AI PRD Generator
The product requirements document AI that knows your codebase
Most AI PRD generators write confident prose about a system they've never seen. ProductOS writes requirements grounded in your real data models, your APIs, and your customers' actual words, so engineering stops saying “that's not how our system works.”
Want to try one right now, no signup?
Our free PRD generator writes a complete 8-section PRD from a one-line idea.
From signal to spec in three steps
Describe the need, or paste the signal
Start from a feature idea, a customer interview, or a support thread. ProductOS researches the market and your users before a single requirement is written.
Connect your existing product
ProductOS reads your codebase once and keeps only the map: data models, APIs, patterns. We never store your code. Your PRD references what actually exists.
Get a PRD engineering respects
User stories, acceptance criteria, scope, and technical considerations that account for your architecture. Then hand it to engineers via MCP, or keep going to designs and working code.
What an engineering-ready PRD includes
- Problem statement backed by research and customer evidence quotes
- User stories with acceptance criteria
- Scope and explicit non-goals
- Technical considerations that reference your real models and endpoints
- Prioritization rationale your engineers can interrogate
- One-click handoff: MCP into Cursor/Claude Code, or continue to design and code in ProductOS
🔒 We never store your code. We read it once and keep only the map.
AI PRD generator FAQ
How is this different from ChatGPT or ChatPRD?
Prompt-based PRD tools write from a blank page, so the output reads like generic AI prose. ProductOS writes the product requirements document from context: your connected codebase (real models, real APIs) and your customer evidence. The difference shows in the first engineering review.
What does "grounded in the codebase" actually mean?
When you connect your product, ProductOS builds a structural map: the Code Wiki. The PRD then references actual entity names, existing endpoints, and established patterns, so engineers review a spec that already fits their system instead of translating a wish list.
Can my engineers use it without leaving their tools?
Yes. That's the point. Via MCP, Cursor and Claude Code pull the full payload into the coding session: the spec, the designs, the customer quotes, and the prioritization rationale. Nothing gets re-explained.
Does it only write documents?
No. The PRD is one stage of a pipeline: research → PRD → design → working code (web and mobile) → deploy. Every stage inherits everything the previous one learned.
Your next PRD can reference your real system.
Free to start: your first feature's research, PRD, and design in one session.
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