In this meeting, the discussion was mainly around optimizing and improving sweeps on simulated input/output processes. The State Changers addressed issues surrounding circular dependencies, cash flow optimization, understanding the role of taxes, and incorporating another dimension (deferred taxes) into the process.
Certain key principles were reiterated, such as the rule that in any optimization, only one aspect can be optimized. It underscored the importance of simplifying processes, breaking them into independent components, and organizing such components in a sequence where possible to avoid problems in high-dimensional optimization. The State Changers exchanged strategies for efficient organization and going line by line through calculations, reducing manual re-setting of inputs, and managing potential errors. They discussed how incorporating machine learning techniques can help in complex cases, warning against “local minima” in the valley — a trap in high-dimensional optimization. The meeting highlighted the interdependencies of several financial indicators like free cash flow, net income, undrawn fees, income tax schedules, among others, demonstrating the complexities of these constructs and the necessity for structured analytical methodologies. Although technologies such as Xano, Retool, AppGyver, Javascript, and OpenAI were not explicitly named in the dialogue, their underlying principles, especially in manipulation of JSON objects and data optimization, were inherent in the discussed methods.
(Source: Office Hours 10/2 )
