Agentic

Fleet operators running electric vehicles face an asymmetry of information that costs them money every week. The vehicles generate enormous quantities of data - battery state, voltage, current draw, motor temperature, GPS, speed - every few seconds. Most of it goes nowhere. When something fails, it fails in the field: recovery time, roadside assistance, cargo delays.

Lots of rhetoric aimed at leadership teams positions the question about AI and software development as primarily whether it will replace engineers. It's the wrong question. Asking it means missing something more useful. The better question is what a single engineer can build in an hour, starting from scratch, and what that tells you about how technical work is changing.

The gap between a written product concept and working, tested, version-controlled code can now be closed without a developer writing a line of application code. From PRD to PR without code, automation is happening today.

After creating a few AI agents, orchestration is the obvious next step; you get those agents talking with each other and working collaboratively, you go from having an assistant to having a team at your disposal. This requires an orchestration framework to connect the agents - I opted for LangGraph for this project due to it working on a state-machine basis, allowing cycles and loops where the agents could get into critique and refine loops with each other.