{
"type": "quiz",
"passThreshold": 0.7,
"questions": [
{
"id": "q1",
"text": "A New Zealand agriculture company needs to process 80,000 sensor readings daily for crop health classification. Which model characteristic should they prioritise when selecting an AI model?",
"points": 10,
"options": [
{"id": "a", "text": "The highest reasoning capability available for maximum accuracy"},
{"id": "b", "text": "Speed and cost per query, since classification is a well-defined, high-volume task"},
{"id": "c", "text": "The largest context window to process all readings at once"},
{"id": "d", "text": "Multimodal capabilities for processing video alongside sensor data"}
],
"correctAnswers": ["b"]
},
{
"id": "q2",
"text": "Your company uses Claude Sonnet for all AI tasks. Your monthly bill is $4,500. After analysis, you find that 70% of requests are simple email classification. What multi-model strategy would most effectively reduce costs?",
"points": 10,
"options": [
{"id": "a", "text": "Switch everything to Claude Haiku to reduce costs across the board"},
{"id": "b", "text": "Implement a router pattern that sends simple classification to Haiku and keeps complex tasks on Sonnet"},
{"id": "c", "text": "Use the ensemble pattern to run every request thro
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