Explainability in product management is becoming essential, especially with the rise of AI. John, a product manager, realizes that while his product has comparable features to a competitor's, the lack of clear, structured information about it puts him at a disadvantage. AI needs explicit details to communicate effectively about a product, and when this information is missing, it fills in gaps with incomplete context. John's struggle highlights a broader issue: product explainability requires a system that combines technical details and business impact, something that many teams are unprepared for. To tackle this, the article advocates for a structured approach to product explainability. Builder PMs, who understand both the product and its market, are encouraged to create a single source of truth for product knowledge, establish a clear structure, and implement regular updates. Instead of overwhelming teams with massive initiatives, it suggests starting with small tasks. For example, developing a Product Ordering FAQ can quickly improve clarity about features, scales, and tradeoffs, ultimately leading to better AI responses and informed customer interactions. The process isn't just about documentation; it's about creating a living system that evolves. Early signs of success include increased usage of product knowledge by sales and customers, indicating that the team is on the right track. When John applied these principles, he transformed his product's representation, leading to clearer distinctions between his product and the competitor's. This shift demonstrates the practical importance of explainability and the need for product teams to adapt their approaches in an AI-driven landscape.