DEV Community: Harshitha H G

TouchGrass AI: An Open-Source AI Mission Planner That Gets You Outside 🌿

Harshitha H G — Sun, 11 Oct 2026 06:59:47 +0000

What I Built

I built TouchGrass AI, a small open-source AI-powered outdoor activity planner designed to help people spend less time on screens and more time outside.

The idea is simple: instead of spending a long time deciding what to do, the user gives a few details such as their available time, preferred activity, and energy level. The application then generates a simple outdoor mission that they can complete in the real world.

The goal is to make the interaction with the application short and actionable — use the screen to get the mission, then put the phone away and go outside. 🌱

Why I Built It

It is very easy to spend too much time on screens, even when we actually want to take a break.

I wanted to experiment with whether AI could be used for the opposite purpose: instead of keeping someone on a screen, use AI to give them a reason to leave the screen.

For example, the application can suggest activities such as:

Going for a short walk
Exploring a nearby area
Sitting outside and observing nature
Taking a short outdoor break
Going on a photo walk
Finding something interesting around you

The generated mission is intended to be simple enough that the user can immediately act on it.

Demo

Try TouchGrass AI here:

https://harshitha-hg.github.io/Touchgrass-ai/

Code

The complete source code is available on GitHub:

https://github.com/Harshitha-HG/touchgrass-ai

How I Built It

I built the project using:

HTML
CSS
JavaScript
WebLLM
SmolLM2 open-weight model
GitHub Pages

The application uses WebLLM to run an open-weight AI model directly in the browser.

The model is used to generate personalized outdoor missions based on the user's inputs.

The project also includes a fallback mechanism so that the application can still provide a useful outdoor mission on devices where local AI inference has limitations.

How Open-Source AI Is Used

The AI is not just added as a chatbot.

The open-weight model is part of the core functionality of the project because it generates the outdoor mission.

The project uses an open-weight SmolLM2 model through WebLLM, allowing inference to happen in the browser rather than requiring a traditional cloud AI API for the main generation process.

This makes the project interesting from an open-AI perspective because developers can inspect the implementation, modify the prompts, experiment with different open-weight models, and extend the application.

How It Gets People Outside

The main idea behind TouchGrass AI is:

Short interaction → Get a mission → Put the phone away → Go outside.

Instead of creating another application that encourages users to continuously interact with their screens, TouchGrass AI tries to make the screen interaction as short as possible.

The output is an activity that can be completed away from the device.

Why Open Innovation Matters

Open innovation makes it possible for developers to understand, modify, and improve the technology they use.

With open-source AI and open-weight models, developers can experiment with different models, change prompts, build new applications, and learn from the underlying technology.

For a project like TouchGrass AI, this also makes experimentation easier. Someone could fork the project and turn it into:

A bird-watching assistant
A running route planner
A gardening assistant
A nature exploration tool
A local photography challenge generator

The community can take the basic idea and build something completely different from it.

What I Learned

This project helped me understand how open-weight AI models can be integrated directly into a web application.

I also learned that an AI project does not have to be complicated to be useful.

The interesting part of TouchGrass AI is not simply generating text with AI. The purpose is to use AI to encourage an activity that happens outside the screen.

Final Thought

AI is usually associated with keeping us connected to our devices.

With TouchGrass AI, I wanted to try something different:

Use AI to help you put the phone down. 🌿

TouchGrass AI: An Open-Source AI Mission Planner That Gets You Outside 🌿

Harshitha H G — Sun, 11 Oct 2026 06:53:36 +0000

What I Built

I built TouchGrass AI, a small open-source AI-powered outdoor activity planner designed to help people spend less time on screens and more time outside.

The goal is to make the interaction with the application short and actionable — use the screen to get the mission, then put the phone away and go outside. 🌱

Why I Built It

It is very easy to spend too much time on screens, even when we actually want to take a break.

I wanted to experiment with whether AI could be used for the opposite purpose: instead of keeping someone on a screen, use AI to give them a reason to leave the screen.

For example, the application can suggest activities such as:

Going for a short walk
Exploring a nearby area
Sitting outside and observing nature
Taking a short outdoor break
Going on a photo walk
Finding something interesting around you

The generated mission is intended to be simple enough that the user can immediately act on it.

Demo

Try TouchGrass AI here:

https://harshitha-hg.github.io/Touchgrass-ai/

Code

The complete source code is available on GitHub:

https://github.com/Harshitha-HG/touchgrass-ai

How I Built It

I built the project using:

HTML
CSS
JavaScript
WebLLM
SmolLM2 open-weight model
GitHub Pages

The application uses WebLLM to run an open-weight AI model directly in the browser.

