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

What I Built

GET OUT is a local AI app designed to help people spend less time on their screens and more time in the real world.

The idea is simple:

The best AI session is the shortest session.

Instead of giving users a chatbot, recommendations, or an endless feed, GET OUT asks for two things:

  • ⏱️ How much time do you have?
  • ⚡ What is your energy level?

It then uses local AI to generate exactly ONE real-world mission.

For example:

You have 30 minutes. Explore a familiar route you normally ignore. Find one unusual detail you've never noticed before and investigate it for a few minutes.

PHONE DOWN. GO.

Then the app gets out of the way.

The flow is:

 text USER ↓ 2 SIMPLE CHOICES ↓ LOCAL AI ↓ ONE MISSION ↓ PHONE DOWN ↓ GO OUTSIDE GET OUT is built for people who feel like they are spending too much time on their phone or computer and need a small push to step away. The goal isn't to maximize AI engagement. The goal is to make the user leave the app. Demo <!-- Add your demo video or deployed link here --> Demo: [Add your demo link here] The demo shows the complete flow from choosing time and energy to receiving a single AI-generated real-world mission. Code <!-- Add your GitHub repository link here --> GitHub: [Add your GitHub repository link here] The project is open source and designed to run locally. How I Built It GET OUT uses open-weight AI with local inference. Tech Stack Qwen3 4B — open-weight language model Ollama — local AI inference FastAPI — backend Python — application logic HTML/CSS/JavaScript — frontend pytest — automated testing The architecture is intentionally simple: Web UI ↓ FastAPI ↓ Mission Generator ↓ Ollama ↓ Qwen3 4B ↓ Safety Validation ↓ Mission Quality Validation ↓ ONE MISSION The model receives the user's available time and energy level and generates a mission designed around those constraints. The application also validates the generated mission before showing it to the user. I intentionally avoided building another AI chatbot. There is no endless conversation, recommendation feed, or AI companion. AI generates the mission. Then the user leaves the screen. Why Does Open Innovation Matter? GET OUT is built around local, open-weight AI because the project does not need a large cloud AI service to work. Using open AI makes it possible to: Run the model locally Avoid sending user context to a third-party AI API Experiment with the model and prompts directly Run without a paid inference API Keep the project accessible to developers who want to modify it Swap models and experiment with different open-weight models More importantly, open innovation allowed me to experiment with a different idea of what an AI product should optimize for. Most digital products try to maximize: engagement → more sessions → more screen time GET OUT tries to optimize for: less AI usage → more real-world time The AI is not the destination. It is the push toward the destination. My Agent Session <!-- Optional: Add your DevRelay agent session here --> Prize Categories Open-Source AI <!-- Team Submissions: No teamates <!-- Thanks for participating! -->