Product Requirements Document (PRD)

Overview

When to Use

• Starting a new product or feature development cycle
• Translating a vague idea into a concrete technical specification
• Defining requirements for AI-powered features
• Stakeholders need a unified "source of truth" for project scope
• User asks to "write a PRD", "document requirements", or "plan a feature"

Operational Workflow

Phase 1: Discovery (The Interview)

• The Core Problem: Why are we building this now?
• Success Metrics: How do we know it worked?
• Constraints: Budget, tech stack, or deadline?

Phase 2: Analysis & Scoping

• Map out the User Flow.
• Define Non-Goals to protect the timeline.

Phase 3: Technical Drafting

PRD Quality Standards

Requirements Quality

# Vague (BAD)
- The search should be fast and return relevant results.
- The UI must look modern and be easy to use.

# Concrete (GOOD)
+ The search must return results within 200ms for a 10k record dataset.
+ The search algorithm must achieve >= 85% Precision@10 in benchmark evals.
+ The UI must follow the 'Vercel/Next.js' design system and achieve 100% Lighthouse Accessibility score.

Strict PRD Schema

1. Executive Summary

• Problem Statement: 1-2 sentences on the pain point.
• Proposed Solution: 1-2 sentences on the fix.
• Success Criteria: 3-5 measurable KPIs.

2. User Experience & Functionality

• User Personas: Who is this for?
• User Stories:

  As a [user], I want to [action] so that [benefit].

• Acceptance Criteria: Bulleted list of "Done" definitions for each story.
• Non-Goals: What are we NOT building?

3. AI System Requirements (If Applicable)

• Tool Requirements: What tools and APIs are needed?
• Evaluation Strategy: How to measure output quality and accuracy.

4. Technical Specifications

• Architecture Overview: Data flow and component interaction.
• Integration Points: APIs, DBs, and Auth.
• Security & Privacy: Data handling and compliance.

5. Risks & Roadmap

• Phased Rollout: MVP -> v1.1 -> v2.0.
• Technical Risks: Latency, cost, or dependency failures.

Implementation Guidelines

DO (Always)

• Define Testing: For AI systems, specify how to test and validate output quality.
• Iterate: Present a draft and ask for feedback on specific sections.

DON'T (Avoid)

• Skip Discovery: Never write a PRD without asking at least 2 clarifying questions first.
• Hallucinate Constraints: If the user didn't specify a tech stack, ask or label it as

  TBD

  .

Example: Intelligent Search System

1. Executive Summary

• Reduce search time by 50%.
• Citation accuracy >= 95%.

2. User Stories

• Story: As a developer, I want to ask natural language questions so I don't have to guess keywords.
• AC:
  • Supports multi-turn clarification.
  • Returns code blocks with "Copy" button.

3. AI System Architecture

• Tools Required:

  codesearch

  ,

  grep

  ,

  webfetch

  .

4. Evaluation

• Benchmark: Test with 50 common developer questions.
• Pass Rate: 90% must match expected citations.