What Now?: because every long email hides a to-do list

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built What Now? 🤔, a small AI tool for the friend who gets a long email, announcement, or message and thinks:

"Okay... but what am I actually supposed to do?"

What Now? turns messy text into a clear overview of:

• 📝 Summary — What is this about?
• ✅ Action Items — What needs to be done?
• 📅 Deadlines — When does it need to be done?
• 👥 People / Organizations — Who is involved?
• ⚠️ Important Information — What shouldn't be missed?

The idea was to build something simple and genuinely useful: instead of reading through a wall of text trying to figure out what matters, you can paste it into What Now? and immediately see what needs your attention.

Demo

The app currently runs locally using Gradio.

Here is an example of What Now? turning a messy message into structured, actionable information:

Input:

Hi Ananya, please submit the revised assignment to Prof. Mehta by Monday. Make sure you attach the updated bibliography and send a confirmation to Prof. Mehta once you've submitted it. Also, please fill out the feedback form from the ISI Mathematics Department before Friday. If you have any questions, contact Rahul from the Academic Office.

Output:

• 📝 Summary: Ananya needs to submit a revised assignment and complete a feedback form.
• ✅ Action Items: Submit the assignment, attach the bibliography, send confirmation, and complete the feedback form.
• 📅 Deadlines: Monday and Friday.
• 👥 People / Organizations: Prof. Mehta, ISI Mathematics Department, Rahul, Academic Office.
• ⚠️ Important Information: The assignment needs the updated bibliography and a confirmation must be sent after submission.

Run it yourself:

https://github.com/theikosB/what-now

Code

The complete source code is available on GitHub:

https://github.com/theikosB/what-now

The project is intentionally small and easy to run locally. The main application is built in Python using Gradio, with Gemma 4 handling the text analysis.

How I Built It

The project is built with Python, Gradio, and the Google GenAI Python SDK.

At the core of What Now? is Gemma 4 (gemma-4-26b-a4b-it), an open-weight model. I prompt the model to analyze the user's text and return a structured JSON response containing the summary, action items, deadlines, people or organizations, and important information.

The basic flow is:

text
Email / Notice / Message
          ↓
        Gradio
          ↓
       Gemma 4
          ↓
    Structured JSON
          ↓
  Clear actionable output

## Why Does Open Innovation Matter?
Open innovation made it possible for me to build this project around an **open-weight AI model** rather than treating the AI as a completely closed black box.

Using Gemma 4 meant I could experiment with the model directly and build a small application around it without needing to develop an AI model myself.

For a weekend project like What Now?, having access to capable open models makes it much easier for individual developers to experiment, build useful tools, and learn by actually working with the technology.

## Prize Categories
### Best Use of Gemma

I used **Gemma 4 (`gemma-4-26b-a4b-it`)**, an open-weight model, as the core AI model behind What Now?.

The model analyzes unstructured emails, notices, and messages and returns structured information that the application turns into summaries, action items, deadlines, people/organizations, and important information.

### Credits

Thanks to the Gemma team for making Gemma available as an open-weight model.

AI tools assisted with the implementation and preparation of this write-up.

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