Finding AI-Native Problems

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import openai
import time

def test_ai_feasibility(problem_description: str, sample_inputs: list[str]) -> dict:
    """
    Quick feasibility test for AI-native problems.
    Tests if current AI can solve the problem with acceptable quality.
    """
    client = openai.OpenAI()
    results = {
        'success_rate': 0,
        'avg_latency': 0,

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interface MarketSizeInputs {
  totalAddressableUsers: number;
  percentageWithProblem: number;
  percentageWillingToPay: number;
  averageMonthlyPrice: number;
  competitorMarketShare: number;
}

interface MarketSizeOutput {
  TAM: number;  // Total Addressable Market
  SAM: number;  // Serviceable Addressable Market  
  SOM: number;  // Serviceable Obtainable Market

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import json
from dataclasses import dataclass
from typing import Callable
import openai

@dataclass
class TestCase:
    input: str
    expected_output: str
    category: str  # e.g., 'simple', 'edge_case', 'adversarial'
    difficulty: int  # 1-5