AI Coding
AI Coding
AI Coding
Jellyfish and OpenAI Team Up to Measure the Impact of AI Coding Tools
AI Coding
Jellyfish AI Impact Now Supports Windsurf to Change How AI and Humans Work Together
AI Coding
What New Data Tells Us About the Rise of Agentic AI in Engineering Workflows
Best Practices
How to Measure Developer Productivity: Best Practices and Key Metrics to Track
Frameworks
Team Productivity: An Engineering Manager’s Guide to Measuring Outcomes
AI Coding Best Practices
3 Takeaways for Engineering Managers from Jellyfish’s State of Engineering Management Report
AI Coding Frameworks
The Jellyfish AI Impact Framework: A Practical Guide for R&D Leaders Navigating the Hybrid AI-Human Era
AI Coding Leadership
Engineering in the Age of AI: What the 2025 State of Engineering Management Report Reveals
AI Coding
Jellyfish Releases Integration to Measure AI Impact for Amazon Q Developer
Best Practices Team Health
Introducing Team Pulse: A Command Center for Engineering Managers
Leadership Strategy & Planning
Setting the Standard for 12 Quarters: Jellyfish Named Consistent Leader in G2’s Software Development Analytics Tools Grid
AI Coding
AI Use in Engineering Up 260% YoY, According to Jellyfish Analysis of 2M+ PRs
AI Coding
Building a Growth Mindset in the Era of AI with Tripleseat’s CTO Pat Jenakanandhini
AI Coding
Jellyfish Measures AI Impact Everywhere You Work – Now with Support for Copilot, Cursor, Google Gemini Code Assist & Sourcegraph
Best Practices Delivery Management
5 Red Flags to Watch for When Evaluating Developer Productivity Tools
AI Coding
Making Magic with Jellyfish’s MCP: How Ably Moves Beyond Data Retrieval to Unlock Real Analysis and Insights
AI Coding