The Curse of the "Complete" Mind
In 4th grade study hall, I was given a simple task: Describe how to make a peanut butter and jelly sandwich.
I wrote it down, confident and quick. I presented my answer, and the teacher looked at me and said, "Wrong."
I was fuming. How can you be "wrong" about a sandwich? But then came the questions that changed how my brain worked forever:
"Where did you get the peanut butter from?"
"How did you open the jar?"
"How did you get the contents out, and specifically, where did they go?"
I realized then that most people live in the "result." I was being forced to live in the process. That frustration turned into a lifelong obsession with completeness.
The Architect’s Dilemma: Completeness vs. Brevity
That 4th-grade lesson is exactly why I spent 21 years mastering systems like Archibus. In a million-square-foot facility, you can’t just "fix a leak." You have to know the valve location, the pipe material, the last inspection date, and the downstream impact. You have to be complete.
In my hobbyist world of AI and 3D modeling, the same rule applies. If you don't define the "normals" of a 3D object or the "parameters" of an LLM, the whole thing collapses.
But here is the irony: After decades of being told to "be more thorough" and "show the work," the feedback in 2026 has shifted. Now, the world wants brevity.
The Middle Ground
The "Peanut Butter Lesson" taught me how to see the invisible steps. But the AI era is teaching me how to package them.
Today, my value isn't just knowing how to open the jar—it’s building the system that opens the jar automatically so the end-user only sees the sandwich. We have to be complete in our thinking so we can be brief in our delivery.
I’m still that kid in 4th grade who wants to tell you exactly how the knife enters the jar. But now, I translate that detail into code, SQL, and automated workflows, so you don't have to fume over the details like I did.