#developer-productivity

#developer-productivity

Gill's prediction has come true: developers are now regularly using AI coding assistants to generate code, but the output is often buggy, forcing engineers to spend a lot of time on corrections. CodeRabbit can help catch some of the errors. The business has been growing 20% a month and is now making more than $15 million in annual recurring revenue (ARR), according to Gill.

She called vibe coding a beautiful, endless cocktail napkin on which one can perpetually sketch ideas. But dealing with AI-generated code that one hopes to use in production can be "worse than babysitting," she said, as these AI models can mess up work in ways that are hard to predict. She had turned to AI coding in a need for speed with her startup, as is the promise of AI tools.

Just over a hundred visitors had crowded into an office building in the Duboce Triangle neighborhood for a showdown that would pit teams armed with AI coding tools against those made up of only humans (all were asked to ditch their shoes at the door). The hackathon was dubbed "Man vs. Machine," and its goal was to test whether AI really does help people code faster-and better.

AI-assisted developers produced three to four times more code than their unassisted peers, but also generated ten times more security issues. "Security issues" here doesn't mean exploitable vulnerabilities; rather, it covers a broad set of application risks, including added open source dependencies, insecure code patterns, exposed secrets, and cloud misconfigurations. As of June 2025, AI-generated code had introduced over 10,000 new "security findings" per month in Apiiro's repository data set, representing a 10x increase from December 2024, the biz said.

GitLab has launched the public beta of its GitLab Duo Agent Platform, an orchestration tool that enables developers to collaborate asynchronously with AI agents across the DevSecOps lifecycle. The platform, now available to GitLab.com Premium and Ultimate customers as well as self-managed installations, transforms traditional, linear development workflows into dynamic, multi-agent systems where AI handles routine tasks such as refactoring, security scanning, and research, while developers focus on complex problem-solving.

The short answer: AI isn't replacing developers-it's changing what developers do. While AI is undoubtedly transforming the programming landscape, we're witnessing an evolution in how software is built, with AI serving as a powerful collaborator rather than a replacement. Understanding this shift is crucial for anyone concerned about the future of programming jobs. The Current State of AI in Development Today's AI coding tools are impressively capable.

84% of developers now use or plan to use AI in their workflow, but only 33% trust the accuracy of AI outputs. This trust gap reflects real-world experience with AI's limitations.

Activision has slashed build times for COD: MWII in half, enhancing developer efficiency by identifying inefficiencies through MSVC Build Insights.

What started as a hedgehog-led love story is now a global community powerhouse, and these murals are its loudest statement yet. This transition illustrates how niche projects can evolve into significant movements.

The third preview release of .NET 10 introduces significant enhancements across various components, aiming to boost developer productivity and streamline application performance.