JFrog and Gradle team up on Feb-19  | Should we worry about AI overwhelming our delivery pipelines? | When CI infra becomes a hidden tax on AI | Insights from Dave Farley | Over 30,000 devs aren’t wrong | Open DPE and AI positions around the world!

Want to connect with Gradle? Email me at owhite@gradle.com, and have a productive month!

FEATURED UPCOMING EVENT

🌐 Feb-19: JFrog and Gradle team up to help you automate governance from build to release

AI-accelerated development is flooding the software supply chain, making the manual effort required to verify the chain of custody for “Every. Single. Artifact.” physically impossible. For engineering leaders, this creates a critical blind spot: while standard security scans tell you what is inside your code, they often miss the integrity of the build process itself.


Join Gradle and JFrog on Feb-19 as we introduce the emerging practice of Continuous Governance, Risk, and Compliance (GRC) for DevOps—or "DevGovOps." We will demonstrate how the integration between Develocity Provenance Governor and JFrog AppTrust creates an immutable system of record for your software, ensuring that only verified, policy-compliant code reaches production.


Oh, and if you missed “CI Without the Wait: Scale Throughput with Universal Cache”, you can watch the recording.
Register here

EXPERT TAKES

Amazon: Your AI coding assistants will overwhelm your delivery pipeline

In a recent Amazon Enterprise Strategy blog, industry experts highlight a growing tension in the modern software supply chain: AI is making code generation nearly effortless, but the infrastructure required to validate and deliver that code is hitting a breaking point.


As developers double their code output using AI assistants, the sheer volume of commits, builds, and tests is surging. For engineering leaders, this creates a "Developer Productivity Paradox." If your delivery pipeline isn't optimized for this 10x increase in activity, the perceived gains from AI at the IDE level will be swallowed by downstream bottlenecks, longer wait times, and exploding CI costs.


To remain competitive, shifting to a high-velocity DPE model is no longer optional—it is a strategic requirement for the GenAI era. We’ve broken down the steps you need to take to ensure your infrastructure can handle the tsunami.
Learn more

IDEAS & INSIGHTS

Is your CI infrastructure the hidden tax on your AI strategy?

The physical reality of moving massive build artifacts across global networks as AI-driven code volume scales is creating a new category of latency—and a massive line item on the CI infrastructure bill.


In this deep dive, Build Artifact CDN: Strategic Infrastructure for AI-Driven DevOps, we explore why traditional caching is no longer sufficient for the high-velocity, globally-distributed teams of 2026. When your developers ship commits at 4x their previous rate, every minute spent re-downloading dependencies or waiting for remote artifacts is a direct hit to your ROI.


By treating build artifacts with the same strategic importance as a content delivery network (CDN) treats web assets, leaders can:

  • Decouple throughput from geography to empower 24/7 global development without regional lag.

  • Slash cloud egress costs by optimizing how and where data is stored and retrieved.

  • Future-proof the pipeline for the even greater data demands of agentic AI and autonomous dev agents.
Read more

EXPERT TAKES

Dave Farley: AI makes it easier than ever to drown in your own code base

(image source)


In this short video by our friend and industry luminary, Dave Farley, we hear his no-nonsense perspective on the upcoming "maintenance nightmare” fueled by AI.  


While many celebrate AI for initial coding speed, maintenance represents 50–80% of total cost of ownership. A controlled study of 151 professionals reveals that AI doesn’t automatically improve code quality; developer skill remains the primary driver of maintainability. 


For leaders, prioritizing short-term feature velocity via AI is a costly tradeoff if it ignores downstream evolution. True engineering ROI requires focusing on code health and discipline—not just how fast we can generate "AI slop."
Watch now

BEST PRACTICES

How 30,000+ engineers are troubleshooting builds and optimizing performance via one IntelliJ plugin

Our popular Develocity IntelliJ IDEA plugin recently surpassed 33,000 downloads, highlighting a significant industry trend toward protecting developer "cognitive flow." 


High-performing organizations are increasingly recognizing that the workspace itself is a critical lever for engineering ROI, as keeping developers in their IDE prevents the productivity leaks caused by context-switching. 


By integrating real-time performance insights directly into the coding environment, teams are resolving build failures faster and stabilizing delivery cycles without the overhead of external tools. 


For a deeper look at how this shift toward in-flow troubleshooting impacts organizational throughput, you can explore the recording of our AI-driven troubleshooting session.
Learn more

CAREER OPPORTUNITIES

DPE (and AI) job openings

The industry needs you! You might find your dream role among these job openings related to DPE, AI developer productivity, and engineering leadership.


NOTE: These postings are active at the time of sending but are subject to change.


Gradle’s customers are hiring: 

Other open positions around the world:

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