{
  "lesson": "01-claude-product-and-model-landscape",
  "title": "Choose the Smallest Surface That Can Carry the Work",
  "questions": [
    {
      "stage": "pre",
      "question": "A regulated application must use an existing Azure agreement, Entra identity, Azure RBAC, and a US data-zone deployment. Which path is the strongest starting candidate?",
      "options": [
        "Amazon Bedrock with an AWS regional endpoint",
        "Microsoft Foundry with the required Azure hosting and deployment type",
        "Claude for Enterprise seats plus direct Claude API workspaces",
        "Google Vertex AI with a US multi-region endpoint"
      ],
      "correct": 1,
      "explanation": "Foundry aligns the stated procurement, identity, operations, and cloud boundary. The team must still verify the current hosting option and feature support."
    },
    {
      "stage": "check",
      "question": "When is Research a better fit than a direct web search?",
      "options": [
        "When one current fact needs confirmation from its authoritative primary page",
        "When the answer needs citations but the relevant source and claim are already known",
        "When several sources must be gathered, reconciled, and cited",
        "When one known document must be opened and checked for an exact policy clause"
      ],
      "correct": 2,
      "explanation": "Research fits broad multi-step investigation. A narrow fact usually needs a simpler search and verification path."
    },
    {
      "stage": "check",
      "question": "What is the safest durable rule for choosing among Haiku, Sonnet, and Opus?",
      "options": [
        "Select the family with the largest context window, then tune prompts to meet cost targets",
        "Assign each family a permanent task category based on its published positioning",
        "Default to the strongest family for external work, then downgrade low-risk internal tasks",
        "Test the smallest plausible family against representative success criteria and escalate on measured failure"
      ],
      "correct": 3,
      "explanation": "The family roles are useful, but actual selection should be measured against the task's quality, latency, and cost constraints."
    },
    {
      "stage": "check",
      "question": "An organization buys Claude for Enterprise for employees and also calls the direct Claude API from an application. Which control design is strongest?",
      "options": [
        "Govern named-user seats and member limits separately from API workspace keys, rate limits, and spend limits",
        "Choose only one control plane because direct Anthropic products share the same identity and budget semantics",
        "Use the Enterprise seat policy for application rate limits and the API workspace for employee access",
        "Treat seats and API tokens as one pooled capacity because both are procured from Anthropic"
      ],
      "correct": 0,
      "explanation": "Human seats and application consumption are different usage shapes. Their identity, budget, and access controls must remain explicit even under direct procurement."
    },
    {
      "stage": "post",
      "question": "An AWS-first company requires AWS IAM, AWS billing, and an AWS-managed inference security boundary. Which deployment path best matches those requirements?",
      "options": [
        "Google Vertex AI because multi-region endpoints are cloud-neutral",
        "Amazon Bedrock, after verifying current model, region, and features",
        "Claude for Enterprise because SSO replaces workload IAM",
        "Microsoft Foundry because Azure Marketplace can be billed back to AWS"
      ],
      "correct": 1,
      "explanation": "Bedrock matches the stated AWS control plane. Current model access, endpoints, data handling, and feature support remain dated inputs."
    },
    {
      "stage": "post",
      "question": "A Google Cloud team needs application inference inside its existing project, IAM, billing, and EU endpoint strategy. What should its ADR do?",
      "options": [
        "Select Vertex AI and permanently encode today's feature matrix because project identity will remain stable",
        "Compare only token prices because Google Cloud already owns identity, procurement, and incident response",
        "Select Vertex AI, then record current model, feature, endpoint, processor, and pricing evidence with a verification date",
        "Select direct Claude API because model behavior is identical across providers and control planes do not affect architecture"
      ],
      "correct": 2,
      "explanation": "Vertex AI fits the stated control plane, but the ADR must preserve dated evidence for every changeable platform fact and name its review triggers."
    }
  ]
}