Make troubleshooting in IntelliJ faster | All DPE Summit videos released | Your toolchain IS production | AI boosts speed at the price of security | Plus, 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

IntelliJ + Develocity = Faster Troubleshooting

You may have noticed some recent buzz about our Develocity IntelliJ plugin—which is about to cross 11,000 downloads and is averaging over 200% month-over-month growth! We're excited about the popularity of this extremely handy tool for troubleshooting failures and performance issues, and we have some resources you might like... 


Nov-13 webinar: Using IntelliJ with Develocity AI for faster troubleshooting


Join Trisha Gee and Laurent Ploix for a deep-dive into how to get the most out of this plugin, as well as a sneak preview of some upcoming features—like connecting our Develocity MCP server to leverage AI-powered troubleshooting for AI-powered projects!


Sign up for the event


We’re planning another live session with the JetBrains team in early 2026 to share new features and broader ecosystem support, so stay tuned for that!


You can also get a head start on using the Develocity IntelliJ plugin by reading through this blog post by the Gradle engineering team. It provides additional details and even real-world use cases. Otherwise, see you Nov-13th!


Register here

DPE SUMMIT WRAP-UP

🌉 DPE Summit 2025 - All recordings now available!

We're happy to share that all recordings from DPE Summit 2025 are now available. For extra convenience, we've tagged each talk with the relevant topics so you can spend less time searching and more time watching:

  • AI - Metrics

  • AI - Tools

  • Build/Test Acceleration

  • CI/CD Pipelines

  • Develocity

  • DORA & Shift Left

  • DPE Metrics & Platforms

  • DPE Research

  • IDE and Tooling

  • Observability

  • Testing

  • Toolchain Reliability

And for those wondering about DPE Summit 2026, we’re already planning big things and will share more details in the new year. Happy watching learning!


Go to videos

EXPERT TAKES

Your toolchain IS production

Java Champion and Gradle developer advocate Brian Demers has something to tell you: there’s a dangerous blind spot when it comes to organizational observability into internal software systems and toolchains. 


After all, when was the last time anyone argued against the need for real-time observability (e.g. Datadog) into production applications like Amazon or Spotify?


Nowadays, no one would find this acceptable; yet we frequently—if innocently—forget to apply this operational rigor to our software toolchains. And this is having real-world effects, as seen in the recent Nx and npm toolchain attacks. As Brian says: 


"We should view every component related to the build, tests, CI pipelines, local build systems, and DevOps tools—what I refer to collectively as the toolchain—as production systems."


Check out his blog post and accompanying DPE Summit session video!


Learn more

BEST PRACTICES

The "Live fast, die young..." philosophy isn’t good for business when AI coding assistants value speed over security

(Image source)


Agentic AppSec provider Apiiro recently published some interesting findings regarding the impact of AI coding assistants on risk exposure. Based on data from "thousands of developers" in Fortune 50 enterprises, Apiiro sums up their findings neatly as:


"[We found that] AI tools driving 4× speed are also generating 10× more security risks. Pull requests are ballooning, vulnerabilities are multiplying, and shallow syntax errors are being replaced with costly architectural flaws."


Some of the main highlights of their research include:

  • More commits with fewer PRs indicate that instead of shipping smaller changes more frequently, AI coding assistants tend to lump more changes into a single PR, increasing the "blast radius per merge" threat and leading to review process inefficiencies.

  • AI coding assistants deliver code 4x faster, but with 10x more flaws and a 33% drop in PR volume as a result—large, less frequent PRs push against DORA’s work in small batches capability.

  • AI is great for handling small syntax errors and logic bugs, but it comes at the cost of major architectural "time bombs" that tend to escape reviews and automated testing.

The bottom line: we need to expect the unexpected when working with AI. This is where deep toolchain observability, DORA metrics, Continuous Delivery practices, and AI-powered technologies to manage AI-powered code enter the spotlight. After all, without observability combined with best practices, you have no idea how your investment into AI is helping—or harming—your business.


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.

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