The Linux kernel community is wrestling with a new frontier: using large language models to sift through mountains of code. A recent summit laid bare the challenges and tantalizing potential.
GitLab's command-line interface, `glab`, is evolving from a developer staple to an AI's direct conduit to project data. This integration promises to dramatically reduce the friction AI agents face when interacting with codebases.
GitHub Copilot has processed over 60 million reviews, a 10x surge in less than a year. More than one in five code reviews on GitHub now involve an agent, a trend that's outpacing human review capacity and introducing hidden technical debt.
AI-powered coding isn't just about writing code faster; it's about a fundamental platform shift. But what happens when the initial hype fades and the real work of scaling begins? This piece dives into the 'Day 2 problems' that emerge when AI adoption matures.