You Just Need the Curiosity to Ask.

Right now, data is accumulating about your life at a rate that would have seemed extraordinary twenty years ago. Your smartwatch is tracking your heart rate, sleep, movement, stress levels. Your phone knows where you’ve been. Your smart heating system logs every room, every degree, every hour the boiler runs. Your emails, your documents, your photos, your calendar — all of it sitting somewhere, all of it quietly building a detailed picture of how you actually live.

Most of that data does very little for you.

My first frustration has always been with health. The technology is extraordinary — years of heart rate data, sleep cycles, activity levels, all sitting in Apple Health, collected faithfully, surfaced in a way that’s occasionally interesting but rarely actionable. You get a weekly summary. A congratulation when you close your rings. Now and then a notification that your heart rate seems elevated.

But the data is there. I believe there’s real signal in it — patterns that could tell you something genuinely useful about how your body works, what affects your energy, where the connections are. It’s just never been surfaced in a way that does anything with it.

Same story everywhere I look. The data exists. The tools that could make sense of it exist. What’s missing is anything that connects the two in a way that actually serves the person it belongs to.

To get anything useful out of your own data, you’ve always needed one of three things: the technical skills to query it yourself, the money to pay someone who could, or the time to make it a proper project. Most people have none of those in the right quantity. Organisations built data teams. You didn’t have that luxury. So the data worked for them, not for you.

I trained as a software engineer. I’ve built serious systems — geographically redundant databases, physical server setups, a side project in Rails. I know what an API is. I could theoretically have queried our Tado heating data years ago. I never did. Because the gap between “I could figure this out” and “I can be bothered to figure this out at 9pm on a Tuesday” is enormous. It was always a weekend project I’d never start.

If that was my experience, I’m fairly sure it was everyone else’s too.

AI is changing that. Not in a grand way — in a very practical, slightly boring, genuinely useful way.

A few weeks ago I asked my AI assistant to pull our Tado data and show me how our heating was actually performing. I should say when I asked: Sunday morning, still in bed, no intention of doing anything remotely productive. Just a question that had been nagging at me. What came back surprised me. Every room was overshooting its target temperature by a degree or two — the boiler was working harder than it needed to. And buried in the data was something I’d never looked at: the boiler’s main flow temperature setting, running higher than it needed to be.

(There were other things too — the spare room had 16 schedule periods, the ghost of a home automation I’d set up so Maddie could heat it when she was working in there and had completely forgotten about.)

I turned the flow temperature down. The following week I asked for a comparison. 31% less heating demand, rooms exactly as warm as before. And when I asked why, I got an explanation: lower flow temperature means the boiler runs in condensing mode more often, recovering heat from exhaust gases that would otherwise disappear up the flue. Efficiency goes up, gas use goes down, the house doesn’t notice.

I didn’t write a line of code. I didn’t get out of bed. I just kept asking questions.

The data was always there. What was missing was any realistic way to use it without making it a project. That bar is gone now. You don’t need the skills, the budget, or the weekend you’ll never get around to. You just need the curiosity to ask.