Isaiah Granet highlights the challenges software companies face when bridging the gap between product capabilities and customer needs. He distinguishes between two types of forward deployed engineers (FDEs): those who enhance the product and those who merely patch gaps with human labor. The latter often lead to a linear business model where hiring more engineers is necessary for each new customer, limiting scalability. In contrast, effective FDEs improve the software by documenting patterns and creating templates, resulting in faster deployments and better products. Granet emphasizes the transformative potential of FDEs in AI companies. Unlike traditional software, AI products evolve continuously, requiring ongoing human expertise. An FDE can help a company automate entire functions, such as replacing a call center, rather than just implementing a tool. This shift means that the contributions of FDEs are not limited to individual hours but are amplified through the product's growth and adaptability. For investors, evaluating an AI company with a significant FDE presence requires a different set of metrics than what’s typically used for consulting businesses. Monitoring the ratio of FDEs to customers is critical. A decreasing ratio indicates that the product is improving and absorbing lessons from the field. Assessing how much of the FDE work is novel versus repeated can reveal whether the product team is effectively addressing new challenges or stuck in a cycle of repetitive tasks. These insights are essential for understanding whether the FDE operation is gaining or losing leverage.