AI Coding
New Research from Harvard & Jellyfish: AI Is Making Developers Faster. So Where’s the Business Impact?
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Featured Resources
AI Coding Frameworks
AI Coding Frameworks
The Jellyfish AI Impact Framework: A Practical Guide for R&D Leaders Navigating the Hybrid AI-Human Era
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AI Coding
2025 AI Metrics in Review: What 12 Months of Data Tell Us About Adoption and Impact
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AI Coding
What Data from 20 Million Pull Requests Reveal About AI Transformation
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AI Coding
Early Adopters are Having Success with Autonomous Agents. Here’s How.
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AI Coding
AI Coding Tools Not Paying Off? Your Code Architecture Might Be to Blame.
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AI Coding
How Prevalent is Autonomous Agent Use? Here’s What the Data Says.
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AI Coding
Does AI Assistance Mean Engineers Are Doing Less Coding Work? Maybe Not.
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![DORA 2025: AI as an Amplifier [Infographic]](https://jellyfish.co/wp-content/uploads/2025/09/blog-DORA-report-1024x561.webp)
AI Coding
DORA 2025: AI as an Amplifier [Infographic]
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AI Coding
The Real Impact of AI Code Review Agents: What We Learned from 1,000 Reviews
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AI Coding
Better Code, or Just Bigger? AI-Assisted Pull Requests Are 18% Larger
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AI Coding
Jellyfish and OpenAI Team Up to Measure the Impact of AI Coding Tools
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AI Coding
What New Data Tells Us About the Rise of Agentic AI in Engineering Workflows
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AI Coding
The Jellyfish AI Impact Framework: A Practical Guide for R&D Leaders Navigating the Hybrid AI-Human Era
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2025 State of Engineering Management Report Old
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AI Coding
AI Use in Engineering Up 260% YoY, According to Jellyfish Analysis of 2M+ PRs
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AI Coding Impact: Practical Measurement Approaches
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Quantifying AI Coding Impact: A deep dive into vendor native data
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AI Coding
With Copilot, Study Finds Engineers Get 15% More Capacity without Additional Headcount
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