ArborPlus
An internal operating platform connecting sales, scheduling, production, reporting, customer communication, and field-service workflows at A Plus Tree.
Read the case noteI turn production, margin, capacity, sales, and workflow problems into software, data systems, AI automation, and decision tools that work in the real world.
The through-line is simple: find a consequential operating problem, make it legible, and build the system that lets people run it better.
An internal operating platform connecting sales, scheduling, production, reporting, customer communication, and field-service workflows at A Plus Tree.
Read the case noteA self-hosted mission-control system that lets different AI agents work from the same durable context, project structure, and human-controlled rules.
Read the case noteForecasting, capacity, backlog, pricing, margin, and production systems built around the questions leaders actually need answered.
Read the case noteI work across the line that usually separates the operator from the builder. That makes it possible to carry a problem from leadership conversation to live system without losing the business context in between.
Start with the operating room, the field handoff, or the decision that keeps breaking—not with a technology shopping list.
Define the workflow, metric, ownership, and source of truth so the organization can see the same problem clearly.
Use software, data, automation, or AI where it creates leverage. Keep the solution close to the work.
Ship, observe, correct, and turn the result into a durable operating habit rather than a one-time analysis.
Writing about operations, product systems, practical AI, and what I am learning while building Loomfield.
Why the next useful layer for AI is not a better chat window, but a shared brain, durable work, and controls that earn trust over time.
Next notes: why dashboards fail, building software from operating questions, and what AI systems need before they deserve automation.
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