This is a note from our game dev journey.
Every indie game team knows the pain (or will know it): you wrap up a big playtest or team review, and suddenly there’s a pile of feedback—emails, Word docs, random tables, Slack posts. You need these comments turned into actionable, trackable Jira bugs, but the thought of slogging through every note to write tickets by hand makes you want to run screaming into the nearest impossible boss fight.
Recently, I found a workflow with ChatGPT that turned this pain point into a quick, almost enjoyable process. Here’s how it works—and why it’s a time-saver for small teams.
The Problem: Feedback Chaos
After a major playtest of our project, our team had a Word document full of review notes. It was organized, kind of: a table with “Reporter”, “Area”, and “Notes”. Multiple people flagged the same problem in different words. Some notes were short (“UI weird”), others were rambling. What we needed was:
- Clear, grouped bugs by game area and problem.
- One ticket per unique issue, even if multiple people flagged it.
- Summaries and descriptions suitable for Jira.
- Contributor emails captured for follow-up.
Step 1: Ask ChatGPT to Summarize and Group
Instead of copy-pasting each row into Jira and guessing what to combine, I uploaded the Word doc straight into ChatGPT (the advanced version that supports file uploads).
Here’s the prompt I used:
“The table is organised into a reporter, which contains the name and Jira username of the person’s entries, the area that represents an area of the game, and notes for that area. Some notes may describe the same problem. Try your best to understand those. Create a summary version grouped by per area / per problem in a table form in a way that each should contain a title and a description if applicable. If an entry does not contain enough information, only include a title. If an entry is indicative of multiple issues, break that down into multiple headings. The ultimate goal is to generate a Jira import CSV in the end, but not yet. I’d like to review it first with you.”
ChatGPT responded with a grouped, readable table summarizing all the issues, merging duplicates, and breaking out multi-part notes. It was honestly better than what I would have done by hand—and ten times faster.
Step 2: Refine and Approve
I reviewed the summary in the chat window, asked ChatGPT to tweak a few things (merge some headings, clarify wording). This step made sure the tickets would actually be actionable and clear for the rest of the team.
Step 3: Convert to Jira CSV
Once the summary looked good, I gave ChatGPT a second prompt:
“All of these need to be Bug types, normal priority, project key is PP, do not assign it to anyone yet. Update the description to start with Project Q, Review1, include any person’s email whose feedback it was made from. The subject should include the area and title.”
In seconds, ChatGPT generated a Jira-compatible CSV (with columns like Project, Issue Type, Summary, Description, Priority, Assignee), filled in with all the grouped bugs and feedback emails. I downloaded the file and imported it straight into Jira—no manual typing, no copy-paste errors, no ticket duplicates.
Step 4: Import a CSV in the New Jira Cloud UI
If you’ve used Jira Cloud lately, you might have noticed that the navigation and layout have changed—and, annoyingly, the official documentation doesn’t quite keep up. Here’s how to get your CSV file into Jira (as of mid-2025):
- Go to your project in Jira Cloud.
- In the left sidebar, select “All work” (not the old “Issues” link).
- In the issue list view, look to the top right for a
...(three dots) menu. - Click it and select “Import work items from CSV”.
- Jira will open a wizard that lets you:
- Upload your CSV file
- Map fields from your CSV to Jira fields (e.g., Summary, Description, Priority, etc.)
- Validate the import (Jira will flag any missing or mismatched data)
- Complete the operation
- Once the import is done, Jira provides a link so you can instantly see all the tickets it just created.
No more digging through settings or outdated documentation—just a streamlined wizard right where you need it.
Why This Workflow Is a Game-Changer for Small Teams
- Super Fast: What used to take me a few hours was done in under 20 minutes, including review.
- Higher Quality Tickets: Duplicates were merged, descriptions were clear, and everyone’s feedback was credited for follow-up.
- Less Admin Pain: More time for design/code, less time wrangling spreadsheets and tickets.
- Scalable: Works for one doc or a dozen.
Tips for Indie Teams Trying This
- Organize your notes: Even a messy table is better than scattered messages.
- Be clear in your ChatGPT prompts: Tell it how you want things grouped, and what Jira fields you need.
- Review the summary: AI isn’t perfect—sometimes context matters.
- Export and import: The CSV ChatGPT gives can go right into Jira via the built-in importer.
- Iterate!: If your workflow changes, tweak your prompts and repeat.
Would I Use This Again?
Absolutely—this workflow took what used to be a drag and made it into something nearly enjoyable. If your indie team dreads the “turn feedback into Jira tickets” grind, give this a try. Your sanity (and your schedule) will thank you.
