Vertical software has effectively captured what’s termed the "context graph," a critical component in enterprise software that many are now trying to build from scratch. Context graphs record the reasoning behind business decisions, not just the outcomes. They reflect the accumulated knowledge of a company's operations, including exceptions and precedents. While many argue that the future of enterprise software lies in new startups that can capture these decision traces, vertical software companies have been developing context graphs for over a decade. The distinction between vertical and horizontal software is key. Horizontal platforms like Salesforce use generic data models, which can apply to various industries but fail to capture specific business realities. In contrast, vertical software offers opinionated, purpose-built data models tailored to specific industries. For example, in a construction management platform, data structures might include elements like change orders and weather delays, allowing for a more nuanced understanding of why decisions were made. This depth not only aids in recording reasoning but also consolidates functions into cohesive systems, reducing silos of information. Moreover, vertical software leverages relationships within its data to enhance inferential density. This means that rather than requiring explicit notes on decisions, the reasoning can be reconstructed from the connections between data points. When an order is linked to inventory, customer data, and payment information, trends and issues can be identified without needing an agent to log every decision. This structural advantage positions vertical platforms favorably as they extend their context graphs by integrating more functions that occur at the edges of their systems, such as marketing and procurement. By embedding these additional capabilities, they deepen their understanding of their specific industry, capturing valuable insights that horizontal platforms may miss.