Core Insights - The traditional PRD (Product Requirement Document) is failing in AI product development due to the unpredictable nature of AI and the chaotic business processes involved [5][10] - The emergence of AI programming tools in 2025 allows product managers to create functional demos without needing coding skills, transforming the concept of "code as requirement" into reality [12][22] Group 1: PRD Limitations - Traditional PRD struggles with AI projects because AI's behavior is unpredictable and business processes are irregular [5] - AI's unpredictable responses make it difficult to define requirements in a document, as nuances in tone and interaction cannot be captured accurately [6] - The complexity of AI interactions leads to convoluted business processes that are hard to document, making traditional flowcharts ineffective [8] Group 2: Tool Revolution - AI programming tools like Cursor 2.0 enable product managers to generate runnable prototypes by simply describing their needs, making the development process more efficient [12][13] - Tools such as Trae 2.0 allow for full AI-led development, significantly reducing the time required to create functional prototypes [12] - Google's Gemini 3.0 enhances code generation efficiency, allowing for better integration of design and functionality [13] Group 3: Delivery Upgrades - The concept of "code as requirement" is not about replacing PRD but restructuring delivery standards in the AI era, combining demos, documentation, and evaluation sets [15] - Demos help address soft logic issues, allowing for real-time adjustments based on feedback from stakeholders [15][17] - Clear documentation of hard logic, such as data mapping and API definitions, remains essential for successful AI project execution [17][20] Group 4: Compliance and Performance - Product managers must include non-functional requirements in their deliverables to ensure compliance with regulations like GDPR while transitioning from demo to production [20] - The production environment must be designed to handle real-world demands, such as simultaneous requests and cost optimization, which are often overlooked in demo versions [20]