Jellyfish

Loving the shoutout to our Jellyfish AI Engineering Trends benchmark on The AI Daily Brief today – thanks Nathaniel Whittemore! Thrilled to hear that our analyses are helping folks make sense of their progress on AI transformation 🙂

In this week's episode of The AI Daily Brief: Artificial Intelligence News and Analysis, Nathaniel Whittemore introduces Maturity Maps, a new framework for benchmarking AI and agent adoption across six key dimensions - from deployment depth to systems integration to people and governance: https://lnkd.in/gMQW-MQW This benchmarking framework referenced is based on industry research and surveys, including the Jellyfish AI Engineering Trends report. See the latest data from February here: https://lnkd.in/gFAyfhw2

Jellyfish is heading to HumanX next week — will we see you there? Stop by our booth (#1726, right next to the Agentic AI stage ) to catch all the AI action. We’re also co-hosting an executive Happy Hour on Monday (April 6) with Rootly, CloudZero, MongoDB, Vanta, and groundcover. If you're an R&D leader looking to make meaningful connections before the conference craziness, RSVP here: https://luma.com/n22qf90w

Jellyfish is expanding our AI ecosystem 🚀 We’ve added new integrations with Qodo, Claude Review, and Augment Code Review to bring engineering leaders more visibility into how AI is being used across the software development lifecycle. With these integrations, you can now track: - Adoption of AI code review agents - Usage across repositories - PRs receiving AI-assisted feedback, and more… ...all from within the Jellyfish AI Impact dashboard. We’re excited to continue helping teams understand and measure the real impact of AI! And we’re sending big congratulations to the Qodo team on their recent fundraise. 🎉 Learn about our newest integrations here: https://lnkd.in/g7JJ9KCp

"Implement AI at your organization and get 10X ROI." Developer Productivity Manager at SPS Commerce, Ryan Erickson, gives his take on this and the journey his team has been on. Watch the full recording here: https://lnkd.in/g8VnBSQQ

New data just dropped on our Jellyfish AI Engineering Trends page! Updated through end of February and now covering 37 million pull requests. A few highlights from this month's version: AUTONOMOUS AGENT ACCELERATION I teased this earlier in the month, but we're seeing exponential growth in autonomous agent adoption, particularly in the top companies: P90 went from 10% to 14.5%, while the median is at ~2%. The gap between the leaders and the rest of the pack is widening – and accelerating. PR THROUGHPUT GAINS In terms of raw code throughput, companies with the strongest adoption of AI coding tools continue to see about 2x gains. In addition we're seeing strong gains (30-60%) even with modest adoption. We may see these gains saturate as other bottlenecks like PR reviews and quality start to play a bigger role, and as teams struggle to get past the "agentic barrier" of moving from interactive to autonomous coding. IS QUALITY AN ISSUE? We're still seeing fairly small impacts on the quality front (+5-11% increase in reverted code as AI adoption increases), but these numbers have been climbing. We're currently digging into many other signals to understand more deeply how AI coding tools are impacting review process, security, and quality – stay tuned! Check out the AI Engineering Trends page for the full set of benchmarks!

Jellyfish Research just released February data exploring how AI is impacting the software development lifecycle. 🔥 Compiled from 1000+ companies, 200K engineers, 37M PRs, the results of the largest study of its kind comprise real-world engineering signals about how organizations and developers are using AI tools across the SDLC. The report digs into both AI adoption and impact and finds: - 67% median AI adoption across companies - 27% of companies are generating a majority of their code with AI - 2x PR throughput for top AI adopters - 14% of PR throughput from autonomous agents for top adopters 👉 Benchmark your organization’s AI adoption and usage maturity against the full report's data here: https://lnkd.in/gFAyfhw2

"Jellyfish gives me the autonomy to treat 'Help' as a piece of the intelligence we provide. Because we are an intelligence platform, our documentation can’t just be a manual; it has to be smart. I’m encouraged to find creative ways to explain how AI tools change the engineering lifecycle. Experimenting with new ways to deliver those insights directly within the user’s workflow makes the work feel less like 'writing' and more like 'experience design.'" Learn more about Senior Documentation Manager, Christine Larkin, and the one project that highlights why she enjoys working at Jellyfish: https://lnkd.in/gQf8SqJx

We turned on AI code review using Cursor Bugbot for 18 engineers. Their PR throughput more than doubled. 📈 Not because they worked more. Not because they wrote more code. Because they started shipping it differently. That result is easy to misinterpret. More PRs does not automatically mean more productivity. So instead of guessing, we designed an experiment to understand what actually changed. 🧪 Find out the results in this article by Jellyfish Senior Software Irene N.: https://lnkd.in/g3bZNdDg

I've been talking with a lot of engineering leaders lately about metrics, visibility, and what comes next, especially as AI continues to play a larger role. Engineering dashboards are powerful, but when the insights they surface are paired with a strong leadership perspective, you can: - interpret the signal - build alignment - drive action - measure impact Read more in the latest edition of Jellyfish's The Current. Link in comments.