Gail Axelrod, Author at Jellyfish - Page 7 of 16

NEW: See AI's real impact on engineering teams with the industry's largest ongoing benchmark study. Explore the trends

ai coding pull request size

AI Coding

Better Code, or Just Bigger? AI-Assisted Pull Requests Are 18% Larger

Jellyfish AI Impact_Claude Code

AI Coding

Jellyfish Enables AI Impact for Claude Code to Bring Greater Visibility to AI Adoption

Jellyfish_OpenAI_research

AI Coding

Jellyfish and OpenAI Team Up to Measure the Impact of AI Coding Tools

7-KPIs

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

engineering managers leading through acquisition

Frameworks

Team Productivity: An Engineering Manager’s Guide to Measuring Outcomes

SEMR25-3 Takeaways for Engineering Managers

AI Coding Best Practices

3 Takeaways for Engineering Managers from Jellyfish’s State of Engineering Management Report

Jellyfish AI Impact Framework

AI Coding Frameworks

The Jellyfish AI Impact Framework: A Practical Guide for R&D Leaders Navigating the Hybrid AI-Human Era

Jellyfish State of Engineering Management 2025

AI Coding Leadership

Engineering in the Age of AI: What the 2025 State of Engineering Management Report Reveals

blog-Jellyfish and Amazon

AI Coding

Jellyfish Releases Integration to Measure AI Impact for Amazon Q Developer