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Talking about value πŸ’Ž A journey to faster backlog refinements (Codegeist unleashed)

Tired of extended backlog refinements? Do you find yourselves delving into topics that could have been resolved prior to meetings? Is your acceptance criteria causing confusion among the development team?

In this article, our focus is on addressing these challenges and introducing an AI-powered assistant designed to enhance your backlog refinement process, potentially making it more efficient and enabling valuable collaboration.

 

 

 

Extended backlog refinements

Drawing from our firsthand experience, backlog refinements can pose significant challenges, often stretching over time. As a product owner, communicating everything comprehensively can be a daunting task. This may be due to being new to the role, dealing with stories that were shelved as loose ideas in the backlog and have now gained sudden importance, or even just having a bad day where writing acceptance criteria becomes challenging.

Hence, we crafted a solution to address this issue. With RefineMeFaster, our AI-driven Jira app, we aim to tackle this task

 

refinemefaster_b.png

 

Our app streamlines the process of improving user stories in Jira. The app analyses  issue data like type, summary and description and tries to find unclear sentences and gives you hints how to improve them. Those suggestions can be accepted, rejected or marked as resolved.

 

rmf_edit-result.png

The field edit dialog with improvement suggestions

 

How does it work?

The "Improvements" field is simply another custom field. You can create it through the familiar admin section called "Custom fields" and add it to the screens where it seems appropriate.

 

image.png

Create the Improvements field as every other custom field

 

Once you've included this field in a screen, go to an issue and open the custom field dialog to initiate the improvement process. At this stage, review and prepare the data for analysis, ensuring the removal of sensitive information.

AI-powered analysis is employed to generate improvement suggestions by examining this data.

The choice to keep suggestions open (indicating they are unresolved but valid) or discard them is entirely up to you. The number of open suggestions will be displayed as a numeric value within the custom field after saving, aiding you in monitoring ongoing improvements.

You can also mark suggested improvements as resolved if you make changes to the sentences. Furthermore, the open suggestion count supports Jira Query Language operations, such as sorting issues based on the highest number.

 

rmf_issue.png

The color changes in accordance with the open suggestion count

 

In addition, it can be integrated into automation, enabling the triggering of actions or workflows when the number of open suggestions surpasses a predetermined threshold.

 

Codegeist unleashed

The application emerged during Atlassian Codegeist Unleashed 2023, and we had a delightful time combining Jira (Forge) with an AI service (ChatGPT). Although we had some familiarity with Forge, our initial challenge was implementing the AI component.

We began with a relatively straightforward task to establish a proof-of-concept: generating release notes from issue data. To accomplish this, we introduced a custom field that allows the creation of a changelog per issue. We believe that having this field as close as possible to the issue view makes perfect sense, making it an ideal choice for a custom field.

Following the completion of this task, we ventured into the improvements field. This proved to be more intricate, both in terms of user interface and AI integration. We had to employ a more sophisticated prompt to achieve optimal results and conduct extensive pre-processing to enhance performance.

Another crucial concern pertains to transparency and privacy. As a response, we've incorporated an admin page that provides details about the AI services in operation, along with the prompt and data that are transmitted to the AI.

 

rmf_admin-page.png

Find important information about the app and used AI services

 

If you're interested in delving into the technical intricacies, please feel free to explore our Codegeist submission.

 

Wanna try it out? Here's the install link 

 

3 comments

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Paul Pasler
Marketplace Partner
Marketplace Partners provide apps and integrations available on the Atlassian Marketplace that extend the power of Atlassian products.
October 24, 2023

Hi @Kelsey Van Scoy ,

could you please add those hashtags to my article (still not allowed to do so)?

 

codegeist, codegeistunleashed, hackathon

Thanks in advance!

Like β€’ Martin Seibert likes this
Kelsey Van Scoy
Atlassian Team
Atlassian Team members are employees working across the company in a wide variety of roles.
October 24, 2023

Hi Paul,

 

I added the tags. Please reach out to  with any concerns in the future. Thank you!

Like β€’ # people like this
Rustem Shiriiazdanov
Contributor
October 24, 2023

Hi @Paul Pasler ,

the application looks absolutely fantastic! I truly appreciate the way it presents suggestions as a separate field, allowing you the flexibility to consider improvements without feeling pressured to make immediate decisions. I'm really like that approach.

Like β€’ Paul Pasler likes this
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