What I Built Verdant is a quest master that runs on your own laptop and wants you to close it. An open-weight AI writes you outdoor quests based on the season and the weather, like a 3 km foliage stroll with a leaf to photograph. You go outside and do it. Back home, Verdant checks your GPS track and
What I Built Verdant is a quest master that runs on your own laptop and wants you to close it. An open-weight AI writes you outdoor quests based on the season and the weather, like a 3 km foliage stroll with a leaf to photograph. You go outside and do it. Back home, Verdant checks your GPS track and your photo, and if both pass, it issues a signed voucher. A sponsor, such as a running shop or an eco brand, pastes the voucher into the Verdant Sponsor Portal, sees at once that it’s genuine, and knows which reward to ship: a sticker pack, a finisher medal, or a swag box. It’s for people who need a small push to start: new walkers, beginner runners, and anyone whose daily steps are mostly to the fridge. The screen is only for getting a quest and claiming the reward, and the real experience happens outside. Demo A note on testing: I wasn’t able to record a real outdoor walk before the deadline, so the route in this demo is a simulated GPS track generated with a small script. It tests the verification logic, but it isn’t a real outdoor test. The Sponsor Portal ran locally for these screenshots, and the repo includes a render.yaml for deploying it. Taking Verdant outside is my next step. The quests Gemma generated / verdant verdant View on GitHub It’s one Python file for the quest master and one for the sponsor portal. Neither needs any extra packages, so a beginner can read all of it in ten minutes. How I Built It Verdant has four parts, and only two of them need AI. Quests (Gemma, running locally). Verdant asks Gemma 3 through Ollama for quests in JSON, based on the user’s level, the season and the weather. If the model isn’t available, built-in quests take over, so the tool still works on a trail. Only a hash of the track goes into the voucher, so sponsors never see where you walked. What went wrong along the way: Gemma wrote long paragraphs for the photo instruction at first, so the photo check kept answering “No”. I fixed it by shortening the subject before sending it to the model and by asking Gemma for short photo subjects in the first place. I also hit install problems and a server that wouldn’t start. [Add one or two more in your own words.] Why Does Open Innovation Matter? Limitations: Outdoor testing was limited to a simulated route. Vouchers use a shared secret in this prototype, so public-key signatures are the next step. The “already redeemed” list lives in memory and resets when the server restarts, so a real version needs a database. The sponsors in the code are placeholders.
Key Takeaways #
- •What I Built Verdant is a quest master that runs on your own laptop and wants you to close it. An open-weight AI writes you outdoor quests based on the season and the weather, like a 3 km foliage stroll with a leaf to photograph
- •This story was reported by Dev.to , covering developments in thedev space.
- •AI advancements continue to reshape industries — read the full article on Dev.to for complete coverage.
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