Inspiration

This inspired me to build Issue Buddy, a simple yet powerful Forge app that uses AI to summarize Jira issues and estimate their complexity. The idea was to create something genuinely helpful for developers and project managers who want to quickly understand what a task involves without reading a wall of text.

🔧 How I Built It

I used Atlassian Forge with Custom UI to embed the app directly in the Jira issue panel. The frontend is a minimal React app that interacts with Forge’s backend resolvers. I connected the app with Open AI’s GPT-3.5-turbo API to generate TL;DR summaries and complexity estimations (Easy, Medium, Hard) based on the issue description. I used Jira’s REST API to fetch issue data dynamically and securely through Forge’s backend capabilities.

🧠 What I Learned How to build and deploy Forge apps inside Jira Cloud. How to securely make external API calls using Forge’s resolver and api.fetch. How to process rich text content from Jira’s API and convert it into useful prompts for AI. How small AI-powered features can make a big difference in user productivity.

⚠️ Challenges Faced

Jira descriptions are stored in a rich-text nested JSON format, which required careful parsing before feeding into the AI model. Forge has strict external fetch policies and limits — configuring permissions correctly and keeping latency low was tricky. As a solo participant, balancing between design, logic, and testing all features on my own required good time management. Rate limiting with Open AI needed handling for reliability in real-world usage we built it.

What's next for Issue Buddy 💡 Final Thoughts

Issue Buddy is my take on making developer workflows more efficient. It’s fast, lightweight, and shows the power of combining Atlassian Forge with generative AI. I’m excited about its potential to help teams save time, reduce miscommunication, and onboard new developers faster.

Whether it’s a solo sprint or a team effort — with Issue Buddy, every issue becomes instantly easier to tackle.

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