Touch Grass: AI Garden Planner to Get You Outside

What I Built

I built the AI Garden Planner, a web application designed to help people get outside and start gardening. By simply entering your city or climate zone, the application uses an open-source AI agent to determine the best plants to start growing this week, taking into account local frost dates, seasonal patterns, and climate characteristics.

The goal is to eliminate the research paralysis that keeps many aspiring gardeners on their screens. Instead of spending hours reading through dense gardening almanacs and comparing frost dates, you get a quick, personalized planting plan so you can immediately go outside and get your hands dirty.

Demo

My Code

The source code for this project consists of a clean, responsive Vanilla HTML/CSS/JS frontend.

Architecture

graph TD;
    User[User Input: City/Zone] --> App[AI Garden Planner UI];
    App --> Agent[Open-Source AI Agent];
    Agent --> Data[Climate & Frost Data];
    Data --> Agent;
    Agent --> Plan[Weekly Planting Plan];
    Plan --> App;
    App --> Display[Rendered UI Cards];

Why Open Matters

Open innovation matters for this build because it empowers individuals to run their own planning agents without relying on closed, centralized services that might gatekeep information or monetize users' location data. For a tool designed to connect people with nature, privacy and local control are paramount. An open-source model allows you to run inference locally—so you could theoretically generate planting plans entirely offline at a remote community garden with no cell service.

Furthermore, an open approach means the community can fine-tune the agent with hyper-local agricultural knowledge, passing down gardening wisdom through an open dataset rather than locking it behind a subscription. Open-source AI isn't just about code; it's about making knowledge accessible so we can all spend less time scrolling and more time touching grass!