I treat daily decisions as coordinates in a high-dimensional space. When you move beyond simple pros and cons lists, you begin to see how variables interact. In our main guide on thinking like an AI, we established that mental models act as cognitive frameworks for complex inputs. Vector Based Thinking takes this further by treating time, cost, and utility as distinct axes. By assigning numerical weights to these factors, you can calculate the distance between your current state and your desired outcome. This method removes emotional bias from your logic.
To apply this, I define three primary dimensions for every dilemma I face. Time represents the duration required for execution. Cost captures the financial or resource-based expenditure. Utility measures the long-term benefit or personal growth gained from the choice. I represent these as a vector V = [t, c, u]. When I compare two potential paths, I calculate the magnitude of the difference vector. If the distance is small, the choices are functionally equivalent. If the distance is large, one path clearly dominates the other in terms of efficiency.
You can refine your decision-making by applying these specific steps to your daily workflow:
- Assign a value from one to ten for time, cost, and utility for every option.
- Normalize these values so they reflect your personal priorities or constraints.
- Plot these points on a mental graph to visualize which choice offers the highest return.
- Calculate the dot product of your vector against your core life goals.
- Discard any options that fall outside your acceptable threshold for resource consumption.
Mathematical rigor provides clarity when intuition fails. During my own testing of this framework, I discovered that I consistently undervalued the utility of long-term learning tasks. By forcing myself to assign a value to utility, I realized that many low-cost, high-time tasks were actually the most valuable investments. This shift in perspective changed how I schedule my mornings. I now prioritize tasks that align with my high-utility vectors rather than just checking off small, low-effort items. It is a precise way to ensure my daily output matches my long-term intent.
Vector Based Thinking is not just for software architects or data analysts. Anyone can use these principles to organize their mental space and reduce decision fatigue. By mapping your choices into a structured space, you gain a clear view of trade-offs that were previously invisible. You stop guessing which path is better. You start seeing the geometry of your life. This approach brings a level of consistency to your choices that few other mental models can provide.
