Study 5 Real PRD Examples for Tech Products (2025)

1.1 Purpose

This document outlines the requirements for an AI-based PRD Reviewer, a new tool offered by pmprompt.com. The tool allows users to upload or paste a PRD, then analyzes and grades the content. It also provides actionable feedback to improve clarity, completeness, and alignment with best practices in product management.

1.2 Background & Rationale

• PRDs are central to product development: A well-written PRD aligns teams around goals, requirements, and success metrics.
• AI-driven assistance: Growing opportunity to automate and enhance document review processes.
• Competitive advantage: Address a niche in the market beyond basic grammar checking.

• Product Managers: Need quick validation and improvement of PRDs
• Entrepreneurs & Founders: Less experienced in formal PRD writing
• PM Students/Enthusiasts: Looking for tutorials and feedback
• Cross-Functional Teams: Need to verify PRD structure and clarity

• Number of unique users running PRD analysis weekly/monthly
• User-reported satisfaction via ratings or surveys
• Conversion rate of free users to premium plans
• Reduction in time spent on manual reviews

Make fine-grained adjustments to priority levels within basic categories. If you implement a stack-ranking system for your tasks and projects, this is specifically made for you!

A very common use case we encounter is global stack-ranking: customers want to form a stable, opinionated order of priority across all of their backlog items. Today, we provide a global manual ordering feature, which we recommend for these cases.

Key Issues:

• Instability: Manual sort is often unstable. Users often don't treat this ordering with care because it feels low-stakes.
• Local vs. Global Sorting: In other apps, manual sort is often local. Users are often surprised we have global manual ordering.
• Redundancy with Priority Field: Having both manual sort and a priority field creates confusion when trying to create a global priority stack rank.

User Pain Points:

• Requests for "custom priority levels" due to insufficient granularity in the 4 basic buckets
• Requests for custom fields to add a "ranking" column for numerical stack-ranking

Allow users to adjust and rearrange the relative priority of their issues within a priority bucket through drag-and-drop. This will be recommended as the primary method for all stack-ranking use-cases.

Options Considered But Rejected:

• Custom priority levels - Would encourage too many distinct categories
• Custom fields - Would solve stack-ranking but diverges from Linear's opinionated defaults philosophy

• MS1: Internal
  • Implement drag-and-drop within priority levels
  • Handle priority changes when dropping between different priority sets
• MS2: Beta
  • Initialize using existing manual sort index
  • Bootstrap initial microadjust ordering
• MS3: GA + Changelog
  • Release alongside project priorities
  • Present cohesive story about Linear's priority system

Make Story Time is a web application that allows users to create personalized AI bedtime stories. The application leverages modern AI technology to generate custom stories based on character information, converts text to audio, and provides a beautiful reading experience with downloadable formats.

• Backend: Laravel 12
• Frontend: Blade templates with Tailwind CSS 4
• Interactivity: Livewire
• Database: SQLite (chosen for simplicity, easy deployment, and sufficient performance for expected load)
• Storage: Cloudflare R2
• Payment: Stripe
• APIs: OpenRouter (AI), Text-to-Speech service

• Mobile-first design throughout the entire application
• Clean, intuitive step-by-step form approach
• Genre selection with visual icons
• Character creation form optimized for touch input
• Setting and theme inputs with visual cues
• Progress indicators for form completion
• Immersive book reading experience with:
  • Page-turning animations
  • Background textures/themes
  • Text that adapts to screen size
  • Optional read-along highlighting
  • Synchronized audio narration
• Persistent audio player that allows users to continue listening while navigating

1. User registers/logs in
2. User navigates to "Create Story" page
3. User selects genres and story template
4. User creates main character and adds details
5. User defines setting (time and place)
6. User adds theme, conflict, and moral elements
7. User adds any special requests
8. User selects target audience
9. User is directed to payment page
10. After payment, system processes:
    • AI story generation
    • Audio narration creation
    • Storage of assets
11. User is notified when story is ready
12. User can view, listen to, and download the story
13. User can access all stories from their dashboard

The PRD includes a comprehensive ERD with the following key entities:

• USERS - Stores user account information
• STORIES - Contains story details and metadata
• CHARACTERS - Stores character information for each story
• STORY_TEMPLATES - Defines available story templates
• STORY_SETTINGS - Contains setting details for each story
• PAYMENTS - Tracks payment information

Key relationships include:

• A User can have many Stories
• A Story belongs to a User
• A Story can have many Characters
• A Story has one StorySettings
• A Story is based on a StoryTemplate
• A Payment belongs to a User and a Story