The AI product landscape has exploded into a diverse ecosystem of product categories, each with distinct technical requirements, user expectations, and go-to-market strategies. As an AI product leader, your ability to recognize these differences—and adapt your approach accordingly—will determine whether your product thrives or becomes another cautionary tale.
123456789101112from dataclasses import dataclass from enum import Enum from typing import List, Dict class AICategory(Enum): GENERATIVE = "generative_ai" PREDICTIVE = "predictive_ml" CONVERSATIONAL = "conversational_ai" COMPUTER_VISION = "computer_vision" RECOMMENDATION = "recommendation_system" @dataclass
123456789101112// Metrics schema for different AI product categories interface BaseAIMetrics { productId: string; timestamp: Date; userId: string; sessionId: string; latencyMs: number; modelVersion: string; } interface GenerativeAIMetrics extends BaseAIMetrics {