EV

I came to electric vehicles the way I come to most things: I bought one, got obsessed, and started instrumenting it. What keeps me here isn't the car as a product — it's the car as a system. A modern EV is a rolling fleet of sensors, a software platform that ships meaningful updates on a cadence most enterprise systems would envy, and a node in a much larger energy graph that runs from the grid through the wall to the battery. That's the angle this section takes. It's "EV," not a brand name, on purpose — the interesting problems are about energy, data, and autonomy, and most of them outlive whatever I happen to be driving.

A few threads I keep pulling on:

Driver assistance is the most public AI deployment most people will ever live with. Supervised self-driving is a moving target that updates underneath you, which makes it a rare chance to watch a real autonomy stack improve — and occasionally regress — in the wild, on roads I drive every day. The engineering is interesting; the ethics are more interesting still, and harder than the marketing on either side admits. That tension is worth writing about honestly rather than as either hype or backlash.

Charging is an energy-and-economics problem hiding inside a convenience feature. The question "how much does it actually cost to drive a mile" turns out to be genuinely hard to answer, because the wall energy that leaves your meter is not the energy that reaches the battery — onboard-charger and EVSE losses sit in between. Answering it well means joining vehicle telemetry, whole-home energy monitoring, and utility interval data, none of which were designed to be joined. That intersection is where the real insight lives.

Instrumentation turns a car into an observable system. I run TeslaMate for drive and charge logging, and I built SWEAT — my single-user energy dashboard — to ingest vehicle, whole-home, and utility data into one place and surface the cross-source questions no single vendor app can answer. Telemetry-first, multiple ingestion paths run side by side, status vocabulary that distinguishes "sleeping" from "broken." It's the same engineering posture I bring to everything else here, applied to my own vehicle.

The crossover with the rest of this site is real. The autonomy stack connects directly to AI. Charging load, behind-the-meter generation, and demand response push straight into GridTech. The on-prem collectors and home-IP constraints that make SWEAT work are the same patterns I wrestle with in Home Automation. An EV is where grid, AI, and personal infrastructure meet at one-vehicle scale, with a fast feedback loop and a real bill attached.

Posts under this section will be a mix: honest field notes on driver assistance as it changes, the economics and data work behind charging and efficiency, build notes on the tools, and the occasional cross-pollination piece where a one-car problem mirrors something I've seen at grid scale.

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