Task Manager

Break down tasks into subtasks and auto-delegate them using Task-Manager.

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https://www.loom.com/share/3cbe08499bba47d69ad60dd89b76c56c?sid=9bd3a4c4-e68f-4b52-89d7-99dc233844bf

Inspiration

When our team started brainstorming, we explored a range of ideas — but one concept immediately stood out. We noticed how common it is for teams to struggle with assigning tasks, tracking progress, and keeping projects on schedule. We wanted to build something that actually solves that problem — a tool that makes collaboration inside Jira smoother, faster, and more intelligent. That idea became Task-Manager, an AI-driven approach to improving how teams plan and execute their work.

What it does

Task-Manager is an AI-powered extension for Jira that automates task delegation and project summarization. It helps teams break down complex goals into clear, actionable tasks while providing insights that make work more balanced and predictable. Here’s what it does:

  • Estimates the time required for each task
  • Summarizes overall project progress
  • Rates task difficulty to distribute workloads fairly

In essence, it acts as a built-in assistant for teams — helping them stay organized, efficient, and aligned without ever leaving Jira.

How we built it

We developed Task-Manager using Atlassian Forge, Rovo, Jira, Node.js, JavaScript, and Gemini. Each component was integrated to create a seamless workflow that brings automation and intelligence directly into Jira’s interface. Since our entire team was new to the Atlassian ecosystem, we had to learn everything from scratch — from configuring Forge environments to understanding Rovo agents. Through constant iteration and problem-solving, we built a working prototype that demonstrates how AI can elevate productivity in collaborative workspaces.

Challenges we ran into

This project came with no shortage of challenges:

  • Deployment permissions – Deploying our Rovo agent through Forge was one of the toughest technical hurdles. We repeatedly encountered permission and access issues that required detailed debugging.
  • New ecosystem – None of us had prior experience with Jira or Forge, so every step involved learning new frameworks, documentation, and workflows.
  • Defining the real problem – As first-time Jira users, understanding which problems were most worth solving required significant exploration and research.

Despite these challenges, we kept pushing forward and turned our learning curve into an opportunity to innovate.

Accomplishments that we're proud of

We’re proud of how quickly we adapted to an entirely new environment and built something functional within such a short timeframe. We went from zero experience with Jira to creating an integrated AI-driven system that could genuinely help teams operate more efficiently. It’s rewarding to know that what started as a small idea evolved into something that has the potential to make a real impact.

What we learned

Over the course of the hackathon, we learned how complex yet powerful the Atlassian ecosystem is. We gained hands-on experience with Forge, Rovo, and Jira — and learned how these tools can work together to build automation that genuinely improves team collaboration. We also learned how to stay persistent under pressure, communicate effectively, and build across disciplines even when starting from scratch.

What's next for Task-Manager

We see Task-Manager as the foundation for something bigger. Moving forward, we plan to:

  • Implement codebase analysis so the system can better understand project context and dependencies.
  • Enhance the Custom UI to make insights easier to interpret and act on.
  • Train the model on real organizational data to improve the accuracy of time and difficulty predictions.

Our long-term vision is to transform Task-Manager into a fully intelligent AI project management copilot — one that empowers teams to spend less time coordinating and more time creating.

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