Senior Technical Business Analyst at a tech vendor with 10,001+ employees
Real User
Top 20
Oct 18, 2026
The biggest issue I have with Jellyfish is how it attributes work done by engineers as AI-assisted work. It is really making a guess based on whether there are AI signals the day that they do appear, which is not really a great determination in my opinion. The dashboard provides strong visibility, but it can sometimes feel a bit complex or dense when trying to drill down quickly into QA-specific insights. More customizable or role-focused views would make it easier to surface what is most relevant without extra filtering.
I find the custom dashboarding challenging, although I acknowledge that the team is moving in the right direction. Sometimes I need to engage support to fix data pulls from GitHub and Jira, but they resolve these issues very quickly. More customizable or role-focused views will make it easier to surface what is most relevant without extra filtering.
To improve Jellyfish, I suggest adding the view on the return on investment, making it easy to identify waste within our processes. It is a great way to see engineering overall results and measure. Sometimes understanding the metrics is not simple. I also believe they should keep improving the user interface. The individual developer metrics are not very useful and make the interface feel cluttered, which is an improvement that Jellyfish needs.
Software Development Analytics involves tools and techniques to track and analyze software development data. These analytics offer insights into performance, efficiency, and quality, helping teams make informed decisions.
Within the software industry, analytics tools are essential for providing visibility into development processes. They play a critical role in identifying bottlenecks and ensuring quality management, helping teams optimize their workflows. Companies use these insights...
The biggest issue I have with Jellyfish is how it attributes work done by engineers as AI-assisted work. It is really making a guess based on whether there are AI signals the day that they do appear, which is not really a great determination in my opinion. The dashboard provides strong visibility, but it can sometimes feel a bit complex or dense when trying to drill down quickly into QA-specific insights. More customizable or role-focused views would make it easier to surface what is most relevant without extra filtering.
I find the custom dashboarding challenging, although I acknowledge that the team is moving in the right direction. Sometimes I need to engage support to fix data pulls from GitHub and Jira, but they resolve these issues very quickly. More customizable or role-focused views will make it easier to surface what is most relevant without extra filtering.
To improve Jellyfish, I suggest adding the view on the return on investment, making it easy to identify waste within our processes. It is a great way to see engineering overall results and measure. Sometimes understanding the metrics is not simple. I also believe they should keep improving the user interface. The individual developer metrics are not very useful and make the interface feel cluttered, which is an improvement that Jellyfish needs.