Somehow this post was stuck in draft and I couldn't publish it. The following post is what I meant to submit to the Week Two Hacktoberfest Challenge.

What I Built

One Project, Many Stories turns one set of project facts into three editable drafts: a portfolio case study, a hiring summary, and a demo outline.

You supply the problem, your contribution, features, tradeoffs, and outcomes. Gemma shapes the writing for each audience. Source references stay in a separate review view, so copied and downloaded drafts are clean.

For the Side Hustle theme, I’m exploring a tool for developers and freelancers who repeatedly write about their work. It could also support a project storytelling service. Whether people would pay is still a hypothesis—I haven’t validated demand or revenue.

Demo

Try the live app

YouTube demo: https://youtu.be/qKRQhKB3e9s

The walkthrough uses Patchwork, a clearly labeled synthetic project, and shows a real hosted Gemma response. You can load the same sample in the app. Hosted generation requires consent to send the notes to Google; please use synthetic or public information.

The demo outline only uses screen actions you write and confirm. The sample has none confirmed, so the app leaves that outline empty instead of inventing a walkthrough.

Code

npm ci
npm run dev

The application source is MIT licensed. Model and dependency licenses are separate.

How I Built It

The app uses React 19, TypeScript, and Vite 7, with Vercel functions calling Google’s Gemini REST API. The server keeps the API key and uses the open-weight model gemma-4-26b-a4b-it.

Gemma writes structured, audience-specific drafts with source IDs. The app checks the response format, source references, summary length, and links to confirmed demo actions. There’s no mock fallback if generation fails.

An early version mostly rearranged the input passages. The results felt too much like the form, so I changed it to write distinct drafts while keeping the original notes available for review.

What’s tested: the latest completed checks passed 36 unit tests, 19 Chrome browser tests, and the production build. Automated generation tests use mocks. Separately, a real synthetic request completed the deployed browser → backend → Google → output flow.

What still needs work: that real response omitted a qualification about testing and measured revenue from the hiring summary. Source IDs don’t prove factual accuracy, so every draft needs human review. Local Ollama inference and generated demo narration with confirmed actions have not completed real-model testing.

Drafts are editable, and changed facts mark existing drafts stale. Evidence links aren’t fetched. Project content stays in browser memory; there are no accounts or database.

Why Does Open Innovation Matter?

I want developers to be able to inspect and adapt the model integration, prompts, and validation rules.

Gemma provides an open-weight foundation, and the app also includes a local Ollama adapter. That offers a path toward running inference under your own control, although that local path is still unverified.

The working demo sends notes to Google. I’m not claiming offline privacy, lower costs, or better quality than a closed model. The value of openness here is the ability to experiment with the writing workflow and inference setup as the project develops.

Which would help you most: the case study, hiring summary, or demo outline?