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🌱 GO. β€” An AI That Wants You to Stop Using It | Touch Grass Challenge

A developer built GO., a small open-source web app that uses AI to generate short offline missions β€” choosing a vibe, duration, company and place β€” then starts a countdown telling users to put their phone away. The project is built with HTML, CSS and JavaScript and is designed around local inference via Ollama and open-weight models rather than a proprietary AI API. It was submitted to the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass category.

by read2 min views3 publishedOct 7, 2026

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass GO. β€” AI for Leaving the Screen is a small web app built around a simple idea:

Ask AI. Then leave.

Most AI tools are designed to keep us on screens longer. GO. tries to do the opposite.

The user chooses a vibe, duration, company, and place, and GO. generates a small offline mission designed to get them away from their device and into the real world.

Examples include:

After generating a mission, GO. starts a short countdown and tells the user to put the phone away.

The app is designed for students, people who spend too much time online, and anyone who wants a simple reason to step outside, move, notice their surroundings, or connect with other people.

The goal isn't to replace real life with AI.

The goal is to use AI for a few seconds so you can leave it behind.

🌱 Live Demo:

https://shikharahirwar489-ui.github.io/-GO.-AI-for-Leaving-the-Screen/ πŸ’» GitHub Repository:

https://github.com/shikharahirwar489-ui/-GO.-AI-for-Leaving-the-Screen.git The project is built with a simple frontend so that it is easy for other developers to understand, modify, and contribute to.

GO. is built with HTML, CSS, and JavaScript on the frontend.

The project is designed around local/open AI rather than depending on a proprietary AI API.

The planned architecture is:

Browser β†’ Local Backend β†’ Ollama β†’ Open-Weight Model β†’ Offline Mission

The AI receives structured information such as:

It then generates a short, practical mission that encourages the user to stop using their device.

The frontend also includes:

The important design decision is that AI is only the starting point. The experience intentionally ends by encouraging the user to stop interacting with the application.

Open innovation makes an idea like GO. much more interesting because the AI doesn't have to live inside a closed ecosystem.

With open-weight models and local inference, the mission-generation system can potentially run directly on the user's own computer.

That means developers can:

It also fits the philosophy of the project.

The AI should be a tool, not another platform trying to capture the user's attention.

Open AI ecosystems make it possible to experiment with that idea while keeping the project transparent and hackable.

I used AI-assisted development while building GO. to help design the application structure, frontend logic, UI, mission-generation system, and project documentation.

I have not included a DevRelay agent session link because I don't want to claim a session that isn't actually available.

Hacktoberfest Open-Source AI Challenge β€” Week 1: Touch Grass

This project is primarily entering the Touch Grass challenge category.

The project focuses directly on the challenge's idea of using open-source/open-weight AI to encourage people to spend less time on screens and more time in the physical world.

We keep asking:

"What can AI help us do online?"

GO. asks a different question:

"What can AI help us do offline?"

Ask AI.

Get your mission.

Put the phone away.

🌱

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