The model is used to generate personalized outdoor missions based on the user's inputs.

The project also includes a fallback mechanism so that the application can still provide a useful outdoor mission on devices where local AI inference has limitations.

How Open-Source AI Is Used

The AI is not just added as a chatbot.

The open-weight model is part of the core functionality of the project because it generates the outdoor mission.

The project uses an open-weight SmolLM2 model through WebLLM, allowing inference to happen in the browser rather than requiring a traditional cloud AI API for the main generation process.

How It Gets People Outside

The main idea behind TouchGrass AI is:

Short interaction → Get a mission → Put the phone away → Go outside.

Instead of creating another application that encourages users to continuously interact with their screens, TouchGrass AI tries to make the screen interaction as short as possible.

The output is an activity that can be completed away from the device.

Why Open Innovation Matters

Open innovation makes it possible for developers to understand, modify, and improve the technology they use.

With open-source AI and open-weight models, developers can experiment with different models, change prompts, build new applications, and learn from the underlying technology.

For a project like TouchGrass AI, this also makes experimentation easier. Someone could fork the project and turn it into:

A bird-watching assistant
A running route planner
A gardening assistant
A nature exploration tool
A local photography challenge generator

The community can take the basic idea and build something completely different from it.

What I Learned

This project helped me understand how open-weight AI models can be integrated directly into a web application.

I also learned that an AI project does not have to be complicated to be useful.

The interesting part of TouchGrass AI is not simply generating text with AI. The purpose is to use AI to encourage an activity that happens outside the screen.

Final Thought

AI is usually associated with keeping us connected to our devices.

With TouchGrass AI, I wanted to try something different:

Use AI to help you put the phone down. 🌿

TouchGrass AI: An Open-Source AI Mission Planner That Gets You Outside 🌿

Harshitha H G — Sun, 11 Oct 2026 06:42:26 +0000

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass.

🌿 What I Built

Most productivity apps ask us to spend even more time looking at a screen.

I built TouchGrass AI, an outdoor mission planner designed to do the opposite.

You tell it:

⏱️ How much time you have
🚶 What kind of activity you want
⚡ Your current energy level

TouchGrass AI creates a simple outdoor mission with a step-by-step plan and a phone-down challenge.

The goal is simple: use the screen for a few seconds, get your mission, put the phone away, and go outside.

🌎 How It Gets People Outside

Instead of giving users another feed, tracker, or endless list of activities, TouchGrass AI gives them one practical mission.

For example:

Take a 30-minute walk, explore your surroundings, keep your phone in your pocket, and notice three things you normally miss.

The generated mission is designed around the user's available time, activity preference, and energy level.

The screen is meant to be the shortest part of the experience.

🚀 Demo

🌐 Live Demo:

https://harshitha-hg.github.io/Touchgrass-ai/

Try selecting different time, activity, and energy combinations and generate an outdoor mission.

💻 Code

🔗 GitHub Repository:

https://github.com/Harshitha-HG/touchgrass-ai

The project is completely public so anyone can inspect, fork, modify, and improve it.

🛠️ How I Built It

TouchGrass AI is built with:

HTML
CSS
JavaScript
WebLLM
SmolLM2 open-weight model
GitHub Pages

The AI model runs through WebLLM directly in the browser rather than sending every request to a closed AI API.

This makes the open model an important part of how the project works, rather than simply using AI as an add-on.

I also added a lightweight fallback so the outdoor-planning experience remains usable when local AI inference cannot return a response on a particular device.

🔓 Why Open Innovation Matters

For this project, open AI makes experimentation much more accessible.

With an open-weight model and browser-based inference, developers can inspect the project, experiment with the model, change the prompts, and build their own version without depending entirely on a closed API.

It also creates an interesting possibility for privacy-focused applications: the long-term goal is to make more of the experience run locally on the user's device rather than constantly sending personal interactions to a remote service.

Most importantly, open innovation means this small idea doesn't have to remain my idea. Someone can fork TouchGrass AI, replace the model, improve the missions, add local languages, add weather information, or turn it into a completely different outdoor experience.

🌱 What I Learned

The biggest lesson was that an AI project doesn't have to keep people staring at AI.

AI can be the small bridge between "I don't know what to do" and "I'm outside doing it."

That is the idea behind TouchGrass AI.

Use the screen to get the mission. Then touch grass. 🌿