Most AI tools promise to “write your PRD.”
But most stop at looking good — not working well. They generate text that resembles a PRD, but lacks the logical depth and structural consistency a real Product Requirements Document needs.
At HowToWritePRD, we took a different approach. We built a dedicated PRD AI Pipeline — a system that encodes the actual thinking process of a product manager. It doesn’t just write; it reasons through a PRD the way a human PM would.
In this post, we’ll walk you through how our AI structures a real PRD using an example product: a Habit Tracker App.
Step 1. Business & Product Overview — Turning Ideas into Business Language
Every PRD starts with a single user idea.
Let’s say the user writes: “I want to build a habit tracker that lets users check off daily routines and visualize their progress.” Our system doesn’t just summarize that text.
The Business Analysis Module interprets it as intent — identifying what problem the idea is solving and what value it aims to create.
It then transforms that intent into a concise overview: To help users build consistent habits by providing simple tracking and visual motivation.
This step is not mere summarization — it’s translation from idea to product logic.
Step 2. Problem Definition — Defining Why the App Should Exist
In our pipeline, problem definition is the foundation of every PRD.
The AI automatically extracts key pain points from the input idea and structures them into a Problem Statement: People want to form new habits but struggle to consistently track their progress and stay motivated.
This sentence naturally follows from the Business Overview, forming the first logical section of the PRD.
That flow — from idea to reason to definition — is one of the key design principles behind our pipeline.
Step 3. Target Audience — Identifying Who Faces This Problem
Next, our User Segmentation Engine activates.
It infers target groups directly from the problem context:
- Office workers who want to build better daily routines
- Students aiming to maintain study habits
- Individuals pursuing fitness or wellness goals
But instead of just listing segments, the AI also outlines the context for each — describing why each group needs the app.
Step 4. Core Features — Structuring Solutions to Match Problems
This is the heart of the PRD: defining what the product does and why.
Our AI doesn’t simply suggest features; it constructs a cause-and-effect relationship between user problems and solutions.
For example:
- Manual Logging — lets users record their progress daily
- Progress Visualization — gives instant visual feedback
- Streak Challenges — motivates consistency through rewards
- Goal Setting — helps users define clear, measurable targets
The output isn’t just a feature list — it’s a structured explanation of why each feature matters.
Step 5. MVP Scope Control — Defining What to Build (and What Not To)
This is one of the most unique aspects of our system.
The AI automatically differentiates between core MVP scope and secondary features, prioritizing feasibility and focus.
Included: Manual Logging, Goal Setting, Streak Challenges
Excluded: GPS auto-tracking, community feed, admin dashboard This stage protects the direction of early development — making sure the PRD serves as a decision framework, not just a document.
Step 6. Final Output — A Structured PRD Draft
After processing each stage, the PRD AI Pipeline produces a structured draft like this:
App Name: Habitly (working title)
Business Overview: Helps users stay motivated through simple tracking and visual rewards.
Problem: Users struggle to maintain consistency when forming new habits.
Target Audience: Office workers, students, and individuals focused on self-improvement.
Core Features: Manual Logging, Progress Visualization, Streak Challenges, Goal Setting.
Scope: MVP version includes only essential features.
This isn’t a “text generated by AI.” It’s the output of structured reasoning, modeled after how real PMs think.
PRD Template vs. Our PRD AI Pipeline
Conclusion — We didn’t Build an AI Writer. We Built an AI Product Manager.
Our AI isn’t designed to write anything. It’s built to write one thing well — a PRD.
We engineered a system optimized for structured reasoning, not storytelling.
It understands the logic of product thinking — how PMs define problems, prioritize features, and scope MVPs.
That’s what makes our AI PRD Pipeline fundamentally different from any other generative system out there.
👉 Generate a clean PRD with HowToWritePRD
