PM Fundamentals7 min read
How to Write a Product Requirements Document (PRD): A Practical Guide with Examples
Table of contents
- 1. What Is a Product Requirements Document?
- 2. Why Do Product Managers Need a PRD?
- 3. What Should a Good PRD Include?
- 4. A Practical PRD Example
- 5. How Is a PRD Different for an AI Product?
- 6. Five Common PRD Mistakes
- 7. Do You Still Need a PRD in Agile?
- 8. Final Thoughts
- Want to Build Real Products, Not Just Study Theory?
The short answer: A product requirements document (PRD) explains what a product or feature should accomplish, who it's for, and how you'll know it worked. A good PRD covers the problem, target users, goals, success metrics, scope, requirements, user stories, constraints and open questions, kept short enough that your team actually reads it.
You have a great product idea. You've spoken to customers, identified a problem, and convinced your team that it's worth solving.
Now comes the difficult part.
How do you make sure your designers, engineers, and stakeholders all understand what you're trying to build?
This is where a Product Requirements Document, or PRD, becomes useful.
But a PRD isn't supposed to be a 30-page document that nobody reads.
It's a tool that helps your team understand the problem, align on the solution, and make better product decisions.
Let's break it down with a practical example.
1. What Is a Product Requirements Document?
A Product Requirements Document (PRD) explains what a product or feature should accomplish, who it's for, and what requirements need to be satisfied.
Think of it as a shared reference for your team.
A good PRD answers five important questions:
- What problem are we solving?
- Who experiences this problem?
- Why is solving it important?
- What should the product do?
- How will we know whether it worked?
Notice that we haven't started talking about programming languages, APIs, or databases.
Those decisions may be important, but the first responsibility of a Product Manager is to make sure the team understands the problem and desired outcome. (If you're unsure where product work ends and delivery work begins, see Product Manager vs. Project Manager.)
2. Why Do Product Managers Need a PRD?
Imagine you're working on a food delivery application.
Your customer support team reports that users frequently contact them because they cannot find their previous orders.
You suggest adding an order history search feature.
The engineering team asks whether users should search by restaurant, date, or order number.
Design wants to know whether the search should include canceled orders.
And customer support wants to know whether refunds should appear.
Without a shared document, everyone might make different assumptions.
A PRD helps the team align before those assumptions turn into expensive rework.
3. What Should a Good PRD Include?
There isn't one universal PRD template. Different companies use different formats.
However, most useful PRDs cover these areas:
| Section | What It Explains |
|---|---|
| Problem statement | What customers are struggling with |
| Target users | Who experiences the problem |
| Goals | What the feature should achieve |
| Success metrics | How results will be measured |
| Scope | What is included and excluded |
| Requirements | What the feature must do |
| User stories | How users will interact with it |
| Constraints | Technical, business, or policy limitations |
| Open questions | Decisions that still need investigation |
The objective isn't to fill every section with paragraphs.
It's to make the important decisions clear.
4. A Practical PRD Example
Let's continue with our food delivery application.
| PRD field | Example: Search Order History |
|---|---|
| Feature | Search Order History |
| Problem statement | Customers with frequent orders struggle to locate previous purchases, especially when they want to reorder meals or check historical receipts. |
| Target users | Customers who place multiple orders each month and need to access their purchase history. |
| Product goal | Make it easier for customers to find previous orders without contacting support. |
Example user story
As a returning customer, I want to search my previous orders by restaurant name so that I can quickly find a meal I purchased before.
Functional requirements
- Users can search previous orders by restaurant name.
- Results display the restaurant, order date, and total amount.
- Users can open an order to view its details.
- The system displays a helpful empty state when no matching orders are found.
Out of scope for the first release
- AI-powered recommendations.
- Searching individual food ingredients.
- Advanced filtering by multiple criteria.
Success metrics
- Percentage of searches leading to an order-details view.
- Time required to find a previous order.
- Support contacts related to finding previous orders.
- Search failure rate.
These metrics should be compared against the existing experience. The team should also monitor performance and customer satisfaction to ensure the change doesn't introduce new problems.
This is a small feature, but the same approach can be applied to much more complex products.
5. How Is a PRD Different for an AI Product?
Suppose instead of building a traditional search feature, your team proposes an AI assistant that answers questions about previous orders.
Now you have additional decisions to make:
- What information can the AI access?
- How should it respond when it doesn't know the answer?
- What happens if it provides incorrect order information?
- How much will each interaction cost?
For AI products, your PRD may need additional requirements covering:
| AI requirement | What to define |
|---|---|
| Model quality and evaluation | How you'll test that answers are accurate and useful |
| Data access and privacy | Which data the AI can read, and what it must never expose |
| Response time | How quickly users should get an answer |
| Operating costs | The acceptable cost per interaction |
| Fallback behavior | What happens when the AI is wrong or can't answer |
| Human review | When a person should check or take over |
For example, the AI assistant should never invent an order status when the order database is unavailable.
Instead, it should explain that it cannot retrieve the information and offer another way to get help.
That's an important product requirement, not merely an engineering detail. For more on the role behind these decisions, read What Does an AI Product Manager Do?
6. Five Common PRD Mistakes
Mistake 1: Starting with features instead of problems
"We need an AI chatbot" isn't a problem statement.
"Customers cannot find accurate information about their orders" is a problem worth investigating.
Mistake 2: Writing requirements nobody can test
"The search experience should be fast" is vague.
"The search results should appear within an agreed performance threshold under defined test conditions" can be tested.
Mistake 3: Including everything in the MVP
A PRD should help define what not to build, not just what to build.
Mistake 4: Forgetting success metrics
Shipping a feature doesn't mean it successfully solved the problem.
Mistake 5: Treating the PRD as permanent
A PRD should evolve as the team learns more. Changes should be documented so everyone understands what was decided and why.
7. Do You Still Need a PRD in Agile?
Yes, but you may not need a large document.
Agile teams still need clarity about customer problems, requirements, and success criteria.
Some teams use concise PRDs, others use product briefs, tickets, or linked documents. (Curious who owns the backlog in Scrum? See Product Manager vs. Product Owner.)
What matters isn't the format.
What matters is whether the team has enough information to make good decisions.
8. Final Thoughts
A good PRD doesn't guarantee a successful product.
But it can prevent confusion, expose assumptions, and help teams focus on outcomes instead of simply delivering features.
If you're learning Product Management, practice by selecting an application you use every day.
Identify one customer problem, write a one-page PRD, and define how you would measure success.
That's a practical way to develop the skills Product Managers use at work. Preparing for interviews too? Try these AI Product Manager Interview Questions.
Want to Build Real Products, Not Just Study Theory?
Inside my AI Product Management community, we connect Product Management fundamentals with hands-on AI product building.
You'll learn how to define customer problems, write product requirements, create prototypes, and evaluate AI-powered experiences.
— Mostafa Mekawy
Want more practical PM guides? Get my free AI Product Playbook, or see what's inside the AIPM community.