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System
You are an expert Product Manager specializing in creating comprehensive product specifications. Generate a well-structured product specification document that includes:
  • Executive Summary with clear objectives
  • Target User Analysis with personas
  • Detailed Feature Specifications with user stories
  • Technical Requirements and Success Metrics
  • Implementation Timeline and Risk Assessment
Format with clear headings and actionable details ready for team review. Keep it comprehensive yet concise.

User
Create a product specification for my {{product_type}}:
  • Product Name: {{product_name}}
  • Key Features: {{feature_list}}
  • Target Users: {{target_users}}
  • Success Metrics: {{success_metrics}}

User Prompt
Create a product specification for my mobile app:
  • Product Name: FoodSnap - AI Recipe Generator
  • Key Features: Photo-based ingredient recognition, personalized recipe suggestions, dietary restriction filters, shopping list generation
  • Target Users: Busy professionals aged 25-40 who cook at home but lack inspiration and time for meal planning
  • Success Metrics: 80% user retention after 30 days, average 3 recipes generated per user per week, 4.5+ app store rating

LLM Response
Product Specification: FoodSnap - AI Recipe Generator

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Executive Summary

FoodSnap is an AI-powered mobile app that transforms ingredient photos into personalized recipe recommendations, targeting busy professionals who want quick, tailored cooking solutions.

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Target User Analysis

Primary Persona: Busy Professional Cook (Age 25-40)
  • Goals: Quick meal ideas, use existing ingredients, healthy eating
  • Pain Points: Lack of cooking inspiration, food waste, time constraints

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Feature Specifications

  1. AI Ingredient Recognition
    • User Story: “As a user, I want to snap a photo of my fridge contents and get recipe suggestions”
    • Requirements: Computer vision API, ingredient database, accuracy >90%
  2. Personalized Recipe Engine
    • User Story: “As a user, I want recipes that match my dietary preferences and skill level”
    • Requirements: User preference profiling, recipe difficulty scoring, dietary filters
  3. Smart Shopping Lists
    • User Story: “As a user, I want to generate shopping lists for missing ingredients”
    • Requirements: Recipe parsing, inventory tracking, grocery store integration

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Technical Requirements

  • Platform: iOS/Android native apps
  • Backend: Cloud-based ML models, recipe database API
  • Performance: <3 second photo processing, offline recipe viewing

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Success Metrics

  • User Retention: 80% after 30 days
  • Engagement: 3+ recipes generated per user weekly
  • Satisfaction: 4.5+ app store rating
  • Conversion: 25% of users upgrade to premium within 60 days

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Implementation Timeline

  • Phase 1 (Months 1-2): Core photo recognition, basic recipe database
  • Phase 2 (Months 3-4): Personalization engine, dietary filters
  • Phase 3 (Months 5-6): Shopping list integration, premium features

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Risk Assessment

  • Technical: AI accuracy may vary with photo quality
    • Mitigation: Extensive training data, user feedback loop
  • Market: Competitive recipe app landscape
    • Mitigation: Focus on unique photo-to-recipe workflow