An AI prototype is a powerful artifact that details user experience and functional requirements. However, it doesn't replace the Product Requirements Document (PRD). The PRD remains essential for outlining the strategic "why"—market differentiation, user acquisition, and monetization—which a prototype cannot convey.
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AI prototyping doesn't replace the PRD; it transforms its purpose. Instead of being a static document, the PRD's rich context and user stories become the ideal 'master prompt' to feed into an AI tool, ensuring the initial design is grounded in strategic requirements.
Contrary to claims that "handoff is dead," designers at top companies use AI-generated prototypes as highly detailed specs. These interactive prototypes provide more information than static designs but are still handed off to developers for implementation, rather than being merged directly into production.
The traditional workflow (Idea -> PRD -> Alignment) is outdated. Now, PMs first create a functional AI prototype. This visual, interactive artifact is then brought to engineers and scientists for debate, accelerating alignment and making the development process more creative and collaborative from the start.
The team no longer relies solely on PRDs and design docs. Product managers are now required to build a functional prototype as a core part of the development cycle, ensuring ideas are validated with a working model early on.
Even for a simple personal project, starting with a Product Requirements Document (PRD) dramatically improves the output from AI code generation tools. Taking a few minutes to outline goals and features provides the necessary context for the AI to produce more accurate and relevant code, saving time on rework.
Product Requirement Documents (PRDs) are often written and then ignored. AI-generated prototypes change this dynamic by serving as powerful internal communication tools. Putting an interactive model in front of engineering and design teams sparks better, more tangible conversations and ideas than a flat document ever could.
For complex features, a 17-page requirements document is inefficient for alignment. An interactive AI-generated prototype allows stakeholders to see and use the product, making it a more effective source of truth for gathering feedback and defining requirements than static documentation.
Instead of writing detailed Product Requirement Documents (PRDs), use a brief prompt with an AI tool like Vercel's v0. The generated prototype immediately reveals gaps and unstated assumptions in your thinking, allowing you to refine requirements based on the AI's 'misinterpretations' before creating a clearer final spec.
Resist the temptation to treat AI-generated prototype code as production-ready. Its purpose is discovery—validating ideas and user experiences. The code is not built to be scalable, maintainable, or robust. Let your engineering team translate the validated prototype into production-level code.
In an AI-driven workflow, the primary value of a rapid prototype is not for design exploration but as a communication tool. It makes the product vision tangible for stakeholders in reviews, increasing credibility and buy-in far more effectively than a slide deck.
