18 Jun 2025 3 min read ai

My ai garden

sholzman: "I’ve been using this chat environment as a tool to teach myself how to plan and care for a summer vegetable garden. What I’ve appreciated most is being able to learn iteratively—asking questions as they come up, troubleshooting in real time, and getting clear, contextual answers tailored to my specific situation. For a piece of content I’m putting together for my website, I’d like to capture that process. Can you write a short, objective summary of how I used, or someone could use, an AI chat environment like this to self-teach a practical, seasonal skill like gardening? Draw from specific examples in this chat environment. I’m not looking for hype or marketing language—just a clear explanation of how this kind of interaction can support learning through conversation, experimentation, and reflection. Many thanks!"

ChatGTP 4.0: "Certainly — here’s a clear, objective summary that reflects your experience:

Using AI Chat to Self-Teach a Seasonal Skill Like Gardening

An AI chat environment can serve as a responsive, context-aware companion for learning seasonal, hands-on skills like gardening. Rather than relying on static articles or broad how-to guides, the user engages in a conversation that evolves in real time—shaped by their goals, environment, and emerging questions.

In this case, the user taught themselves how to plan, plant, and care for a summer vegetable garden, starting from scratch. The process included working through decisions like:

Choosing container gardening as a manageable starting point, followed by upgrading to galvanized raised beds once comfort and confidence grew
Determining how much soil to buy and how to layer it for good drainage and fertility
Planning two distinct beds—one for starter plants (like tomatoes, zucchini, and peppers) and one for direct-sow crops (like lettuce, spinach, carrots, and radishes)
Adjusting planting timelines based on real-time weather forecasts for Easthampton, MA
Installing a rainwater collection system for roof runoff
Learning how to read and respond to plant health signs, including what to do when a bean plant wilted or a zucchini leaf yellowed
Deciding when and how to thin seedlings—and whether it was safe or worthwhile to eat the thinnings as microgreens
Knowing when herbs were mature enough to begin harvesting, and how to do so without damaging the plants
Sorting out what needed support (like tomato cages or pepper stakes) and what could grow freely

Throughout the process, the user shared photos of their setup and plant growth, asked targeted questions, and received clear, contextual responses tailored to what they were seeing that day. The interaction supported iterative learning: plant, observe, reflect, adjust. Guidance was available exactly when it was needed—whether that meant troubleshooting a drooping jalapeño or confirming that it was okay to direct-sow seeds after a stretch of cool nights.

This approach enabled a fluid, hands-on learning experience rooted in the real rhythms of the garden: trial, response, and small daily decisions. The chat environment functioned less like a teacher and more like a thinking partner—responsive, practical, and always ready to pick up where the last conversation left off."

On AI: I believe AI will be as disruptive as people fear. Our systems are brittle, and those building this technology often show little concern for the harm they’re accelerating. An AI future worth living in will require real accountability, robust regulation, strong ethical guardrails, and collective action—especially around climate and inequality. Dismantling capitalism wouldn’t hurt, either.

And still: I have hope. AI has helped me learn things I thought I couldn’t. It’s made my thinking feel more possible, closer to life. I don’t believe AI must replace our humanity—I believe it can help us exemplify it more clearly.

Using AI Chat to Self-Teach a Seasonal Skill Like Gardening

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