AI Coding
AI Coding
Best Practices Engineering Investment and Business Alignment
How to Align Product and Engineering to Drive Better Planning in 2026
AI Coding Best Practices
Jellyfish Deep Dive: Measuring the Adoption and Impact of AI Coding Tools
Best Practices DevFinOps Strategy & Planning
How to Use Real Data to Build Your 2026 R&D Headcount Planning Model
Delivery Management Engineering and Product Operations Strategy & Planning
Jellyfish Now Brings Developer Productivity and AI Insights to Azure DevOps Customers
AI Coding
AI Coding Tools Not Paying Off? Your Code Architecture Might Be to Blame.
AI Coding
How Prevalent is Autonomous Agent Use? Here’s What the Data Says.
AI Coding Delivery Management
Jellyfish and Sonar Team Up to Provide Better Visibility into Code Quality, Coverage and Vulnerability Metrics
Best Practices DevFinOps
Why Successful R&D Budget Planning for 2026 Means Closer Alignment Between Finance & Engineering
AI Coding Best Practices
Cracking the AI Productivity Paradox: A Framework for Real Impact
AI Coding
Does AI Assistance Mean Engineers Are Doing Less Coding Work? Maybe Not.
AI Coding Leadership
DORA 2025: AI as an Amplifier [Infographic]
AI Coding Best Practices Leadership
Bringing AI to the Boardroom: 6 Slides for Engineering Leaders [TEMPLATE]
Best Practices Leadership Team Health
Leading Change Post-Acquisition: A Guide for Engineering Managers
AI Coding
Comparing the Impact of AI Tools with Jellyfish’s Multi Tool Comparison
AI Coding
Now Available: Install the Jellyfish MCP via Claude Desktop
In the Bloom
Three Years and Counting: Jellyfish Leads the Way in G2’s Software Development Analytics Tools Grid
AI Coding