A few days after decoding my car’s oxygen sensor mystery, I found myself staring at another stubborn system: my swimming pool. It looked fine—clear, calm—but anyone who owns one knows that the chemistry can turn against you overnight. The test strips told me I was off balance again: chlorine, pH, alkalinity, all drifting. Normally, I’d guess, dump in a little of this or that, and hope for the best. But now I had a new habit—ask ChatGPT first.

I explained what I was seeing, including the color gradients from the test strip. I even took a photo in even light, away from direct sun, because I’d learned that lighting changes the perceived color. ChatGPT helped me interpret the results accurately, referencing the manufacturer’s chart and adjusting for normal daylight conditions. It then suggested what to add—and in what quantities—to bring the water back into range.

The interesting part came later. I realized that ChatGPT could act as a logbook. Each time I tested the pool, I entered the date, readings, and actions taken. Over a few weeks, it built a history of my pool’s behavior—how sunlight, rainfall, and temperature affected the chemistry. That turned the AI into a kind of pool chemist and historian rolled into one.

After a while, I started to see patterns. For instance, chlorine always dipped two days after a heavy rain, and pH crept upward during long hot weeks. ChatGPT would spot these cycles and even remind me when to test earlier when conditions were about to shift. The more data I gave it, the smarter it got at anticipating the pool’s rhythm.

It struck me that this wasn’t really about pools at all. It was about how accessible expert-level maintenance becomes when you combine simple sensors with an intelligent interpreter. Most of us have the data—we just don’t have the patience or background to decode it. AI fills that gap. It connects the dots and turns trial-and-error into deliberate care.

Soon, I had what I half-jokingly called my “water diary.” A record of adjustments, weather patterns, and results. It wasn’t fancy, but it meant I could predict issues before they happened. No more green surprises after a storm. No more guessing.

I could see everyday people using this same pattern—for garden care, home HVAC, or even basic car maintenance. The point isn’t to replace professionals. It’s to make the language of maintenance readable to the rest of us.

AI doesn’t just answer questions. It teaches you how to ask better ones. And sometimes, that’s all you need to keep the water clear.

Jorge Luis de la Torre. I put the C in GRC. I bring compliance to the table.