purpose, features, and behavior
Atlassian: How to create a product requirements document (PRD) The guide uses this as the baseline for what a PRD is meant to align: product purpose, user need, features, and success criteria.

Key facts

Source base
Public sources cover PRD practice, requirements engineering, Working Backwards, AI prompting, and hallucination risk.
AI files
llms.txt and llms-full.txt summarize core pages, tools, templates, and source context.
Publication stance
Idea2PRD is an independent educational site and its templates are original synthesis.

Bibliography

Sources used

IEEE/ISO/IEC 29148-2018

IEEE Standards Association · Accessed 2026-07-06

Requirements-engineering standard used here for requirement quality, traceability, and lifecycle discipline.

IEEE 830-1998

IEEE Standards Association · Accessed 2026-07-06

Historical software requirements specification reference, useful for explaining the PRD/spec boundary.

Start with why

AWS Prescriptive Guidance · Accessed 2026-07-06

AWS guidance on PR/FAQ as a way to clarify scope and downstream feature planning.

Prompt engineering

OpenAI Developers · Accessed 2026-07-06

Official OpenAI guidance on prompts as instructions that shape model output.

GPT-4.1 prompting guide

OpenAI Cookbook · Accessed 2026-07-06

OpenAI guidance used to frame AI PRD work as an empirical drafting and evaluation loop.

Accelerating Research with AI

Nielsen Norman Group · Accessed 2026-07-06

Research guidance used to limit where AI helps most in discovery and PRD preparation.

Product Development Flow

GitLab Handbook · Accessed 2026-07-06

Public product-development workflow reference for moving from validation to build without ceremony creep.

People + AI Guidebook

Google PAIR · Accessed 2026-07-06

Human-centered AI design guide used for AI PRD requirements around user trust, control, and uncertainty.

Citation policy

How sources are used

Idea2PRD uses public sources to ground definitions, requirements-engineering discipline, Working Backwards context, and AI limitations. The templates and examples are original synthesis, not copied source material.

Source quotes are intentionally short and attached to the page where they are most relevant. Most guidance is paraphrased into practical product-management language.