As AI is embedded in every corner of software development, engineering leaders face a new challenge: proving that these tools actually deliver value. From autonomous agents to code assistants, the landscape is evolving faster than most teams can measure. Leaders are left asking: What’s working, what’s not, and how can we know for sure?
That’s where Jellyfish’s AI Impact comes in. AI Impact quantifies the value of AI-powered developer tools across the software development lifecycle (SDLC). It unifies adoption, usage, spend, and outcome data across AI assistants, agents, and other AI-augmented workflows, enabling engineering leaders to:
- Measure AI ROI
- Optimize investments
- Scale adoption
- Guide AI strategy with confidence
Now we’re taking AI Impact to the next level with new capabilities that bring together system data, developer sentiment, and guided insights – giving leaders a clearer, faster, and more complete picture of how AI is transforming their organizations and the overall SDLC.
Autonomous Agent Insights
Autonomous Agent Insights
Autonomous agents are reshaping how work gets done in engineering teams, from code generation to PR submission. Our new Autonomous Agent Insights helps leaders track code generated by agents, agent PRs, AI contribution ratios and merge rates to better understand agent effectiveness.
Jellyfish now supports insights across all major agents including Devin, Factory, Codegen, Claude Agent, Copilot Agent, and Google Jules so teams can understand how these tools are contributing to delivery, quality and throughput.
With deeper, more granular visibility, engineering leaders can finally measure the real impact of agentic AI in their workflows.
Developer Insights
Developer Insights
AI’s impact isn’t just about system data – it’s about how developers experience it. To better understand developer sentiment specifically related to AI, Jellyfish now directly integrates pre-built developer experience surveys into AI Impact so teams can collect real-time sentiment data on AI enablement, productivity, suggestion quality, innovation capacity and more.
This feedback fills a critical gap in understanding how developers feel about using AI tools, and how that sentiment correlates with adoption and output. It’s also a powerful lever during experimentation, offering directional feedback even before large-scale adoption and impact data is available.
Executive Reporting Workflows
Executive Reporting Workflows
As AI tooling data continues to expand, leaders need faster ways to make sense of it. Our new Executive Reporting Workflows guide engineering leaders through key takeaways based on their reporting needs – whether that’s demonstrating ROI, assessing adoption, or planning next-phase investments.
This workflow-driven experience helps engineering leaders go from data to insight in minutes, providing executive- and board-level clarity as the volume of data and complexity surrounding AI only continues to increase.
Deeper AI Impact Telemetry
Deeper AI Impact Telemetry
Finally, AI Impact data is now available directly in Jellyfish’s Metrics Explorer so teams can combine AI usage insights with engineering performance metrics to ask new kinds of questions including:
- How is AI affecting productivity at the individual or team level?
- How is AI changing the shape of our workflows or roles?
- Which parts of our codebase are seeing the most AI-driven change?
- …and so much more
This deeper, more custom and connected view helps teams understand not only what’s happening, but why.
Why It Matters
Why It Matters
AI adoption is accelerating, but the pressure on leaders to demonstrate value is intensifying just as quickly. Jellyfish is continuing to innovate to meet and anticipate the needs of the market, including broader coverage of tooling – now covering all major coding assistants, code review agents, and autonomous agents – and enhancing those insights with developer sentiment to better understand AI’s impact on developer workflows.
Jellyfish AI Impact helps engineering leaders cut through the noise with unified systems data, developer sentiment, and business outcomes all in one place. The result is faster insights, smarter investment decisions, and stronger confidence in your AI strategy.
Ready to See AI Impact in Action?
Explore all of AI Impact’s new functionality and see how your team can measure the value of AI.
Request a Jellyfish demo.About the author
Lauren is Senior Product Marketing Director at Jellyfish where she works closely with the product team to bring software engineering intelligence solutions to market. Prior to Jellyfish, Lauren served as Director of Product Marketing at Pluralsight.
