soundness or a machine-checkable fitness; most agent tasks land here",
        "When you have a GPU cluster available",
        "When latency is below 100 ms"
      ],
      "correct": 1,
      "explanation": "The lesson explicitly warns against over-engineering: most tasks do not need formal planning or evolutionary search."
    }
  ]
}