Petals
One of my fondest childhood memories was tending to my grandfather’s rose garden. As young as I was (around 9 years old), gardening was less of a chore and more of a way to enjoy the time with my grandpa. This hobby also coincided with typical 4th grade science course content like photosynthesis. That a plant’s petal could harness sunlight and use it for its own growth perplexed me. I enjoyed disentangling these concepts in class, but what I naturally gravitated towards was understanding that photosynthesis was just a pin drop in a pool of processes, lifecycles, and mechanisms that governed whether the roses in the garden could survive or not.
The gardening techniques I learned over the spring and summer months helped fill in the blanks for my ‘budding’ interest. Removing faded, dead, and worn out flowers (deadheading or pruning), ensuring continued access to nutrient-rich soil (mulching and fertilization), and watering the plants — each with its own particular technique — clarified for me that, while a plant executes its own internal processes (like photosynthesis, respiration, and transpiration), I was assisting it, by following a tried-and-true, external process to maintain its equilibrium. This, iterated over and over again across the rose bed, attracted cross-pollinators, offered nesting sites, and enhanced soil health. It felt good to act as a steward in this way, with the added bonus of doing so in good company.
Processes
Four years later, after my grandfather passed away, life grew ‘busier’ as a thirteen-year-old. Yet, I still made time to care for the roses. I had salvaged a clutter of rose bushes from my grandfather’s property, and as their sole gardener, applied the same horticultural methods, refining them over time. Revisiting these memories has helped me recognize the evidence of how I developed my process-oriented way of thinking. One specific experience stands out above the rest.
Bottlenecks as Problems
The garden boasted 8 rose bushes, spread out at least two feet away from each other. My half-cracked, lime green watering can couldn’t hold very much water. Even when full, it was quite heavy to carry from plant to plant. Stooping down and pouring the water at the base always got my shoes and ankles dirty. Wanting to lift less and spare my shoes, I sketched out a canal system to centralize the flow of water between each bush. Water then flowed from the first plant downstream until the last plant. With time, I learned that my canal design was susceptible to bottlenecks. At times, a twig would block the waterway or silt would accumulate along the bottom of the canal. I continuously cleared twigs and occasionally had to restore the canal to its original dimensions. The solution for clearing away bottlenecks was sometimes a quick fix or it required larger, structural modifications. Without realizing it at the time, my consistent effort in restoring capacity to the canal became a training ground for applying the bottleneck framework of problem solving. It remains a cherished childhood memory of putting the theory of constraints (TOC) into practice.
The bottleneck framework is not a catch-all problem solving method, but it remains a proven way to spot inefficiencies. Over the past five years, as both a student and professional practicing systems thinking, I’ve come to value this style of reasoning for its rigor: carefully identifying, defining, and diagraming the problem to be solved (”work the problem” is a phrase I often keep in mind). By this method, one can measure a problem and then build/find the solution that addresses it (The Goal was a great primer for me on TOC and system thinking). But the problem to be solved, a gap, inefficiency, or limitation is transitory. It’s what we see and choose to define as a problem, and then, what we think is worth solving. In this way, problems are moving targets rather than static objects of study.
Bottlenecks as Opportunities
In The Structure of Scientific Revolutions, Thomas Kuhn argues that scientific progress, applicable to modern-day technological progress, advances in a stepped pattern via paradigm shifts rather than a singular curve of cumulative progress. These seismic shifts fundamentally change the rules of the game in dictating what society deems as constraints and the ceiling of innovation. A modern day example of this concept in action is the AI labor market. Once upon a time, rules-based programming needed engineers to holistically key in all of the software scenarios. Now, the question is “which engineers can teach a model to evolve and adapt to all software scenarios?” The type of engineer needed (the problem to be solved) has changed because of a technological breakthrough. This example is about talent, but the whole build, ship, monitor, secure, and maintain product development cycle is shifting.
The questions that demand answers evolve over time, which is why it is essential to first understand the problem to be solved. To me, the intersection of precisely identifying problems and doing so repeatedly over time is deeply compelling. This is the primary reason why the world of deploying innovation-enabling capital excites me.
The Systems Ledger
Revisiting this singular data point in my childhood has been a journey into my own epistemology. My hope is that the Systems Ledger be a space to record my impressions and insights, and at times, apperceptive takes as I develop my own ways to think about investing. While the scope may evolve, my curiosity gravitates toward innovations disrupting the future of deep tech, the industrial economy, food tech, and healthcare. My hope is that this exercise of expatiating will help refine my ideas over time.
Retardmaxxing
