Independent build · Energy & EV · In personal use
Turn energy signals into a useful decision.
Tariff and carbon signals turned into useful charging windows and automation.
01 / problem
The problem to solve
EV owners can access tariff and grid-carbon data, but the data alone does not answer the practical question: when should I charge, and what difference will that choice make? The product problem is turning changing energy signals into a decision that is simple enough to act on.
02 / decision
The decision
I chose to test the whole decision loop rather than build another energy dashboard: understand the outlook, choose a charging window, automate the action and then see what happened.
03 / approach
How I approached it
The native iOS app combines Octopus tariff data with UK grid carbon-intensity signals and turns them into a 24-hour charging outlook. I connected recommendations to automation rules and usage insights so the product can move from information to action and then make the result visible.
04 / outcome
What changed
PowerPilot is in personal use and includes unit tests. It surfaces estimated cost, carbon impact and completed charging activity, giving me a direct way to test whether the recommendation-to-action loop is understandable and useful. Any savings shown by the product remain estimates rather than measured customer outcomes.
05 / What I take forward
What I take forward
A useful recommendation must be understandable enough to trust and simple enough to repeat. Personal use lets me test that loop directly.
Inside PowerPilot
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