It started as a simple experiment: could ChatGPT help me manage a small backyard greenhouse? Nothing fancy—just a mix of herbs, tomatoes, peppers, and a few experimental plants that I couldn’t keep alive the year before. What surprised me wasn’t that it worked. It was how it worked.

At first, I used ChatGPT as a digital farmer’s almanac. I’d describe local conditions here in Georgia—soil type, humidity, temperature, sunrise times—and ask for daily care suggestions. It helped me set watering intervals and feeding schedules based on projected weather swings. When I added sensor data (temperature, humidity, light), the feedback became specific. It could identify when the soil was holding too much water or when the shade cloth should stay up an extra hour.

I started feeding it journal entries every evening: what plants looked stressed, which ones thrived, what the weather had done that day. In return, it offered patterns. “The basil tends to droop two days after high humidity spikes.” “Tomato growth correlates with longer morning light windows.” None of this was mystical; it was pattern recognition—but the kind that humans usually take a season or two to learn.

Soon, I was asking more complex questions. Could it recommend which plants to rotate next season to replenish soil nutrients? Could it compare the local forecast against my greenhouse’s microclimate to prevent mildew? It could—and it did.

That’s when I realized something: AI had effectively become my new Farmer’s Almanac. Not a static book of wisdom, but a living one—context-aware, hyperlocal, always learning. It blended tradition with data. It didn’t replace intuition; it tuned it.

The thing about plant care is that it’s slow feedback. You can make a mistake today and not see the consequences for a week. Having something track those delays and connect the dots is powerful. I stopped thinking of ChatGPT as just an assistant. It became part of the rhythm of care—the quiet note-taker that never forgets a variable.

Sometimes, when I walk into the greenhouse early in the morning, I check the light, feel the humidity, and think, somewhere in the background, an AI knows this pattern now. And that’s strangely comforting. It’s not farming by formula; it’s farming with awareness.

We once relied on the almanac to tell us when to plant by the moon. Now, we have an almanac that learns our soil, our light, and our mistakes. And helps us get better, season by season.

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